Customer Cases

Health & Elderly Care Management

 

AllegroSmart helps families and administrators in grasping the health condition from remote areas, prevention of diseases, watching over. The company is also trying to make it useful for labor management. Wireless real time collection of available data of heart rate monitor, pulse monitor, blood pressure gauge, weight scale, thermometer, activity meter, blood glucose meter, body composition meter, sleeping time, sensor built in smartphone, accumulating BigData To go. It is possible to grasp the health condition from a remote place in real time and to notify multiple people if there is abnormality in health condition.
For example, in real time blood pressure value or heart rate value every day morning / night, if not out of the usual numerical value contact notification to the family and administrative officials in a remote place to avoid a dangerous situation You can support. Also, since you can see the stress index from heart rate variability time series by utilizing heart rate value, by correlating it with working time, overwork is prevented. By accumulating data and developing the AI ​​(Machine Learning) Model by utilizing the data, individual condition condition prediction becomes possible.

 

 

Solar power generation Facilities Management

By collecting data of connection box (input DC, output DC), power conditioner (input DC, output AC), transformer (input AC, output AC) of photovoltaic power generation equipment and visualizing it by arranging it in time series waveform , Enables remote monitoring. Also, by collecting environmental sensors (temperature, illuminance) and open data (temperature, illuminance), forecast of power generation capacity is predicted, and when there is a deviation from the actual value, it is detected as abnormality and notified, We will make it possible. Also, by utilizing that data, it will lead to preventive maintenance by predicting and predicting breakdown of photovoltaic power generation equipment. It becomes remote diagnosis of failure, and efficiency of maintenance maintenance management can be improved.

Smart Factory

At the factory, we plan product planning, make a manufacturing plan, and carry out commercialization at the production line. We will make production according to plan while controlling and managing facilities by manufacturing execution management system. In addition, we will manage the planned production process while managing with product quality control system whether product is being manufactured as planned product. Production delay may occur due to a sudden production line electric machine failure. Also, in the production line, we must reduce the costs that affect the profits of production products by reducing the cost of power consumption and preventing the production of defective products. To that end, we have been promoting IT in factories, but in order to make the whole as efficient as planned, we collect and analyze and analyze a large amount of data of each system and electrical equipment of each production line in real time , It will not lead to an improvement in production efficiency unless instant visualization of production efficiency is done. Moreover, in order to continue more stable production, we will develop AI Model using a large amount of accumulated data and realize smart factory more efficient. However, in order to realize it, since it can not be utilized unless the multiple facility operation logs of each production line, multiple system data, and power consumption data are integrated, on the spot, data is collected manually according to need I did not make it at all in order to improve production efficiency further. Therefore, it is necessary to optimize data in real time, real-time grasp of the production process using AI, production prediction, and prevention of failure of the electrical equipment of the production line.

Automotive Management

In the automotive field, by collecting traveling data (speed, acceleration, angular velocity, etc.) from in-vehicle data (ODB 2 etc.), it is possible to determine hazardous driving such as sudden braking, sudden departure and sharp turn, and the driver’s driving skill It is possible to evaluate. By using wearable sensors and non-contact sensors to measure and collect vital data (heart rate, RRI etc.) and GPS data from the driver, health management becomes possible along with management of position information of business vehicles and drivers I will. By doing this, it is useful for preventing accidents by detecting, predicting and predicting poor physical condition. In addition, we can measure and collect vehicle traveling data, weather information, attribute information (useful life, etc.), integrate it with recorded data of failure occurrence, analyze and analyze it, enabling real time failure prediction of the car .