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Exploring IoT: Industry-Specific Success Stories and Fascinating Use Cases
When you hear the word ” IoT ,” it may seem like something from a faraway world, but in reality, there are many things that have already permeated our daily lives. In order to understand the future of IoT, it is necessary to know in what fields IoT is currently being used. In this article, we will introduce what IoT technology can do and various examples of how IoT is used in businesses and homes.
We also explain the benefits and points to note when introducing IoT, so please read until the end.

Basic knowledge of IoT
Before introducing specific use cases of IoT, let’s first deepen our understanding of what IoT is.
What is IoT?
IoT is an acronym for “Internet of Things,” and is translated into Japanese as “Internet of Things.” In other words, it is a system that connects various things around us to the Internet.
Until recently, it was common to connect to the Internet from a computer at home or work. However, with the spread of mobile devices such as smartphones and tablets, it has become easier to access the Internet from anywhere. Furthermore, “smart home appliances” such as televisions and air conditioners that can be connected to the Internet are appearing one after another, making it possible to operate devices remotely even when you are far away.
There are great expectations for technology that utilizes IoT, as it has the potential to make life even more convenient and enrich society. Against this background, the IoT market continues to grow year by year, and is expected to further expand in the future.

How IoT works
Various home appliances and equipment targeted by IoT are equipped with sensors, cameras, etc. These sensors and cameras sense and collect information such as the condition of objects and the surrounding environment, and transmit this data to people and objects via the Internet. The sensors installed vary depending on the device, such as light sensors, temperature sensors, and acceleration sensors.
Let’s take smartwatches as an easy-to-understand example. A smartwatch acquires information such as biometric data such as heart rate and blood pressure, as well as the number of steps taken, based on sensors attached to the watch and GPS. That data is then sent to your smartphone via the internet or stored in the cloud, where it accumulates. The data collected in this way is analyzed by AI, converted into easy-to-understand information such as graphs, and then presented to the user again.
Until now, when selling something, the functionality and price of the item itself were considered to be the main sales criteria to determine whether it would sell or not. However, by introducing IoT, manufacturers are now able to add new added value to existing products.

What can be achieved with IoT technology
By using IoT technology, you can do four main things.
The keyword for what can be done with IoT is “remote”.
Now, let’s introduce one by one what you can do using IoT technology.

Remote control
In recent years, many IoT home appliances have been released. Typical examples include lighting equipment and air conditioners. By using home smart devices and sensors, you can remotely control lights, air conditioners, home appliances, etc. It also helps prevent people from forgetting to turn off these devices, improving safety and efficiency. Remote control of IoT devices will make our lives more comfortable.
You can also use smartphone apps to boil a bath or cook rice from anywhere. In this way, remote control of IoT devices makes life more comfortable.
Furthermore, remote pairing allows devices that are physically separated to communicate with each other.
In the medical field, online medical treatment is conducted using “wearable devices” that can be worn on clothing or wrapped around the hand.
The unique feature is that patients can wear a wearable device to monitor their health status, such as their blood pressure, in real time. This has the advantage of being able to provide medical examinations and guidance in remote locations such as the patient’s home and the hospital.
In addition, at manufacturing sites, sensors and control equipment are paired with PCs in the factory for data communication, and real-time monitoring and equipment control are performed from remote locations.

Detecting the movement of objects from a distance
By utilizing IoT, it is also possible to detect and monitor the movement of things from a distance.
It is also possible to construct a remote monitoring system using cameras and sensors.
Various sensors have been developed, including sensors that detect people and movement, and sensors that detect temperature.
The following are examples of what can be done by combining such sensors and IoT technology.
- Activate the camera and take images only when someone passes by
- Send signals to other devices and play alarms, etc.
Autonomous driving, which applies the brakes when it detects a pedestrian, is also an example of the use of IoT technology to detect the movement of objects.

Detect the status remotely
Using IoT, it is possible to detect conditions from a remote location, but even in this case, sensors are used.
For example, it uses temperature and humidity sensors to sound an alert when a certain value is exceeded.
Soil sensors also allow agriculture to monitor soil moisture, temperature, and nutrient levels.
Accelerometers that detect vibration, shock, and motion are used for structural monitoring of buildings, bridges, and vehicles.

Examples of IoT usage by industry
Now that we have a deeper understanding of IoT, let’s take a look at more specific use cases of IoT by industry. Convenient products and services with hidden potential are appearing one after another, including products that may become mainstream in the future.

Examples of use in the agricultural field
In the agricultural field, “smart agriculture,” which reduces the labor of agricultural work, is attracting attention. Smart agriculture is next-generation agriculture that uses cutting-edge technology that enables labor-saving and high-quality production. Specifically, sensors collect information on things like solar radiation and soil conditions, and calculate the timing of watering and fertilization, as well as the optimal amount of fertilizer.
In the agricultural industry, where labor shortages are becoming a major issue in the future due to the aging of workers and the lack of successors, there are high hopes for smart agriculture. By combining IoT with robot technology, it is possible to automatically water or spread fertilizer based on calculated data. It is not a dream to be able to automatically determine the harvest time, harvest, box and ship. It is expected that this technology will reduce the workload, improve productivity, and solve the problem of human resource shortages.

Examples of use in the medical field
One example of IoT being utilized in the medical field is wearable devices. This allows patients to wear a device connected to the Internet, which measures biological data such as body temperature, blood pressure, and pulse, and converts it into data.
If it becomes easier for medical institutions to collect detailed biological data on patients, it will help them make accurate diagnoses and provide appropriate treatment. When something abnormal is detected, it will help you make a quick diagnosis and take appropriate measures.
In recent years, there has been a serious shortage of doctors in the medical field, and the increasing burden placed on medical personnel has become a problem. IoT in medical institutions is an area of great interest from the perspective of improving the working environment for doctors. IoT specialized in medical care is called “IoMT (Internet of Medical Things),” and research and development is progressing to provide better medical services.

Examples of use in the logistics industry
In the logistics field, IoT is used for warehouse management, picking, delivery, etc. DX that uses the latest technologies such as IoT is called “Logistics 4.0” by the industry’s unique name.
For example, you may have heard of technology that uses robotics for picking tasks, automatically transporting shelves containing products to staff. This allows staff to quickly locate specific products without having to walk around a large warehouse. Furthermore, by attaching IC tags to the materials managed in the distribution warehouse, it is possible to manage the materials using drones flown into the sky.
In the area of delivery, a transportation management system called “TMS” has emerged that comprehensively manages transportation and delivery. This helps you plan efficient dispatches and accurately calculate freight and labor costs. Utilizing the GPS function, you can understand the location of each delivery vehicle in real time and guide drivers to the optimal route based on traffic congestion information. Additionally, you can manage delivery vehicle lease contracts and calculate expenses.
Due to the increased use of online shopping, the logistics industry is currently facing increased supply and complexity. It is also true that the burden on each worker is increasing, as the number of delivery drivers is decreasing due to the declining birthrate and aging of the population.

Examples of usage in the manufacturing industry
The manufacturing industry is an industry where work automation is progressing, with the introduction of industrial robots. With the advent of robots that can operate 24 hours a day, 365 days a year, productivity improvements and quality stabilization have been realized. IoT in the manufacturing industry is characterized by the collaboration of robotics with AI and M2M (machine-to-machine).
Introducing IoT to the manufacturing industry enables visualization, control, and automation. “Visualization” refers to visualizing the information collected by sensors. It collects information that is difficult to express, such as handwritten data and the amount of force applied during manufacturing, and visualizes it for easy analysis. “Control” uses the analysis results to help things operate efficiently. Furthermore, “automation” is the ability to automatically perform such control using AI and other means.
By introducing IoT into factories, we can also aim to create a ” smart factory ” (a thinking factory). A smart factory is a system that connects the systems and equipment in a factory to the Internet to visualize and automate various tasks. You can expect to improve productivity by understanding the operating status of your factory in detail and placing human resources in the appropriate locations. If you use a function to manage the status of equipment and issue an alert before it breaks down, you will be able to carry out maintenance and repairs as necessary and minimize the damage caused by equipment failure.

Familiar IoT usage examples
We have introduced examples of IoT usage in companies such as agriculture, medical care, and manufacturing, but now we will introduce more familiar usage examples of IoT that are closely related to daily life.

Multifunctional and versatile smart speaker
Multifunctional and versatile smart speakers are attracting attention as an example of IoT applications.
- Amazon’s Alexa
- Google’s “Google Assistant”
- Apple’s “Siri”
etc. are famous.
Smart speakers not only control IoT devices and home appliances, but also come with a variety of functions.
Additionally, more and more people are using smart speakers as part of their morning routine, as they can play music and provide audio information such as news, weather, traffic information, and stock prices.
You can also use your smart speaker to order products from online stores such as Amazon.

Smart locks are very popular among the dual-income generation.
Smart locks that utilize IoT are a convenient tool that is popular among the dual-income generation.
No more forgetting your house keys, forgetting to give them to family members, or worrying about losing your keys.
Depending on the product, it is also possible to manage car keys.
You can use the dedicated app to check the unlock history of your keys, and if there is unauthorized access, you will receive an alert notification, so you can also take security measures.

Refrigerator that lets you know how much stock is left
One of the home appliances that uses IoT is a refrigerator that allows you to see how much stock is left.
It has a built-in camera and weight sensor that monitors the remaining amount of food and drinks and sends this information through an app.
It is also possible to send an alert when food ingredients are nearing their expiry date.
You can also check the list of ingredients and drinks and create a shopping list by linking with the smartphone app.
Using IoT refrigerators not only contributes to reducing food waste, but also contributes to household finances.

Wearable underwear that shows your child’s health status
Wearable underwear that utilizes IoT has built-in sensors that measure body temperature, heart rate, breathing rate, etc.
This allows parents to monitor their children with peace of mind, even from a distance, as they can monitor their child’s health status in real time.
When an abnormality is detected, an alert notification will be sent via the smartphone app.
Furthermore, wearable underwear has been developed that is breathable, lightweight, and waterproof, making it comfortable to wear.
It seems that the day when it will be used for nursing care will be in the near future.

A GPS device that lets you know where your child is when they go to and from school.
One system that uses IoT to manage children going to and from school is a GPS device that children carry around with them.
It is useful for parents who want to check their child’s safety because they can know their child’s whereabouts in real time.
You can receive alerts from the app if you go outside of the range pre-set on your device.
This allows parents to quickly locate their children even if they do not return home or become lost.

Interesting IoT usage examples
So far, we have introduced typical IoT usage cases.
I’m sure there are many that you use or have heard of.
From here, we will introduce three interesting IoT usage cases that have become popular and have attracted attention.

MAMORIO
“MAMORIO” is an IoT device that can be used in conjunction with a smartphone to prevent the loss of items and confirm location information.
By attaching it to your keys, wallet, or your luggage, you can check your location information on your smartphone.
You can also always check where your pet is by attaching MAMORIO to your pet’s collar.
You can also set the app to notify you when your pet leaves a certain range.
You can also attach it to your car, so you can easily find it even in a large parking lot.

Foop
foop is a smart device that will change the way you grow vegetables.
It automatically manages the environmental conditions necessary for growing vegetables, such as light, water, and temperature, and supports the growth of vegetables.
You can operate it from your smartphone and check the progress of training and environmental conditions in real time, so you can go to work or travel with peace of mind.
It also automatically sets the optimal growing program for the type of vegetable.
The stylish design allows you to grow vegetables even in limited space such as in urban areas.

Crunchy machine
“Kari Kari Machine” is a service that supports pet meal management using IoT devices.
The Karikari Machine allows you to set the amount of food according to your pet’s weight and age, and can also record the amount eaten. It is also possible to adjust the amount of food by remote control.
You can accurately manage your pet’s diet even when you are away.
Additionally, if your pet overeats while you are away, you will receive a notification on your smartphone, so you can take immediate action.

Benefits of IoT for businesses
From here, for those who are positively considering the introduction of IoT, we will introduce the benefits that the use of IoT brings to companies.

Enables improved quality and productivity
By utilizing IoT, quality and productivity can be improved in many industries such as manufacturing, logistics, agriculture, and construction.
For quality improvement, IoT devices can be used to monitor product quality in real time.
If a quality abnormality occurs, by setting up an alert to be sent, you can prevent the occurrence of defective products at an early stage and ensure quality.
When it comes to improving productivity, IoT devices can be used to streamline work processes and reduce production line downtime.

Can reduce the number of workers
By utilizing IoT, it may be possible to reduce the number of workers required for some tasks.
Particularly at manufacturing sites, IoT sensors can be used to predict machine failures and perform necessary maintenance in advance, reducing the number of maintenance workers.
In some cases, automating tasks can free up your time for other tasks.

Know the issues to consider when introducing IoT
Although we have introduced the benefits of using IoT, there are also issues to consider when implementing it.
We will explain the five issues in an easy-to-understand manner.

Radio wave trouble
Radio wave troubles are an issue when introducing IoT.
Communication may become unstable due to radio wave interference, external noise, radio wave shielding, etc.
Radio wave problems may be resolved by taking measures such as selecting an appropriate installation location, setting the frequency band, and selecting the antenna.
It is also an effective method to obtain support from engineers who have technical knowledge about IoT device communication specifications and radio wave troubles.

Power supply trouble
Power supply problems are a major issue when introducing IoT.
Since power needs to be constantly supplied, power supply problems can affect the entire IoT system.
- Problems where power is not supplied to IoT devices due to power outages due to earthquakes, disasters, etc.
- An issue where an abnormality occurs in the power supply circuit, causing IoT devices to malfunction.
To solve these problems, it is necessary to have a backup power supply, such as an uninterruptible power supply or battery.

Securing human resources familiar with IoT
One of the issues to consider when introducing IoT is securing knowledgeable human resources.
Implementing an IoT system requires a wide range of knowledge, including hardware, software, cloud, and data analysis.
However, depending on the industry, there is a limited number of experienced human resources available for IoT technology, so it may be difficult to secure human resources.
IoT technology is evolving rapidly, so it is important to always learn the latest knowledge.
It is also necessary to utilize support from experts such as consulting firms, and to develop human resources in-house by utilizing online learning, training, seminars, etc.

Security trouble
Security measures are important when introducing IoT.
Unauthorized access to an IoT system may result in damage such as system misuse or leakage of personal information.
- Encrypt data to prevent information leaks
- Achieve secure authentication using multi-factor authentication
- Update regularly and fix vulnerabilities
- Continuously implement security measures such as introducing security monitoring tools
When it comes to security, the measures mentioned above are key.
Privacy trouble
When introducing IoT, it is also important to pay attention to privacy.
Since users’ actions and situations are recorded and analyzed, there is a possibility that this may violate the Personal Information Protection Act.
It is also necessary to take measures to prevent data leaks such as personal information leaks.
- Building a system that complies with laws and regulations regarding personal information protection
- Implement security measures such as data encryption and access control
- When collecting personal information, keep it to the minimum necessary and clarify the purpose of use.
Privacy measures, like security measures, require the above consideration from the system construction stage.

Summary
This time, we have introduced some well-known and interesting IoT usage cases.
Incorporating IoT products at home can lead to improved quality of life, such as reducing the burden of housework and reducing anxiety for families with children.
While the introduction of IoT in companies has security and privacy issues, there are many benefits such as reduced labor costs, increased efficiency, improved productivity, and improved safety.

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June 29, 2024
Exploring IoT: Industry-Specific Success Stories and Fascinating Use Cases
When you hear the word ” IoT ,” it may seem like something from a faraway world, but in reality, there are many things that have already permeated our daily lives. In order to understand the future of IoT, it is necessary to know in what fields IoT is currently being used. In this article, we will introduce what IoT technology can do and various examples of how IoT is used in businesses and homes.
We also explain the benefits and points to note when introducing IoT, so please read until the end.

Basic knowledge of IoT
Before introducing specific use cases of IoT, let’s first deepen our understanding of what IoT is.
What is IoT?
IoT is an acronym for “Internet of Things,” and is translated into Japanese as “Internet of Things.” In other words, it is a system that connects various things around us to the Internet.
Until recently, it was common to connect to the Internet from a computer at home or work. However, with the spread of mobile devices such as smartphones and tablets, it has become easier to access the Internet from anywhere. Furthermore, “smart home appliances” such as televisions and air conditioners that can be connected to the Internet are appearing one after another, making it possible to operate devices remotely even when you are far away.
There are great expectations for technology that utilizes IoT, as it has the potential to make life even more convenient and enrich society. Against this background, the IoT market continues to grow year by year, and is expected to further expand in the future.

How IoT works
Various home appliances and equipment targeted by IoT are equipped with sensors, cameras, etc. These sensors and cameras sense and collect information such as the condition of objects and the surrounding environment, and transmit this data to people and objects via the Internet. The sensors installed vary depending on the device, such as light sensors, temperature sensors, and acceleration sensors.
Let’s take smartwatches as an easy-to-understand example. A smartwatch acquires information such as biometric data such as heart rate and blood pressure, as well as the number of steps taken, based on sensors attached to the watch and GPS. That data is then sent to your smartphone via the internet or stored in the cloud, where it accumulates. The data collected in this way is analyzed by AI, converted into easy-to-understand information such as graphs, and then presented to the user again.
Until now, when selling something, the functionality and price of the item itself were considered to be the main sales criteria to determine whether it would sell or not. However, by introducing IoT, manufacturers are now able to add new added value to existing products.

What can be achieved with IoT technology
By using IoT technology, you can do four main things.
The keyword for what can be done with IoT is “remote”.
Now, let’s introduce one by one what you can do using IoT technology.

Remote control
In recent years, many IoT home appliances have been released. Typical examples include lighting equipment and air conditioners. By using home smart devices and sensors, you can remotely control lights, air conditioners, home appliances, etc. It also helps prevent people from forgetting to turn off these devices, improving safety and efficiency. Remote control of IoT devices will make our lives more comfortable.
You can also use smartphone apps to boil a bath or cook rice from anywhere. In this way, remote control of IoT devices makes life more comfortable.
Furthermore, remote pairing allows devices that are physically separated to communicate with each other.
In the medical field, online medical treatment is conducted using “wearable devices” that can be worn on clothing or wrapped around the hand.
The unique feature is that patients can wear a wearable device to monitor their health status, such as their blood pressure, in real time. This has the advantage of being able to provide medical examinations and guidance in remote locations such as the patient’s home and the hospital.
In addition, at manufacturing sites, sensors and control equipment are paired with PCs in the factory for data communication, and real-time monitoring and equipment control are performed from remote locations.

Detecting the movement of objects from a distance
By utilizing IoT, it is also possible to detect and monitor the movement of things from a distance.
It is also possible to construct a remote monitoring system using cameras and sensors.
Various sensors have been developed, including sensors that detect people and movement, and sensors that detect temperature.
The following are examples of what can be done by combining such sensors and IoT technology.
- Activate the camera and take images only when someone passes by
- Send signals to other devices and play alarms, etc.
Autonomous driving, which applies the brakes when it detects a pedestrian, is also an example of the use of IoT technology to detect the movement of objects.

Detect the status remotely
Using IoT, it is possible to detect conditions from a remote location, but even in this case, sensors are used.
For example, it uses temperature and humidity sensors to sound an alert when a certain value is exceeded.
Soil sensors also allow agriculture to monitor soil moisture, temperature, and nutrient levels.
Accelerometers that detect vibration, shock, and motion are used for structural monitoring of buildings, bridges, and vehicles.

Examples of IoT usage by industry
Now that we have a deeper understanding of IoT, let’s take a look at more specific use cases of IoT by industry. Convenient products and services with hidden potential are appearing one after another, including products that may become mainstream in the future.

Examples of use in the agricultural field
In the agricultural field, “smart agriculture,” which reduces the labor of agricultural work, is attracting attention. Smart agriculture is next-generation agriculture that uses cutting-edge technology that enables labor-saving and high-quality production. Specifically, sensors collect information on things like solar radiation and soil conditions, and calculate the timing of watering and fertilization, as well as the optimal amount of fertilizer.
In the agricultural industry, where labor shortages are becoming a major issue in the future due to the aging of workers and the lack of successors, there are high hopes for smart agriculture. By combining IoT with robot technology, it is possible to automatically water or spread fertilizer based on calculated data. It is not a dream to be able to automatically determine the harvest time, harvest, box and ship. It is expected that this technology will reduce the workload, improve productivity, and solve the problem of human resource shortages.

Examples of use in the medical field
One example of IoT being utilized in the medical field is wearable devices. This allows patients to wear a device connected to the Internet, which measures biological data such as body temperature, blood pressure, and pulse, and converts it into data.
If it becomes easier for medical institutions to collect detailed biological data on patients, it will help them make accurate diagnoses and provide appropriate treatment. When something abnormal is detected, it will help you make a quick diagnosis and take appropriate measures.
In recent years, there has been a serious shortage of doctors in the medical field, and the increasing burden placed on medical personnel has become a problem. IoT in medical institutions is an area of great interest from the perspective of improving the working environment for doctors. IoT specialized in medical care is called “IoMT (Internet of Medical Things),” and research and development is progressing to provide better medical services.

Examples of use in the logistics industry
In the logistics field, IoT is used for warehouse management, picking, delivery, etc. DX that uses the latest technologies such as IoT is called “Logistics 4.0” by the industry’s unique name.
For example, you may have heard of technology that uses robotics for picking tasks, automatically transporting shelves containing products to staff. This allows staff to quickly locate specific products without having to walk around a large warehouse. Furthermore, by attaching IC tags to the materials managed in the distribution warehouse, it is possible to manage the materials using drones flown into the sky.
In the area of delivery, a transportation management system called “TMS” has emerged that comprehensively manages transportation and delivery. This helps you plan efficient dispatches and accurately calculate freight and labor costs. Utilizing the GPS function, you can understand the location of each delivery vehicle in real time and guide drivers to the optimal route based on traffic congestion information. Additionally, you can manage delivery vehicle lease contracts and calculate expenses.
Due to the increased use of online shopping, the logistics industry is currently facing increased supply and complexity. It is also true that the burden on each worker is increasing, as the number of delivery drivers is decreasing due to the declining birthrate and aging of the population.

Examples of usage in the manufacturing industry
The manufacturing industry is an industry where work automation is progressing, with the introduction of industrial robots. With the advent of robots that can operate 24 hours a day, 365 days a year, productivity improvements and quality stabilization have been realized. IoT in the manufacturing industry is characterized by the collaboration of robotics with AI and M2M (machine-to-machine).
Introducing IoT to the manufacturing industry enables visualization, control, and automation. “Visualization” refers to visualizing the information collected by sensors. It collects information that is difficult to express, such as handwritten data and the amount of force applied during manufacturing, and visualizes it for easy analysis. “Control” uses the analysis results to help things operate efficiently. Furthermore, “automation” is the ability to automatically perform such control using AI and other means.
By introducing IoT into factories, we can also aim to create a ” smart factory ” (a thinking factory). A smart factory is a system that connects the systems and equipment in a factory to the Internet to visualize and automate various tasks. You can expect to improve productivity by understanding the operating status of your factory in detail and placing human resources in the appropriate locations. If you use a function to manage the status of equipment and issue an alert before it breaks down, you will be able to carry out maintenance and repairs as necessary and minimize the damage caused by equipment failure.

Familiar IoT usage examples
We have introduced examples of IoT usage in companies such as agriculture, medical care, and manufacturing, but now we will introduce more familiar usage examples of IoT that are closely related to daily life.

Multifunctional and versatile smart speaker
Multifunctional and versatile smart speakers are attracting attention as an example of IoT applications.
- Amazon’s Alexa
- Google’s “Google Assistant”
- Apple’s “Siri”
etc. are famous.
Smart speakers not only control IoT devices and home appliances, but also come with a variety of functions.
Additionally, more and more people are using smart speakers as part of their morning routine, as they can play music and provide audio information such as news, weather, traffic information, and stock prices.
You can also use your smart speaker to order products from online stores such as Amazon.

Smart locks are very popular among the dual-income generation.
Smart locks that utilize IoT are a convenient tool that is popular among the dual-income generation.
No more forgetting your house keys, forgetting to give them to family members, or worrying about losing your keys.
Depending on the product, it is also possible to manage car keys.
You can use the dedicated app to check the unlock history of your keys, and if there is unauthorized access, you will receive an alert notification, so you can also take security measures.

Refrigerator that lets you know how much stock is left
One of the home appliances that uses IoT is a refrigerator that allows you to see how much stock is left.
It has a built-in camera and weight sensor that monitors the remaining amount of food and drinks and sends this information through an app.
It is also possible to send an alert when food ingredients are nearing their expiry date.
You can also check the list of ingredients and drinks and create a shopping list by linking with the smartphone app.
Using IoT refrigerators not only contributes to reducing food waste, but also contributes to household finances.

Wearable underwear that shows your child’s health status
Wearable underwear that utilizes IoT has built-in sensors that measure body temperature, heart rate, breathing rate, etc.
This allows parents to monitor their children with peace of mind, even from a distance, as they can monitor their child’s health status in real time.
When an abnormality is detected, an alert notification will be sent via the smartphone app.
Furthermore, wearable underwear has been developed that is breathable, lightweight, and waterproof, making it comfortable to wear.
It seems that the day when it will be used for nursing care will be in the near future.

A GPS device that lets you know where your child is when they go to and from school.
One system that uses IoT to manage children going to and from school is a GPS device that children carry around with them.
It is useful for parents who want to check their child’s safety because they can know their child’s whereabouts in real time.
You can receive alerts from the app if you go outside of the range pre-set on your device.
This allows parents to quickly locate their children even if they do not return home or become lost.

Interesting IoT usage examples
So far, we have introduced typical IoT usage cases.
I’m sure there are many that you use or have heard of.
From here, we will introduce three interesting IoT usage cases that have become popular and have attracted attention.

MAMORIO
“MAMORIO” is an IoT device that can be used in conjunction with a smartphone to prevent the loss of items and confirm location information.
By attaching it to your keys, wallet, or your luggage, you can check your location information on your smartphone.
You can also always check where your pet is by attaching MAMORIO to your pet’s collar.
You can also set the app to notify you when your pet leaves a certain range.
You can also attach it to your car, so you can easily find it even in a large parking lot.

Foop
foop is a smart device that will change the way you grow vegetables.
It automatically manages the environmental conditions necessary for growing vegetables, such as light, water, and temperature, and supports the growth of vegetables.
You can operate it from your smartphone and check the progress of training and environmental conditions in real time, so you can go to work or travel with peace of mind.
It also automatically sets the optimal growing program for the type of vegetable.
The stylish design allows you to grow vegetables even in limited space such as in urban areas.

Crunchy machine
“Kari Kari Machine” is a service that supports pet meal management using IoT devices.
The Karikari Machine allows you to set the amount of food according to your pet’s weight and age, and can also record the amount eaten. It is also possible to adjust the amount of food by remote control.
You can accurately manage your pet’s diet even when you are away.
Additionally, if your pet overeats while you are away, you will receive a notification on your smartphone, so you can take immediate action.

Benefits of IoT for businesses
From here, for those who are positively considering the introduction of IoT, we will introduce the benefits that the use of IoT brings to companies.

Enables improved quality and productivity
By utilizing IoT, quality and productivity can be improved in many industries such as manufacturing, logistics, agriculture, and construction.
For quality improvement, IoT devices can be used to monitor product quality in real time.
If a quality abnormality occurs, by setting up an alert to be sent, you can prevent the occurrence of defective products at an early stage and ensure quality.
When it comes to improving productivity, IoT devices can be used to streamline work processes and reduce production line downtime.

Can reduce the number of workers
By utilizing IoT, it may be possible to reduce the number of workers required for some tasks.
Particularly at manufacturing sites, IoT sensors can be used to predict machine failures and perform necessary maintenance in advance, reducing the number of maintenance workers.
In some cases, automating tasks can free up your time for other tasks.

Know the issues to consider when introducing IoT
Although we have introduced the benefits of using IoT, there are also issues to consider when implementing it.
We will explain the five issues in an easy-to-understand manner.

Radio wave trouble
Radio wave troubles are an issue when introducing IoT.
Communication may become unstable due to radio wave interference, external noise, radio wave shielding, etc.
Radio wave problems may be resolved by taking measures such as selecting an appropriate installation location, setting the frequency band, and selecting the antenna.
It is also an effective method to obtain support from engineers who have technical knowledge about IoT device communication specifications and radio wave troubles.

Power supply trouble
Power supply problems are a major issue when introducing IoT.
Since power needs to be constantly supplied, power supply problems can affect the entire IoT system.
- Problems where power is not supplied to IoT devices due to power outages due to earthquakes, disasters, etc.
- An issue where an abnormality occurs in the power supply circuit, causing IoT devices to malfunction.
To solve these problems, it is necessary to have a backup power supply, such as an uninterruptible power supply or battery.

Securing human resources familiar with IoT
One of the issues to consider when introducing IoT is securing knowledgeable human resources.
Implementing an IoT system requires a wide range of knowledge, including hardware, software, cloud, and data analysis.
However, depending on the industry, there is a limited number of experienced human resources available for IoT technology, so it may be difficult to secure human resources.
IoT technology is evolving rapidly, so it is important to always learn the latest knowledge.
It is also necessary to utilize support from experts such as consulting firms, and to develop human resources in-house by utilizing online learning, training, seminars, etc.

Security trouble
Security measures are important when introducing IoT.
Unauthorized access to an IoT system may result in damage such as system misuse or leakage of personal information.
- Encrypt data to prevent information leaks
- Achieve secure authentication using multi-factor authentication
- Update regularly and fix vulnerabilities
- Continuously implement security measures such as introducing security monitoring tools
When it comes to security, the measures mentioned above are key.
Privacy trouble
When introducing IoT, it is also important to pay attention to privacy.
Since users’ actions and situations are recorded and analyzed, there is a possibility that this may violate the Personal Information Protection Act.
It is also necessary to take measures to prevent data leaks such as personal information leaks.
- Building a system that complies with laws and regulations regarding personal information protection
- Implement security measures such as data encryption and access control
- When collecting personal information, keep it to the minimum necessary and clarify the purpose of use.
Privacy measures, like security measures, require the above consideration from the system construction stage.

Summary
This time, we have introduced some well-known and interesting IoT usage cases.
Incorporating IoT products at home can lead to improved quality of life, such as reducing the burden of housework and reducing anxiety for families with children.
While the introduction of IoT in companies has security and privacy issues, there are many benefits such as reduced labor costs, increased efficiency, improved productivity, and improved safety.

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June 29, 2024
What is a smart factory? Explaining the advantages, disadvantages, issues, and examples!
Smart factories that make full use of IT technologies such as IoT and AI have the potential to be useful in situations such as failure prediction, defective product detection, human resource development, and energy conservation. Smart factories are one of the effective solutions to the challenges facing manufacturers in terms of factory operations. However, implementing it requires manufacturing knowledge and digital know-how. In order to introduce it, other issues such as initial cost and security must be resolved.
In this article, we will discuss the advantages and disadvantages, challenges, and tips for implementing smart factories.

What is a smart factory?
A smart factory is a factory that connects various equipment such as machine tools and production lines to a network to improve the efficiency of information management and optimize operations.
Traditional factory operations typically relied on skilled labor, highly technical staff, and experienced managers. However, factories, which support the backbone of the manufacturing industry, must constantly respond to a variety of issues. It is true that humans have limits when it comes to tackling issues such as failure detection, defective product detection, productivity improvement, and energy optimization.
Currently, in addition to the sophistication of equipment, the situation is constantly changing, such as the introduction of FA equipment (factory automation equipment) that supports automation, the spread of IoT, which refers to the Internet of Things, and the practical use of AI (artificial intelligence). . It is no exaggeration to say that all operations related to factory operations are supported by IT. It is now possible to quickly link product quality and condition, factory equipment operating status, and line information, dramatically improving capabilities.
As a result, the number of options for achieving the traditional issues of labor saving and productivity improvement has increased. With the introduction of smart factories, it is becoming easier to address pressing issues such as dealing with labor shortages and saving energy.

[Advantages] 5 reasons why you should work on a smart factory

This chapter introduces five benefits that can be gained by implementing a smart factory.

Can solve the shortage of human resources
Japan is experiencing a declining birthrate and aging population, and it is predicted that there will be a chronic labor shortage in the future. In the manufacturing industry, it is necessary to create an environment where even the elderly can work comfortably and to recruit human resources.
Labor savings can be achieved by automating tasks that were previously done manually. Furthermore, by having robots perform tasks that require physical strength, it will be easier to create an environment in which skilled seniors can work comfortably. It is predicted that the declining birthrate and aging population will continue in the future, so the introduction of smart factories can be expected to be effective in the long term.
Can promote work style reform
The introduction of smart factories will also lead to the promotion of work style reform . As the needs of workers continue to diversify and the working population continues to decline due to the declining birthrate and aging population, work style reforms are being promoted with the aim of reducing working hours and improving productivity in order to solve these issues. I am.
Its introduction can be expected to improve productivity and improve management efficiency in many manufacturing companies, which may lead to the promotion of work style reforms. Since it responds to the diversifying needs of workers, it can be said that it can be expected to improve employee satisfaction.
Technology can be inherited for a long time
Japan’s manufacturing industry has continued to make strides with its high technological capabilities, but the current situation is that technology has not been passed down. By using smart factories, you can collect know-how and skills as data. By using the collected data to create manuals and standardize work, it becomes easier to transfer technology smoothly.
By making it easier to inherit technology, there is also the benefit of smoother business succession, allowing advanced technology to be passed on to the next generation. Another feature is that by digitizing know-how and experience, it becomes easier to share it with the next generation.
You can promote your efforts towards SDGs.
This will also help promote your efforts towards the SDGs. SDGs (Sustainable Development Goals) are sustainable development goals that were unanimously adopted at the United Nations Summit in 2015. Since the Japanese government and many companies are also working on this, it is one of the elements that we would like to use as material for our appeal.
Smart factories can be said to be a response to the SDGs because they can monitor energy usage and prevent wasteful energy use.
Leads to cost reduction
Working towards smart factories will lead to cost reductions. Since defects in factory equipment can be identified, defective products can be reduced, and material costs can be expected to be reduced.
In addition, it will be possible to visualize the status of the production line and link data such as customer data, which will reduce the burden on employees and reduce labor costs.
By introducing this system, you can expect cost reductions, including material costs and labor costs.

[Disadvantages] Issues that arise when working on smart factories and how to deal with them

While smart factories have many benefits, they can also come with challenges. From here, we will explain the four main issues and how to deal with them.

Securing digital human resources
It is important to secure digital human resources in order to work on smart factories. Since knowledge and know-how in introducing and utilizing digital technology are required, human resources cannot be developed immediately. Furthermore, since know-how in manufacturing technology is required, it is common to proceed with training by introducing experts, IT vendors, etc.
Japan is experiencing a declining birthrate and aging population, making it more difficult than ever to secure human resources. Therefore, there are many cases where smart factories cannot be introduced due to a lack of human resources.
Enhanced security
Strengthening security is important in these efforts. It is common to handle large amounts of data, but this data is often important confidential information for companies, and if it is leaked, it will cause great damage.
In recent years, external threats such as unauthorized access and malware infection have increased the risk of data leaks. Therefore, a strong security model is essential for operating a smart factory.
Network system capacity issues
For deployment, network system capacity criteria must be met. If an IoT system does not have a certain amount of network system capacity, it will not be possible to collect huge amounts of data and improve efficiency and automation.
Additionally, slow system communication speeds may lead to response delays and performance deterioration. However, understanding the required capacity requires someone knowledgeable in cost-benefit analysis of IoT systems.
Securing initial costs
In order to introduce a smart factory, it is necessary to introduce various equipment such as systems, AI, IoT sensors, cloud servers, and IoT gateways. Therefore, the high initial cost for introduction is a major issue.
The cost of installation varies depending on the environment construction, the cost of necessary equipment, and the company providing the service. Therefore, it is important to clarify costs before implementation. It is important to note that smart factories require not only initial costs but also maintenance costs and other costs.

Issues that can be solved with smart factories
Factories that support the manufacturing industry face a variety of challenges. For example, troubleshooting, defective product countermeasures, lack of skilled workers, and energy conservation measures are issues that must be steadily addressed in any factory.
Due to the globalization of business and the diversification of consumer needs, customer demands have expanded to include delivery times, costs, and quality. Additionally, the competition for talented human resources is expanding beyond industry boundaries, making it increasingly difficult to secure human resources to support businesses. Under such circumstances, we must also face the problem of an aging workforce. Stable succession of technology is also an urgent issue.
Smart factories are expected to play a supporting role in solving these problems faced by the manufacturing industry.
Prediction of failure
Failure prediction is the use of IoT to monitor the status of equipment and other factory equipment, predict the probability of failure in advance, or detect areas where abnormalities are currently occurring.
In many cases, factory line monitoring is already being carried out in a typical factory. However, there are many cases where data cannot be measured because the equipment is outdated, or even if the data itself can be measured without any problems, it is difficult to manage the data because the data format is different. In such cases, the problem is that it takes a lot of effort to accurately understand the operating status and prepare for failures.
Making factories smart can solve these challenges. For example, by installing sensors equipped with IoT functions on devices, data can be aggregated regardless of whether they are new or old. By consolidating data in one place, you can centrally manage operating status. Management becomes more efficient by making it easier to understand operating rates and operating conditions, and the accuracy of failure prediction can be improved by utilizing centralized data.

Detecting defective products using image recognition
Image recognition technology is also useful for finding defective products. Traditionally, defective products have been detected through manual inspection. However, this method not only requires a lot of effort, but also has the issue of not being able to train human resources who can perform the inspection and eliminate the risk of human error. Additionally, installing equipment to detect defective products requires a large amount of cost. Dealing with defective products can be said to have continued to be a major problem for factory operations.
Using current image recognition technology, it is possible to solve these problems related to defective products. Deep learning in AI automatically detects specific patterns when a large amount of image data is loaded. By repeating this process, we have seen results such as a dramatic improvement in the accuracy of discovering patterns from image data.
This technology can also be applied to detect defective products in factories. If quality inspection is digitized, AI will be able to automatically learn from the data, and it will also be able to accumulate information on situations where defective products are likely to occur, which will be of great help in analyzing the causes.

Human resource development through remote support using VR
VR (virtual reality) technology, which enables remote operation and management, is also useful for human resource development.
Securing and developing human resources is an urgent issue for the entire manufacturing industry and factory operations. As Japan as a whole progresses toward a declining birthrate and aging population, the proportion of young people in the labor force is decreasing, and the number of middle-aged and older workers is increasing. Under such circumstances, a labor shortage has occurred, and work style reforms are being promoted to reduce working hours. Factories are faced with the challenge of how to pass on the skills of veterans and how to make effective use of their time to develop the next generation of human resources.
VR, also known as “virtual reality,” is a technology that uses goggle-type devices, cameras, and remote systems to monitor and experience the situation as if you were actually there, even if you are not there. As a related technology, a technology called “ mixed reality ” has also emerged, which allows a person wearing a goggle-type device to simultaneously see another image in addition to the reality they are currently seeing.
This has made it possible for veteran employees in remote locations to instruct new employees on tasks and provide manuals through goggles. By using the VR system, it is becoming possible to efficiently develop human resources.

Optimizing factory energy with sensors
Smart factories are also suitable for energy conservation throughout the factory. Currently, the importance of environmental awareness is being emphasized worldwide, as exemplified by terms such as “SDGs” (Sustainable Development Goals) and “ESG management” (management that takes into account the environment, society, and governance). I am. The manufacturing industry, which uses a lot of energy, is also being forced to take a clear response.
In a smart factory, the operating status and energy usage status of the factory can be visualized by utilizing IoT sensors. By managing numerically, it is possible to use energy efficiently and save energy.

Methods and tips for realizing a smart factory

Simply introducing a smart factory does not guarantee success. This chapter introduces methods to ensure smooth operation after installation.
Thoroughly visualize and accumulate data
In order to realize a smart factory, it is important to thoroughly visualize and accumulate data. Until now, in the manufacturing industry, it was common to manually manage data related to quality control and production. However, handwritten data cannot be shared in real time.
Therefore, by digitizing the necessary data, it becomes possible to visualize and accumulate it in real time.
Deploy tools for efficient analysis
For efficient analysis, it is a good idea to introduce tools. It is necessary not only to collect data, but also to analyze and utilize it. However, manually analyzing data is time-consuming and difficult.
Therefore, it is important to introduce tools that automatically create graphs to visualize data, accumulate data, and analyze it from various angles.
Set automation as the end goal
Furthermore, it is important to set automation as the end goal. Ultimately, the purpose of introducing a smart factory is to collect and accumulate data and automate the process for efficient analysis.
This allows you to generate effective data without spending time and effort on data collection and analysis. This data can be effectively utilized for future factory operations and marketing measures.

Initiatives for smart factories that are progressing around the world
Efforts toward smart factories are progressing in countries around the world.
The government of Germany, a manufacturing powerhouse in Europe, is advocating ” Industry 4.0 .” The government is promoting the development of the manufacturing industry through advanced technologies such as the IoT as an industrial revolution. The underlying idea is that the development of IoT will reduce costs and improve productivity, leading to new economic development and social structural change.
For example, as smart factories become more sophisticated, machines will not only be able to carry out human commands, but factory equipment will also be able to guide the way towards finished products themselves. The development of smart factories that can complete products without human instructions is underway.
In China, the national leadership is proposing an industrial policy called “Made in China 2025.” 23 items in 10 fields have been set to advance the manufacturing industry, including next-generation information technology (semiconductors and 5G) and new energy vehicles. We are working to strengthen our manufacturing industry with the aim of joining the world’s manufacturing powerhouses by 2025.
India also advocated “Make in India,” and announced a policy to develop the Indian manufacturing industry through foreign investment. Among these, the development of manufacturing infrastructure has been emphasized, and efforts have been made to comprehensively upgrade the manufacturing industry, including smart factories.
Summary

A smart factory is a factory that utilizes network connectivity and introduces digital technology to equipment and equipment within the factory. By creating a smart factory, you can improve productivity, eliminate labor shortages, and perform efficient data analysis.

Follow us on Facebook for updates and exclusive content! Click here: Each Techy
June 28, 2024
What is a smart factory? Explaining the advantages, disadvantages, issues, and examples!
Smart factories that make full use of IT technologies such as IoT and AI have the potential to be useful in situations such as failure prediction, defective product detection, human resource development, and energy conservation. Smart factories are one of the effective solutions to the challenges facing manufacturers in terms of factory operations. However, implementing it requires manufacturing knowledge and digital know-how. In order to introduce it, other issues such as initial cost and security must be resolved.
In this article, we will discuss the advantages and disadvantages, challenges, and tips for implementing smart factories.

What is a smart factory?
A smart factory is a factory that connects various equipment such as machine tools and production lines to a network to improve the efficiency of information management and optimize operations.
Traditional factory operations typically relied on skilled labor, highly technical staff, and experienced managers. However, factories, which support the backbone of the manufacturing industry, must constantly respond to a variety of issues. It is true that humans have limits when it comes to tackling issues such as failure detection, defective product detection, productivity improvement, and energy optimization.
Currently, in addition to the sophistication of equipment, the situation is constantly changing, such as the introduction of FA equipment (factory automation equipment) that supports automation, the spread of IoT, which refers to the Internet of Things, and the practical use of AI (artificial intelligence). . It is no exaggeration to say that all operations related to factory operations are supported by IT. It is now possible to quickly link product quality and condition, factory equipment operating status, and line information, dramatically improving capabilities.
As a result, the number of options for achieving the traditional issues of labor saving and productivity improvement has increased. With the introduction of smart factories, it is becoming easier to address pressing issues such as dealing with labor shortages and saving energy.

[Advantages] 5 reasons why you should work on a smart factory

This chapter introduces five benefits that can be gained by implementing a smart factory.

Can solve the shortage of human resources
Japan is experiencing a declining birthrate and aging population, and it is predicted that there will be a chronic labor shortage in the future. In the manufacturing industry, it is necessary to create an environment where even the elderly can work comfortably and to recruit human resources.
Labor savings can be achieved by automating tasks that were previously done manually. Furthermore, by having robots perform tasks that require physical strength, it will be easier to create an environment in which skilled seniors can work comfortably. It is predicted that the declining birthrate and aging population will continue in the future, so the introduction of smart factories can be expected to be effective in the long term.
Can promote work style reform
The introduction of smart factories will also lead to the promotion of work style reform . As the needs of workers continue to diversify and the working population continues to decline due to the declining birthrate and aging population, work style reforms are being promoted with the aim of reducing working hours and improving productivity in order to solve these issues. I am.
Its introduction can be expected to improve productivity and improve management efficiency in many manufacturing companies, which may lead to the promotion of work style reforms. Since it responds to the diversifying needs of workers, it can be said that it can be expected to improve employee satisfaction.
Technology can be inherited for a long time
Japan’s manufacturing industry has continued to make strides with its high technological capabilities, but the current situation is that technology has not been passed down. By using smart factories, you can collect know-how and skills as data. By using the collected data to create manuals and standardize work, it becomes easier to transfer technology smoothly.
By making it easier to inherit technology, there is also the benefit of smoother business succession, allowing advanced technology to be passed on to the next generation. Another feature is that by digitizing know-how and experience, it becomes easier to share it with the next generation.
You can promote your efforts towards SDGs.
This will also help promote your efforts towards the SDGs. SDGs (Sustainable Development Goals) are sustainable development goals that were unanimously adopted at the United Nations Summit in 2015. Since the Japanese government and many companies are also working on this, it is one of the elements that we would like to use as material for our appeal.
Smart factories can be said to be a response to the SDGs because they can monitor energy usage and prevent wasteful energy use.
Leads to cost reduction
Working towards smart factories will lead to cost reductions. Since defects in factory equipment can be identified, defective products can be reduced, and material costs can be expected to be reduced.
In addition, it will be possible to visualize the status of the production line and link data such as customer data, which will reduce the burden on employees and reduce labor costs.
By introducing this system, you can expect cost reductions, including material costs and labor costs.

[Disadvantages] Issues that arise when working on smart factories and how to deal with them

While smart factories have many benefits, they can also come with challenges. From here, we will explain the four main issues and how to deal with them.

Securing digital human resources
It is important to secure digital human resources in order to work on smart factories. Since knowledge and know-how in introducing and utilizing digital technology are required, human resources cannot be developed immediately. Furthermore, since know-how in manufacturing technology is required, it is common to proceed with training by introducing experts, IT vendors, etc.
Japan is experiencing a declining birthrate and aging population, making it more difficult than ever to secure human resources. Therefore, there are many cases where smart factories cannot be introduced due to a lack of human resources.
Enhanced security
Strengthening security is important in these efforts. It is common to handle large amounts of data, but this data is often important confidential information for companies, and if it is leaked, it will cause great damage.
In recent years, external threats such as unauthorized access and malware infection have increased the risk of data leaks. Therefore, a strong security model is essential for operating a smart factory.
Network system capacity issues
For deployment, network system capacity criteria must be met. If an IoT system does not have a certain amount of network system capacity, it will not be possible to collect huge amounts of data and improve efficiency and automation.
Additionally, slow system communication speeds may lead to response delays and performance deterioration. However, understanding the required capacity requires someone knowledgeable in cost-benefit analysis of IoT systems.
Securing initial costs
In order to introduce a smart factory, it is necessary to introduce various equipment such as systems, AI, IoT sensors, cloud servers, and IoT gateways. Therefore, the high initial cost for introduction is a major issue.
The cost of installation varies depending on the environment construction, the cost of necessary equipment, and the company providing the service. Therefore, it is important to clarify costs before implementation. It is important to note that smart factories require not only initial costs but also maintenance costs and other costs.

Issues that can be solved with smart factories
Factories that support the manufacturing industry face a variety of challenges. For example, troubleshooting, defective product countermeasures, lack of skilled workers, and energy conservation measures are issues that must be steadily addressed in any factory.
Due to the globalization of business and the diversification of consumer needs, customer demands have expanded to include delivery times, costs, and quality. Additionally, the competition for talented human resources is expanding beyond industry boundaries, making it increasingly difficult to secure human resources to support businesses. Under such circumstances, we must also face the problem of an aging workforce. Stable succession of technology is also an urgent issue.
Smart factories are expected to play a supporting role in solving these problems faced by the manufacturing industry.
Prediction of failure
Failure prediction is the use of IoT to monitor the status of equipment and other factory equipment, predict the probability of failure in advance, or detect areas where abnormalities are currently occurring.
In many cases, factory line monitoring is already being carried out in a typical factory. However, there are many cases where data cannot be measured because the equipment is outdated, or even if the data itself can be measured without any problems, it is difficult to manage the data because the data format is different. In such cases, the problem is that it takes a lot of effort to accurately understand the operating status and prepare for failures.
Making factories smart can solve these challenges. For example, by installing sensors equipped with IoT functions on devices, data can be aggregated regardless of whether they are new or old. By consolidating data in one place, you can centrally manage operating status. Management becomes more efficient by making it easier to understand operating rates and operating conditions, and the accuracy of failure prediction can be improved by utilizing centralized data.

Detecting defective products using image recognition
Image recognition technology is also useful for finding defective products. Traditionally, defective products have been detected through manual inspection. However, this method not only requires a lot of effort, but also has the issue of not being able to train human resources who can perform the inspection and eliminate the risk of human error. Additionally, installing equipment to detect defective products requires a large amount of cost. Dealing with defective products can be said to have continued to be a major problem for factory operations.
Using current image recognition technology, it is possible to solve these problems related to defective products. Deep learning in AI automatically detects specific patterns when a large amount of image data is loaded. By repeating this process, we have seen results such as a dramatic improvement in the accuracy of discovering patterns from image data.
This technology can also be applied to detect defective products in factories. If quality inspection is digitized, AI will be able to automatically learn from the data, and it will also be able to accumulate information on situations where defective products are likely to occur, which will be of great help in analyzing the causes.

Human resource development through remote support using VR
VR (virtual reality) technology, which enables remote operation and management, is also useful for human resource development.
Securing and developing human resources is an urgent issue for the entire manufacturing industry and factory operations. As Japan as a whole progresses toward a declining birthrate and aging population, the proportion of young people in the labor force is decreasing, and the number of middle-aged and older workers is increasing. Under such circumstances, a labor shortage has occurred, and work style reforms are being promoted to reduce working hours. Factories are faced with the challenge of how to pass on the skills of veterans and how to make effective use of their time to develop the next generation of human resources.
VR, also known as “virtual reality,” is a technology that uses goggle-type devices, cameras, and remote systems to monitor and experience the situation as if you were actually there, even if you are not there. As a related technology, a technology called “ mixed reality ” has also emerged, which allows a person wearing a goggle-type device to simultaneously see another image in addition to the reality they are currently seeing.
This has made it possible for veteran employees in remote locations to instruct new employees on tasks and provide manuals through goggles. By using the VR system, it is becoming possible to efficiently develop human resources.

Optimizing factory energy with sensors
Smart factories are also suitable for energy conservation throughout the factory. Currently, the importance of environmental awareness is being emphasized worldwide, as exemplified by terms such as “SDGs” (Sustainable Development Goals) and “ESG management” (management that takes into account the environment, society, and governance). I am. The manufacturing industry, which uses a lot of energy, is also being forced to take a clear response.
In a smart factory, the operating status and energy usage status of the factory can be visualized by utilizing IoT sensors. By managing numerically, it is possible to use energy efficiently and save energy.

Methods and tips for realizing a smart factory

Simply introducing a smart factory does not guarantee success. This chapter introduces methods to ensure smooth operation after installation.
Thoroughly visualize and accumulate data
In order to realize a smart factory, it is important to thoroughly visualize and accumulate data. Until now, in the manufacturing industry, it was common to manually manage data related to quality control and production. However, handwritten data cannot be shared in real time.
Therefore, by digitizing the necessary data, it becomes possible to visualize and accumulate it in real time.
Deploy tools for efficient analysis
For efficient analysis, it is a good idea to introduce tools. It is necessary not only to collect data, but also to analyze and utilize it. However, manually analyzing data is time-consuming and difficult.
Therefore, it is important to introduce tools that automatically create graphs to visualize data, accumulate data, and analyze it from various angles.
Set automation as the end goal
Furthermore, it is important to set automation as the end goal. Ultimately, the purpose of introducing a smart factory is to collect and accumulate data and automate the process for efficient analysis.
This allows you to generate effective data without spending time and effort on data collection and analysis. This data can be effectively utilized for future factory operations and marketing measures.

Initiatives for smart factories that are progressing around the world
Efforts toward smart factories are progressing in countries around the world.
The government of Germany, a manufacturing powerhouse in Europe, is advocating ” Industry 4.0 .” The government is promoting the development of the manufacturing industry through advanced technologies such as the IoT as an industrial revolution. The underlying idea is that the development of IoT will reduce costs and improve productivity, leading to new economic development and social structural change.
For example, as smart factories become more sophisticated, machines will not only be able to carry out human commands, but factory equipment will also be able to guide the way towards finished products themselves. The development of smart factories that can complete products without human instructions is underway.
In China, the national leadership is proposing an industrial policy called “Made in China 2025.” 23 items in 10 fields have been set to advance the manufacturing industry, including next-generation information technology (semiconductors and 5G) and new energy vehicles. We are working to strengthen our manufacturing industry with the aim of joining the world’s manufacturing powerhouses by 2025.
India also advocated “Make in India,” and announced a policy to develop the Indian manufacturing industry through foreign investment. Among these, the development of manufacturing infrastructure has been emphasized, and efforts have been made to comprehensively upgrade the manufacturing industry, including smart factories.
Summary

A smart factory is a factory that utilizes network connectivity and introduces digital technology to equipment and equipment within the factory. By creating a smart factory, you can improve productivity, eliminate labor shortages, and perform efficient data analysis.

Follow us on Facebook for updates and exclusive content! Click here: Each Techy
June 28, 2024
What is a smart factory? Explaining the advantages, disadvantages, issues, and examples!
Smart factories that make full use of IT technologies such as IoT and AI have the potential to be useful in situations such as failure prediction, defective product detection, human resource development, and energy conservation. Smart factories are one of the effective solutions to the challenges facing manufacturers in terms of factory operations. However, implementing it requires manufacturing knowledge and digital know-how. In order to introduce it, other issues such as initial cost and security must be resolved.
In this article, we will discuss the advantages and disadvantages, challenges, and tips for implementing smart factories.

What is a smart factory?
A smart factory is a factory that connects various equipment such as machine tools and production lines to a network to improve the efficiency of information management and optimize operations.
Traditional factory operations typically relied on skilled labor, highly technical staff, and experienced managers. However, factories, which support the backbone of the manufacturing industry, must constantly respond to a variety of issues. It is true that humans have limits when it comes to tackling issues such as failure detection, defective product detection, productivity improvement, and energy optimization.
Currently, in addition to the sophistication of equipment, the situation is constantly changing, such as the introduction of FA equipment (factory automation equipment) that supports automation, the spread of IoT, which refers to the Internet of Things, and the practical use of AI (artificial intelligence). . It is no exaggeration to say that all operations related to factory operations are supported by IT. It is now possible to quickly link product quality and condition, factory equipment operating status, and line information, dramatically improving capabilities.
As a result, the number of options for achieving the traditional issues of labor saving and productivity improvement has increased. With the introduction of smart factories, it is becoming easier to address pressing issues such as dealing with labor shortages and saving energy.

[Advantages] 5 reasons why you should work on a smart factory

This chapter introduces five benefits that can be gained by implementing a smart factory.

Can solve the shortage of human resources
Japan is experiencing a declining birthrate and aging population, and it is predicted that there will be a chronic labor shortage in the future. In the manufacturing industry, it is necessary to create an environment where even the elderly can work comfortably and to recruit human resources.
Labor savings can be achieved by automating tasks that were previously done manually. Furthermore, by having robots perform tasks that require physical strength, it will be easier to create an environment in which skilled seniors can work comfortably. It is predicted that the declining birthrate and aging population will continue in the future, so the introduction of smart factories can be expected to be effective in the long term.
Can promote work style reform
The introduction of smart factories will also lead to the promotion of work style reform . As the needs of workers continue to diversify and the working population continues to decline due to the declining birthrate and aging population, work style reforms are being promoted with the aim of reducing working hours and improving productivity in order to solve these issues. I am.
Its introduction can be expected to improve productivity and improve management efficiency in many manufacturing companies, which may lead to the promotion of work style reforms. Since it responds to the diversifying needs of workers, it can be said that it can be expected to improve employee satisfaction.
Technology can be inherited for a long time
Japan’s manufacturing industry has continued to make strides with its high technological capabilities, but the current situation is that technology has not been passed down. By using smart factories, you can collect know-how and skills as data. By using the collected data to create manuals and standardize work, it becomes easier to transfer technology smoothly.
By making it easier to inherit technology, there is also the benefit of smoother business succession, allowing advanced technology to be passed on to the next generation. Another feature is that by digitizing know-how and experience, it becomes easier to share it with the next generation.
You can promote your efforts towards SDGs.
This will also help promote your efforts towards the SDGs. SDGs (Sustainable Development Goals) are sustainable development goals that were unanimously adopted at the United Nations Summit in 2015. Since the Japanese government and many companies are also working on this, it is one of the elements that we would like to use as material for our appeal.
Smart factories can be said to be a response to the SDGs because they can monitor energy usage and prevent wasteful energy use.
Leads to cost reduction
Working towards smart factories will lead to cost reductions. Since defects in factory equipment can be identified, defective products can be reduced, and material costs can be expected to be reduced.
In addition, it will be possible to visualize the status of the production line and link data such as customer data, which will reduce the burden on employees and reduce labor costs.
By introducing this system, you can expect cost reductions, including material costs and labor costs.

[Disadvantages] Issues that arise when working on smart factories and how to deal with them

While smart factories have many benefits, they can also come with challenges. From here, we will explain the four main issues and how to deal with them.

Securing digital human resources
It is important to secure digital human resources in order to work on smart factories. Since knowledge and know-how in introducing and utilizing digital technology are required, human resources cannot be developed immediately. Furthermore, since know-how in manufacturing technology is required, it is common to proceed with training by introducing experts, IT vendors, etc.
Japan is experiencing a declining birthrate and aging population, making it more difficult than ever to secure human resources. Therefore, there are many cases where smart factories cannot be introduced due to a lack of human resources.
Enhanced security
Strengthening security is important in these efforts. It is common to handle large amounts of data, but this data is often important confidential information for companies, and if it is leaked, it will cause great damage.
In recent years, external threats such as unauthorized access and malware infection have increased the risk of data leaks. Therefore, a strong security model is essential for operating a smart factory.
Network system capacity issues
For deployment, network system capacity criteria must be met. If an IoT system does not have a certain amount of network system capacity, it will not be possible to collect huge amounts of data and improve efficiency and automation.
Additionally, slow system communication speeds may lead to response delays and performance deterioration. However, understanding the required capacity requires someone knowledgeable in cost-benefit analysis of IoT systems.
Securing initial costs
In order to introduce a smart factory, it is necessary to introduce various equipment such as systems, AI, IoT sensors, cloud servers, and IoT gateways. Therefore, the high initial cost for introduction is a major issue.
The cost of installation varies depending on the environment construction, the cost of necessary equipment, and the company providing the service. Therefore, it is important to clarify costs before implementation. It is important to note that smart factories require not only initial costs but also maintenance costs and other costs.

Issues that can be solved with smart factories
Factories that support the manufacturing industry face a variety of challenges. For example, troubleshooting, defective product countermeasures, lack of skilled workers, and energy conservation measures are issues that must be steadily addressed in any factory.
Due to the globalization of business and the diversification of consumer needs, customer demands have expanded to include delivery times, costs, and quality. Additionally, the competition for talented human resources is expanding beyond industry boundaries, making it increasingly difficult to secure human resources to support businesses. Under such circumstances, we must also face the problem of an aging workforce. Stable succession of technology is also an urgent issue.
Smart factories are expected to play a supporting role in solving these problems faced by the manufacturing industry.
Prediction of failure
Failure prediction is the use of IoT to monitor the status of equipment and other factory equipment, predict the probability of failure in advance, or detect areas where abnormalities are currently occurring.
In many cases, factory line monitoring is already being carried out in a typical factory. However, there are many cases where data cannot be measured because the equipment is outdated, or even if the data itself can be measured without any problems, it is difficult to manage the data because the data format is different. In such cases, the problem is that it takes a lot of effort to accurately understand the operating status and prepare for failures.
Making factories smart can solve these challenges. For example, by installing sensors equipped with IoT functions on devices, data can be aggregated regardless of whether they are new or old. By consolidating data in one place, you can centrally manage operating status. Management becomes more efficient by making it easier to understand operating rates and operating conditions, and the accuracy of failure prediction can be improved by utilizing centralized data.

Detecting defective products using image recognition
Image recognition technology is also useful for finding defective products. Traditionally, defective products have been detected through manual inspection. However, this method not only requires a lot of effort, but also has the issue of not being able to train human resources who can perform the inspection and eliminate the risk of human error. Additionally, installing equipment to detect defective products requires a large amount of cost. Dealing with defective products can be said to have continued to be a major problem for factory operations.
Using current image recognition technology, it is possible to solve these problems related to defective products. Deep learning in AI automatically detects specific patterns when a large amount of image data is loaded. By repeating this process, we have seen results such as a dramatic improvement in the accuracy of discovering patterns from image data.
This technology can also be applied to detect defective products in factories. If quality inspection is digitized, AI will be able to automatically learn from the data, and it will also be able to accumulate information on situations where defective products are likely to occur, which will be of great help in analyzing the causes.

Human resource development through remote support using VR
VR (virtual reality) technology, which enables remote operation and management, is also useful for human resource development.
Securing and developing human resources is an urgent issue for the entire manufacturing industry and factory operations. As Japan as a whole progresses toward a declining birthrate and aging population, the proportion of young people in the labor force is decreasing, and the number of middle-aged and older workers is increasing. Under such circumstances, a labor shortage has occurred, and work style reforms are being promoted to reduce working hours. Factories are faced with the challenge of how to pass on the skills of veterans and how to make effective use of their time to develop the next generation of human resources.
VR, also known as “virtual reality,” is a technology that uses goggle-type devices, cameras, and remote systems to monitor and experience the situation as if you were actually there, even if you are not there. As a related technology, a technology called “ mixed reality ” has also emerged, which allows a person wearing a goggle-type device to simultaneously see another image in addition to the reality they are currently seeing.
This has made it possible for veteran employees in remote locations to instruct new employees on tasks and provide manuals through goggles. By using the VR system, it is becoming possible to efficiently develop human resources.

Optimizing factory energy with sensors
Smart factories are also suitable for energy conservation throughout the factory. Currently, the importance of environmental awareness is being emphasized worldwide, as exemplified by terms such as “SDGs” (Sustainable Development Goals) and “ESG management” (management that takes into account the environment, society, and governance). I am. The manufacturing industry, which uses a lot of energy, is also being forced to take a clear response.
In a smart factory, the operating status and energy usage status of the factory can be visualized by utilizing IoT sensors. By managing numerically, it is possible to use energy efficiently and save energy.

Methods and tips for realizing a smart factory

Simply introducing a smart factory does not guarantee success. This chapter introduces methods to ensure smooth operation after installation.
Thoroughly visualize and accumulate data
In order to realize a smart factory, it is important to thoroughly visualize and accumulate data. Until now, in the manufacturing industry, it was common to manually manage data related to quality control and production. However, handwritten data cannot be shared in real time.
Therefore, by digitizing the necessary data, it becomes possible to visualize and accumulate it in real time.
Deploy tools for efficient analysis
For efficient analysis, it is a good idea to introduce tools. It is necessary not only to collect data, but also to analyze and utilize it. However, manually analyzing data is time-consuming and difficult.
Therefore, it is important to introduce tools that automatically create graphs to visualize data, accumulate data, and analyze it from various angles.
Set automation as the end goal
Furthermore, it is important to set automation as the end goal. Ultimately, the purpose of introducing a smart factory is to collect and accumulate data and automate the process for efficient analysis.
This allows you to generate effective data without spending time and effort on data collection and analysis. This data can be effectively utilized for future factory operations and marketing measures.

Initiatives for smart factories that are progressing around the world
Efforts toward smart factories are progressing in countries around the world.
The government of Germany, a manufacturing powerhouse in Europe, is advocating ” Industry 4.0 .” The government is promoting the development of the manufacturing industry through advanced technologies such as the IoT as an industrial revolution. The underlying idea is that the development of IoT will reduce costs and improve productivity, leading to new economic development and social structural change.
For example, as smart factories become more sophisticated, machines will not only be able to carry out human commands, but factory equipment will also be able to guide the way towards finished products themselves. The development of smart factories that can complete products without human instructions is underway.
In China, the national leadership is proposing an industrial policy called “Made in China 2025.” 23 items in 10 fields have been set to advance the manufacturing industry, including next-generation information technology (semiconductors and 5G) and new energy vehicles. We are working to strengthen our manufacturing industry with the aim of joining the world’s manufacturing powerhouses by 2025.
India also advocated “Make in India,” and announced a policy to develop the Indian manufacturing industry through foreign investment. Among these, the development of manufacturing infrastructure has been emphasized, and efforts have been made to comprehensively upgrade the manufacturing industry, including smart factories.
Summary

A smart factory is a factory that utilizes network connectivity and introduces digital technology to equipment and equipment within the factory. By creating a smart factory, you can improve productivity, eliminate labor shortages, and perform efficient data analysis.

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June 28, 2024
What is Artificial Intelligence? AI that can be learned from the basics
Artificial Intelligence has increased the chances of hearing it throughout our lives. I understand it somehow, but I think there are many people who are vague and difficult to explain the concept. In the coming era, a basic background in AI will be indispensable. Therefore, in this article, we will explain the outline and history of AI from the basics. If you want to know about AI, please refer to it.

Basic knowledge of AI
First, let’s take a look at the definition of AI and its types.
What is AI?
AI is an abbreviation for “Artificial Intelligence”, which is an artificial reproduction of a part of human intelligence using software. However, the definition of AI has not been clearly defined at this time, and it is widely understood by academic experts. In any case, it’s a good idea to remember that it’s a computer system that mimics human intelligence.
What is machine learning?
Machine learning is one of the methods of analyzing data, and it is a technique in which a computer automatically learns from the data to find out the rules and patterns behind the data. Algorithms implemented by manual programming can be automatically constructed from a large amount of data, so they are applied in various fields.
What is deep learning?
Deep learning is one of the machine learning methods that utilize neural networks. A neural network is a mathematical model based on the neural circuits (neurons) of the human brain, and is characterized by its ability to perform more complex calculations and learning.
What is big data?
Big data means a huge group of data that is difficult to record, store, and analyze with conventional database management systems. With the widespread use of big data, it has become possible to handle data that could not be collected in the past.
What is a quantum computer?
A quantum computer is a computer that can decipher complicated calculations that cannot be solved by conventional computers by applying the phenomenon of quantum mechanics to information processing technology. Quantum computers are being researched and developed as next-generation high-speed computers.
History of AI

AI has become a word that everyone has heard once, but by the time we got here, it took many years to develop. Let’s take a look at the history and roots of AI.
The birth of AI and the first boom
The concept of AI has its roots in the book “Calculating Machines and Humans” published in 1950 by the English mathematician Alan Turing. In the same book, he asked the question, “Can machines think?” And for the first time at the Dartmouth Conference held in 1956, machines that think like humans were named “artificial intelligence.” This conference will make AI known to scientists.
The first AI boom was in the 1960s. What was researched in the first AI boom was the appearance of computers solving specific problems one after another, such as puzzles and games with clear rules, by inferring and searching using computers. .. However, when I realized that the rules were unclear and I couldn’t solve complicated problems, it gradually went down.
The second boom arrived in the 1980s
In the second AI boom that came in the 1980s, “expert systems” emerged. An expert system is a program that has knowledge in a specific specialized field and can infer and judge events like an expert. Expert systems seemed like a great approach, but the boom didn’t last long because AI at the time couldn’t handle every case accurately.
Third boom and future
In the third boom, which has continued from the 2000s to the present, the practical level of machine learning has greatly improved by utilizing big data. The existence of the research team at the University of Toronto, Canada, was the catalyst for the boom around this time. At the 2012 image recognition software competition, we used neural networks to win the championship by a large margin in second place. In the same year, a group of Google researchers published a paper on image discrimination of cats using neural networks, which is said to have triggered the third boom.
AI utilization case study
Currently, AI is widely used in various fields. Here, we will introduce familiar cases where AI is used.
Netflix recommendation feature
Netflix, a video distribution subscription service, has built its own recommendation system to increase the engagement rate of viewers, and displays thumbnails of works according to the tastes of viewers. Even for the same movie / content, what kind of image it reacts to depends on the viewer. In Netflix, the theme and actors to be emphasized are changed according to the user’s viewing history, and the most effective thumbnail is displayed, which leads to the improvement of the audience rating of the content.
Google search engine
AI technology is also used in the field of search. For example, Google, which is famous for its search engine, uses “Sematic Search”, a mechanism that analyzes the meaning of search terms and displays the optimum search results. In addition, various technologies are used, such as “entity search” that displays accurate search results even from ambiguous information, and “voice search” that supports voice search.
Image diagnosis of NTT DATA
At NTT DATA, the development of diagnostic imaging AI that streamlines the diagnosis of doctors is underway. By analyzing the medical image of the patient with AI technology and showing the potential part of the disease on the screen of the PACS system used for diagnosis, we support accurate diagnosis.
AI learning method

There are several ways to learn AI. This time, we will list three learning methods that have the highest study effect among AI learning methods.
Buy a reference book
Currently, there are many AI-related reference books out there. You can learn by yourself by using such books. By incorporating knowledge using reference books, you can feel the merits such as “information is covered”, “expressions are easy to understand even for beginners”, and “you can remember important parts while writing”. ..
Go to school
In order to acquire AI, a wide range of specialized knowledge such as machine learning, deep learning knowledge, mathematics and statistics is required. Therefore, for those who have difficulty studying on their own or who do not know what to start with, learning from a professional at school is one way to do it.
There are two types of schools, school type and online type. If you want to study more efficiently, you can use a school-based programming school, and if you want to study at home in your spare time, you can use an online school.
Introduce tools
There is also a way to introduce AI tools and learn systematically while actually operating the tools. By learning while experiencing, you can master AI in the shortest time, which also helps to improve work efficiency.
TRYETING’s “UMWELT” for business use
If you want to utilize AI for your own business, we recommend using “UMWELT” developed by TRYETING. UMWELT is a “no-code AI cloud tool” that allows you to easily analyze data and automate operations without programming. Since it is equipped with abundant algorithms, you can build your own original AI system in 3 steps: data collection, algorithm selection, and system integration. Another strength of UMWELT is that it is offered at the lowest price in the industry, so it can be introduced while keeping costs down.
summary
In this article, we introduced the outline and basic knowledge of AI, and familiar cases where AI is currently used. AI itself is still in the process of growth. Going forward, “evolution of machine learning and deep learning technology” and “further improvement of computer computing performance” will continue to solve social issues facing Japan and play a role in supporting sustainable economic growth. Why don’t you deepen your knowledge about AI in this article and use AI for your business?

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June 27, 2024
What is AI training? Specific explanation of what you can learn
With the arrival of the full-scale AI era, it is an urgent task to develop AI human resources. I think there are many people in charge of companies who want to incorporate it into employee training as soon as possible. In this article, we will explain the content of AI training required to keep up with the accelerating wave of AI introduction.
Table of contents
- The introduction of AI training is widespread
- What you can learn from AI training: Utilization
- What you can learn from AI training: Skills
- Key points for successful AI training
- Issues after AI training
- With UMWELT, you can develop AI without skills!
- summary
The introduction of AI training is widespread

With the introduction of AI training spreading, let’s first look at the outline of AI and the specific content of AI training.
What is AI (artificial intelligence) in the first place?
AI (artificial intelligence) is an abbreviation for Artificial Intelligence, which is an artificial reproduction of a part of human intellectual action using software. Artificial intelligence that exists as of 2022 is either human-like or smarter artificial intelligence (specialized AI) for specific tasks, or a tool that reproduces a part of human intelligence (weak AI).
It is said that there is no conscious artificial intelligence (strong AI) that is as smart as humans or smarter than humans (general-purpose AI) or that human intelligence itself is precisely reproduced in every task. .. However, AI technology is expected to continue to evolve at an accelerating pace.
What is AI training?
AI training is literally training to learn about AI. There are various purposes and training contents for AI, from those who want to learn from the basics to those who want to deepen their knowledge. The specific content of the training will be described later.

What you can learn from AI training: Utilization

Now, I will explain the curriculum that you can actually learn in AI training.
Basic knowledge of AI
Learn about the history of AI from the first AI boom to the third AI boom, the current state of AI, and future forecasts of how AI will evolve in the future.
In addition, basic terms related to AI include machine learning, neural networks, big data, deep learning, and data mining. There are many terms that I have heard once, and even if I have a vague understanding of their contents, it is difficult to elaborate on them. So, first of all, you will learn the basic terms related to AI and how to use it.
How to use AI tools
Next, you will learn how to use AI tools that are suitable for your company and the steps and points that you should take when introducing AI to the actual site.
AI development tools have been released by many IT vendors, but in order to select the one that suits your company’s requirements, it is necessary to consider not only the cost but also the operation method and environment construction.
Business improvement utilizing AI
Think about the business content that will lead to improvement by utilizing AI. For example, in the manufacturing industry, the use of image recognition technology enables faster and more accurate object recognition, leading to improved manufacturing efficiency. If you are a customer center, you can use AI chatbots to respond quickly to frequently asked questions, which will improve user satisfaction and reduce human costs. We will learn these cases in a classroom lecture and think about how to utilize our own business.

What you can learn from AI training: Skills
From here, let’s take a closer look at the skills that can be learned in AI training.
Programming language
Learn the programming languages needed for AI development. There are many different types of programming languages, but Python, which features simple code, is popular because it is in high demand and relatively easy to learn.
Data analysis
Once you have acquired data analysis skills, you will be able to utilize internal data. As a result, we can expect to contribute to improving operational efficiency and increasing sales.
Machine learning
Machine learning is a method of letting artificial intelligence learn knowledge by itself based on past experience and statistical data. You can discover rules and patterns in the data that humans cannot think of. In the training, you will learn the principles of machine learning and the differences in learning methods (supervised learning, unsupervised learning, enhanced learning, semi-supervised learning, deep enhanced learning).

Key points for successful AI training
Now that we’ve looked at the content of AI training, let’s consider three points for successful AI training.
Clarify the purpose
It is not limited to AI training, but the first is to clarify the purpose of the training. If the purpose remains ambiguous, the training will not be fruitful and cannot be put to practical use. It is necessary to clarify the future utilization method of AI in the company’s business and share the vision with the trainees.
Clarify the target person
Decide who will take the AI training. If you are a complete amateur with regard to AI, it will take time and cost to develop as an AI human resource. We recommend that you select the target person in advance, considering the level of understanding and proficiency of each employee.
Emphasis on skill acquisition
Just understanding the basic knowledge and outline of AI will not lead to practical use. In order to effectively utilize AI in business, it is desirable to have training that emphasizes the acquisition of data analysis skills and programming skills that are useful in practice.

Issues after AI training
In order for AI training to be successful, it is necessary to keep the above points in mind, but let’s also look at the issues after the training.
Unable to formulate a training plan for AI human resources
As a preliminary step to AI training, many companies have not been able to systematize AI human resources development plans. It is necessary to understand in advance “how much AI human resources are needed in the company” and “whether education by training is enough”. On top of that, let’s create an effective AI human resources development system.
Incompatible with existing businesses
Many companies will introduce AI while continuing their existing businesses. If there is not enough human resources to have a dedicated AI introduction staff, there will be cases where you will be doing normal work while also performing AI introduction work. The person in charge may run out of time and spirit due to the work load.
I can’t improve my skills in practice
After AI training, it is necessary to utilize what we have learned to improve our skills in practice, but the problem is that we are not blessed with the opportunity. Especially for companies that have just started to introduce AI, it will be even more difficult to improve their skills in actual projects.

With UMWELT, you can develop AI without skills!
So far, I have explained about AI training. I think there are many companies that want to introduce AI as soon as possible, but are thinking that “there are no human resources with knowledge of AI” and “there is no time to train AI human resources through training”. Therefore, I would like to recommend TRYETING’s no-code AI tool “UMWELT”. With UMWELT, you can realize advanced AI development without programming, and you can build an AI system in-house without the need for specialized personnel. Currently, it is used by companies in a wide range of industries, from major companies to start-ups.
Summary
While you can learn a lot from AI training, it is also a fact that there are issues such as difficulty in planning AI human resource development. With UMWELT, our dedicated consultants run in parallel not only at the time of introduction but also after operation, so there is an advantage that AI human resources and DX human resources can be trained in your company. If you are interested in introducing UMWELT, please feel free to contact us.

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June 26, 2024
What is AI training? Specific explanation of what you can learn
With the arrival of the full-scale AI era, it is an urgent task to develop AI human resources. I think there are many people in charge of companies who want to incorporate it into employee training as soon as possible. In this article, we will explain the content of AI training required to keep up with the accelerating wave of AI introduction.
Table of contents
- The introduction of AI training is widespread
- What you can learn from AI training: Utilization
- What you can learn from AI training: Skills
- Key points for successful AI training
- Issues after AI training
- With UMWELT, you can develop AI without skills!
- summary
The introduction of AI training is widespread

With the introduction of AI training spreading, let’s first look at the outline of AI and the specific content of AI training.
What is AI (artificial intelligence) in the first place?
AI (artificial intelligence) is an abbreviation for Artificial Intelligence, which is an artificial reproduction of a part of human intellectual action using software. Artificial intelligence that exists as of 2022 is either human-like or smarter artificial intelligence (specialized AI) for specific tasks, or a tool that reproduces a part of human intelligence (weak AI).
It is said that there is no conscious artificial intelligence (strong AI) that is as smart as humans or smarter than humans (general-purpose AI) or that human intelligence itself is precisely reproduced in every task. .. However, AI technology is expected to continue to evolve at an accelerating pace.
What is AI training?
AI training is literally training to learn about AI. There are various purposes and training contents for AI, from those who want to learn from the basics to those who want to deepen their knowledge. The specific content of the training will be described later.

What you can learn from AI training: Utilization

Now, I will explain the curriculum that you can actually learn in AI training.
Basic knowledge of AI
Learn about the history of AI from the first AI boom to the third AI boom, the current state of AI, and future forecasts of how AI will evolve in the future.
In addition, basic terms related to AI include machine learning, neural networks, big data, deep learning, and data mining. There are many terms that I have heard once, and even if I have a vague understanding of their contents, it is difficult to elaborate on them. So, first of all, you will learn the basic terms related to AI and how to use it.
How to use AI tools
Next, you will learn how to use AI tools that are suitable for your company and the steps and points that you should take when introducing AI to the actual site.
AI development tools have been released by many IT vendors, but in order to select the one that suits your company’s requirements, it is necessary to consider not only the cost but also the operation method and environment construction.
Business improvement utilizing AI
Think about the business content that will lead to improvement by utilizing AI. For example, in the manufacturing industry, the use of image recognition technology enables faster and more accurate object recognition, leading to improved manufacturing efficiency. If you are a customer center, you can use AI chatbots to respond quickly to frequently asked questions, which will improve user satisfaction and reduce human costs. We will learn these cases in a classroom lecture and think about how to utilize our own business.

What you can learn from AI training: Skills
From here, let’s take a closer look at the skills that can be learned in AI training.
Programming language
Learn the programming languages needed for AI development. There are many different types of programming languages, but Python, which features simple code, is popular because it is in high demand and relatively easy to learn.
Data analysis
Once you have acquired data analysis skills, you will be able to utilize internal data. As a result, we can expect to contribute to improving operational efficiency and increasing sales.
Machine learning
Machine learning is a method of letting artificial intelligence learn knowledge by itself based on past experience and statistical data. You can discover rules and patterns in the data that humans cannot think of. In the training, you will learn the principles of machine learning and the differences in learning methods (supervised learning, unsupervised learning, enhanced learning, semi-supervised learning, deep enhanced learning).

Key points for successful AI training
Now that we’ve looked at the content of AI training, let’s consider three points for successful AI training.
Clarify the purpose
It is not limited to AI training, but the first is to clarify the purpose of the training. If the purpose remains ambiguous, the training will not be fruitful and cannot be put to practical use. It is necessary to clarify the future utilization method of AI in the company’s business and share the vision with the trainees.
Clarify the target person
Decide who will take the AI training. If you are a complete amateur with regard to AI, it will take time and cost to develop as an AI human resource. We recommend that you select the target person in advance, considering the level of understanding and proficiency of each employee.
Emphasis on skill acquisition
Just understanding the basic knowledge and outline of AI will not lead to practical use. In order to effectively utilize AI in business, it is desirable to have training that emphasizes the acquisition of data analysis skills and programming skills that are useful in practice.

Issues after AI training
In order for AI training to be successful, it is necessary to keep the above points in mind, but let’s also look at the issues after the training.
Unable to formulate a training plan for AI human resources
As a preliminary step to AI training, many companies have not been able to systematize AI human resources development plans. It is necessary to understand in advance “how much AI human resources are needed in the company” and “whether education by training is enough”. On top of that, let’s create an effective AI human resources development system.
Incompatible with existing businesses
Many companies will introduce AI while continuing their existing businesses. If there is not enough human resources to have a dedicated AI introduction staff, there will be cases where you will be doing normal work while also performing AI introduction work. The person in charge may run out of time and spirit due to the work load.
I can’t improve my skills in practice
After AI training, it is necessary to utilize what we have learned to improve our skills in practice, but the problem is that we are not blessed with the opportunity. Especially for companies that have just started to introduce AI, it will be even more difficult to improve their skills in actual projects.

With UMWELT, you can develop AI without skills!
So far, I have explained about AI training. I think there are many companies that want to introduce AI as soon as possible, but are thinking that “there are no human resources with knowledge of AI” and “there is no time to train AI human resources through training”. Therefore, I would like to recommend TRYETING’s no-code AI tool “UMWELT”. With UMWELT, you can realize advanced AI development without programming, and you can build an AI system in-house without the need for specialized personnel. Currently, it is used by companies in a wide range of industries, from major companies to start-ups.
Summary
While you can learn a lot from AI training, it is also a fact that there are issues such as difficulty in planning AI human resource development. With UMWELT, our dedicated consultants run in parallel not only at the time of introduction but also after operation, so there is an advantage that AI human resources and DX human resources can be trained in your company. If you are interested in introducing UMWELT, please feel free to contact us.

Follow us on Facebook for updates and exclusive content! Click here: Each Techy
June 26, 2024
What kind of work and skills do you need to know if you become a cloud engineer?
In this article, we will explain the outline, work content, required skills, demand, future potential, etc. of cloud engineers.
In the last few years, the word “cloud” has become quite familiar to our lives.
The use of cloud services such as online storage has become widespread among individuals, and cloud computing is steadily increasing, especially in companies.
And the demand for cloud engineers to cope with this rapidly increasing “cloudization” is increasing, and it is also attracting attention as an engineer’s career.
Let’s take a concrete look at cloud engineers.

1. What is a cloud engineer?
1.1 Born due to changes in the infrastructure environment accompanying the cloud era
A cloud engineer is an engineer who designs, builds, operates, and maintains infrastructure such as servers and networks in a cloud environment .
Cloud (Cloud Computing) is a form of using necessary functions at a destination connected to a network via the Internet.
By using this cloud, “clouding” has the advantages of speeding up installation, reducing costs, and reducing operational load. In the past, infrastructure engineers and network engineers had to spend time on network and server installation and management. The work load such as is also lightened.
Cloud engineers are often involved in cloud computing, and need to have knowledge and experience around infrastructure and be familiar with the cloud.
From such a trend, it seems that infrastructure engineers are also required to acquire cloud knowledge and technology and become cloud engineers who are strong in “infrastructure + cloud”.
It can be said that cloud engineers were born from the changes in the infrastructure environment accompanying the cloud era.

2. What the cloud engineer does
Cloud engineers are engaged in work in the following cloud environment *, and the work content may differ slightly depending on the environment.
Types of cloud environment *
Public cloud: Cloud service that can rent the infrastructure environment required for system operation
Private cloud: Cloud that is built and operated exclusively by the company
Hybrid cloud: Cloud environment that uses both public cloud and private cloud
2.1 Infrastructure design on the cloud
The important work of a cloud engineer is design work on the cloud.
The public cloud does not require the physical design of your own data center, but we will design by taking advantage of the features and services of the cloud service you use .
In the hybrid cloud, it is also necessary to design the connection part that connects the data center and the cloud, and it will be useful to have knowledge of the network because design information is added to routers and switches and router installation work is required. ..
There are various cases such as migration work from on-premises to the cloud and launching a new system on the cloud, but in each case, it is important to design considering the high availability * and scalability * that are the characteristics of the cloud. Will be.
In addition, each cloud service provides learning resources and tools to support your design.
For example, on AWS, the AWS Well-Architected Tool allows you to check whether the design is in line with the optimal use of AWS.

High Availability *
Obtain higher reliability by keeping the system running without stopping due to a failure or the like.
Extensibility *
Obtain higher processing performance by distributing processing
2.2 Building the cloud
We will build a system environment on the cloud by using various functions provided by the cloud service.
When creating a virtual server , you set the server location, network settings, load balancer for redundancy and load balancing, backup, and so on.
In addition, cloud storage settings for data sharing and storage , virtual network construction, and selection of optimal database services are performed.
In addition, infrastructure may be coded to simplify infrastructure management, change management, and improve efficiency by automating infrastructure construction .
2.3 Cloud operation and maintenance
As with on-premises, it is the job of the cloud engineer to operate and maintain after construction.
We have tasks such as tuning for stable operation of various services, management of operating costs , version upgrades of OS / middleware / applications, patch application , authority management , and system monitoring .

3. What skills are required of cloud engineers?
3.1 Knowledge of public cloud services
Engineers involved in cloud operations need not only basic knowledge of the cloud, but also knowledge and skills related to public cloud services such as AWS .
Various cloud services provide certifications by level and specialty, as well as a wealth of training and learning sources .
Qualifications allow you to systematically study services and architectures that you do not normally use, so it is a good idea to try them.
In recent projects for cloud engineers, it seems that the number of businesses dealing with typical public cloud services such as AWS (Amazon Web Services) , Azure (Microsoft Azure) , and GCP (Google Cloud Platform) is increasing rapidly.
Even if you have no work experience, holding a certification will be useful as a proof of knowledge and skills for such cases.
3.2 Knowledge and skills of the latest cloud-related technology
Cloud trends are constantly changing as companies become more “cloud-first”.
One of the skills you need to know is to grasp and understand the latest trends in container technology, serverless computing, security and more.

3.3 Knowledge and experience of cloud technology
3.3.1 Server virtualization
Virtual server , which is the most basic of the cloud environment Understand the procedures and optional functions for using a virtual server
on the cloud, knowledge about server virtualization technology, and the advantages and disadvantages of server virtualization.
3.3.2 Network virtualization
It is a good idea to acquire the following knowledge and skills regarding network virtualization technology. -A technology that divides the network to enable the exchange of limited data in
VLAN (Virtual LAN) -VPN (Virtual Private Network) Makes a private connection like a dedicated line to realize a network connection method with a high security level. Technology – NFV (Network Functions Virtualization) Technology that implements network functions as application software on a virtual server in order to flexibly respond to configuration changes of network devices.

Also, for VPN services provided by major cloud services
- Amazon VPC (Virtual Private Cloud)
- Azure VPN Gateway
- Google Cloud VPN
And so on.
3.3.3 Database technology
Each cloud service provides various database services.
- Free RDBMS such as MySQL and Postgre
- Paid RDBMS such as Oracle, Microsoft SQL Server
- Database services provided by each cloud service (Amazon RDS, Azure SQL Database, Google Cloud SQL, etc.)
- NoSQL (database that is not a relational database)
RDBMS is most often used, but for big data analysis and IoT, a distributed database such as NoSQL that distributes a large amount of data and performs high-speed processing is used.
By understanding the characteristics of each database, acquiring knowledge, and selecting a database according to the purpose of use, you can build a faster and more scalable cloud environment.

4. Demand and future potential of cloud engineers
■ The domestic market size of cloud services has grown to 1.9 trillion yen (FY2018)
■ The movement to move existing corporate systems to the public cloud is in full swing
■ AWS, Azure, GCP (Google) global vendors are becoming oligopolistic
- (Reference source: MM Research Institute: From the 2019 Domestic Cloud Service Demand Trend Survey )
According to the [Cloud Service Market Scale / Results / Forecast] report released by MM Research Institute, the movement to cloud the infrastructure of companies is accelerating, and it is expected to reach 4,475.4 billion yen in FY2011. It can be predicted that the demand for cloud engineers will increase as the number of cloud-related businesses and operations increases.
In the public cloud services industry, AWS usage is more than half, and more and more companies are deploying Azure and GCP .
In the future, each cloud service company will compete to evolve cloud technology by providing new services and parts used in the latest technologies such as machine learning and IoT, which are not limited to infrastructure.

In addition, Gartner Inc. predicts that 80% of companies will close their data centers by 2025, and with the birth of technologies such as cloud services and IoT, the advantages of conventional on-premises data centers will be diminished. I point out that I will go.
* Reference source: The Data Center is Dead (Gartner Blog Network) )
From the above, it can be expected that the demand for cloud engineers will increase, and it can be considered that there is a future.
5. Summary
Nowadays, which is called the cloud era, many cloud engineers are needed and demand is increasing, but there is still a shortage of engineers specializing in the cloud.
Even infrastructure engineers who have only on-premises experience can apply their knowledge and experience of infrastructure to the cloud and further expand their knowledge.
Based on the experience you have cultivated so far, let’s spread the knowledge and understanding of the cloud and gain experience.
Even if you are an application engineer with no experience in infrastructure, if you can understand the code, it will be easier to catch up with the infrastructure, so you will be able to deepen your understanding of the cloud.
Cloud engineers have high skills required such as knowledge and experience of infrastructure, knowledge of cloud and knowledge of various public services, but it can be said that it is a valuable career to aim for from the viewpoint of demand and future potential.
How about aiming to become a cloud engineer by referring to the contents of this article?

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June 25, 2024
What kind of work and skills do you need to know if you become a cloud engineer?
In this article, we will explain the outline, work content, required skills, demand, future potential, etc. of cloud engineers.
In the last few years, the word “cloud” has become quite familiar to our lives.
The use of cloud services such as online storage has become widespread among individuals, and cloud computing is steadily increasing, especially in companies.
And the demand for cloud engineers to cope with this rapidly increasing “cloudization” is increasing, and it is also attracting attention as an engineer’s career.
Let’s take a concrete look at cloud engineers.

1. What is a cloud engineer?
1.1 Born due to changes in the infrastructure environment accompanying the cloud era
A cloud engineer is an engineer who designs, builds, operates, and maintains infrastructure such as servers and networks in a cloud environment .
Cloud (Cloud Computing) is a form of using necessary functions at a destination connected to a network via the Internet.
By using this cloud, “clouding” has the advantages of speeding up installation, reducing costs, and reducing operational load. In the past, infrastructure engineers and network engineers had to spend time on network and server installation and management. The work load such as is also lightened.
Cloud engineers are often involved in cloud computing, and need to have knowledge and experience around infrastructure and be familiar with the cloud.
From such a trend, it seems that infrastructure engineers are also required to acquire cloud knowledge and technology and become cloud engineers who are strong in “infrastructure + cloud”.
It can be said that cloud engineers were born from the changes in the infrastructure environment accompanying the cloud era.

2. What the cloud engineer does
Cloud engineers are engaged in work in the following cloud environment *, and the work content may differ slightly depending on the environment.
Types of cloud environment *
Public cloud: Cloud service that can rent the infrastructure environment required for system operation
Private cloud: Cloud that is built and operated exclusively by the company
Hybrid cloud: Cloud environment that uses both public cloud and private cloud
2.1 Infrastructure design on the cloud
The important work of a cloud engineer is design work on the cloud.
The public cloud does not require the physical design of your own data center, but we will design by taking advantage of the features and services of the cloud service you use .
In the hybrid cloud, it is also necessary to design the connection part that connects the data center and the cloud, and it will be useful to have knowledge of the network because design information is added to routers and switches and router installation work is required. ..
There are various cases such as migration work from on-premises to the cloud and launching a new system on the cloud, but in each case, it is important to design considering the high availability * and scalability * that are the characteristics of the cloud. Will be.
In addition, each cloud service provides learning resources and tools to support your design.
For example, on AWS, the AWS Well-Architected Tool allows you to check whether the design is in line with the optimal use of AWS.

High Availability *
Obtain higher reliability by keeping the system running without stopping due to a failure or the like.
Extensibility *
Obtain higher processing performance by distributing processing
2.2 Building the cloud
We will build a system environment on the cloud by using various functions provided by the cloud service.
When creating a virtual server , you set the server location, network settings, load balancer for redundancy and load balancing, backup, and so on.
In addition, cloud storage settings for data sharing and storage , virtual network construction, and selection of optimal database services are performed.
In addition, infrastructure may be coded to simplify infrastructure management, change management, and improve efficiency by automating infrastructure construction .
2.3 Cloud operation and maintenance
As with on-premises, it is the job of the cloud engineer to operate and maintain after construction.
We have tasks such as tuning for stable operation of various services, management of operating costs , version upgrades of OS / middleware / applications, patch application , authority management , and system monitoring .

3. What skills are required of cloud engineers?
3.1 Knowledge of public cloud services
Engineers involved in cloud operations need not only basic knowledge of the cloud, but also knowledge and skills related to public cloud services such as AWS .
Various cloud services provide certifications by level and specialty, as well as a wealth of training and learning sources .
Qualifications allow you to systematically study services and architectures that you do not normally use, so it is a good idea to try them.
In recent projects for cloud engineers, it seems that the number of businesses dealing with typical public cloud services such as AWS (Amazon Web Services) , Azure (Microsoft Azure) , and GCP (Google Cloud Platform) is increasing rapidly.
Even if you have no work experience, holding a certification will be useful as a proof of knowledge and skills for such cases.
3.2 Knowledge and skills of the latest cloud-related technology
Cloud trends are constantly changing as companies become more “cloud-first”.
One of the skills you need to know is to grasp and understand the latest trends in container technology, serverless computing, security and more.

3.3 Knowledge and experience of cloud technology
3.3.1 Server virtualization
Virtual server , which is the most basic of the cloud environment Understand the procedures and optional functions for using a virtual server
on the cloud, knowledge about server virtualization technology, and the advantages and disadvantages of server virtualization.
3.3.2 Network virtualization
It is a good idea to acquire the following knowledge and skills regarding network virtualization technology. -A technology that divides the network to enable the exchange of limited data in
VLAN (Virtual LAN) -VPN (Virtual Private Network) Makes a private connection like a dedicated line to realize a network connection method with a high security level. Technology – NFV (Network Functions Virtualization) Technology that implements network functions as application software on a virtual server in order to flexibly respond to configuration changes of network devices.

Also, for VPN services provided by major cloud services
- Amazon VPC (Virtual Private Cloud)
- Azure VPN Gateway
- Google Cloud VPN
And so on.
3.3.3 Database technology
Each cloud service provides various database services.
- Free RDBMS such as MySQL and Postgre
- Paid RDBMS such as Oracle, Microsoft SQL Server
- Database services provided by each cloud service (Amazon RDS, Azure SQL Database, Google Cloud SQL, etc.)
- NoSQL (database that is not a relational database)
RDBMS is most often used, but for big data analysis and IoT, a distributed database such as NoSQL that distributes a large amount of data and performs high-speed processing is used.
By understanding the characteristics of each database, acquiring knowledge, and selecting a database according to the purpose of use, you can build a faster and more scalable cloud environment.

4. Demand and future potential of cloud engineers
■ The domestic market size of cloud services has grown to 1.9 trillion yen (FY2018)
■ The movement to move existing corporate systems to the public cloud is in full swing
■ AWS, Azure, GCP (Google) global vendors are becoming oligopolistic
- (Reference source: MM Research Institute: From the 2019 Domestic Cloud Service Demand Trend Survey )
According to the [Cloud Service Market Scale / Results / Forecast] report released by MM Research Institute, the movement to cloud the infrastructure of companies is accelerating, and it is expected to reach 4,475.4 billion yen in FY2011. It can be predicted that the demand for cloud engineers will increase as the number of cloud-related businesses and operations increases.
In the public cloud services industry, AWS usage is more than half, and more and more companies are deploying Azure and GCP .
In the future, each cloud service company will compete to evolve cloud technology by providing new services and parts used in the latest technologies such as machine learning and IoT, which are not limited to infrastructure.

In addition, Gartner Inc. predicts that 80% of companies will close their data centers by 2025, and with the birth of technologies such as cloud services and IoT, the advantages of conventional on-premises data centers will be diminished. I point out that I will go.
* Reference source: The Data Center is Dead (Gartner Blog Network) )
From the above, it can be expected that the demand for cloud engineers will increase, and it can be considered that there is a future.
5. Summary
Nowadays, which is called the cloud era, many cloud engineers are needed and demand is increasing, but there is still a shortage of engineers specializing in the cloud.
Even infrastructure engineers who have only on-premises experience can apply their knowledge and experience of infrastructure to the cloud and further expand their knowledge.
Based on the experience you have cultivated so far, let’s spread the knowledge and understanding of the cloud and gain experience.
Even if you are an application engineer with no experience in infrastructure, if you can understand the code, it will be easier to catch up with the infrastructure, so you will be able to deepen your understanding of the cloud.
Cloud engineers have high skills required such as knowledge and experience of infrastructure, knowledge of cloud and knowledge of various public services, but it can be said that it is a valuable career to aim for from the viewpoint of demand and future potential.
How about aiming to become a cloud engineer by referring to the contents of this article?

Follow us on Facebook for updates and exclusive content! Click here: Each Techy
June 25, 2024