Fujitsu Limited has developed a new algorithm to estimate ongoing heat stress in workers, such as security guards, using its artificial intelligence technologies, known as Human Centric AI Zinrai.
Developed together with Fujitsu Laboratories Ltd., Fujitsu aims to enhance solutions deployed on its digital business platform, "Fujitsu Digital Business Platform MetaArc", that use IoT to support on-site safety management. This new algorithm will be available from the end of July. Also from June through September, Fujitsu is implementing solutions incorporating this new algorithm in a field trial with security guards at its own Kawasaki Plant.
Previous algorithms estimated heat stress levels using a device worn on the arm to measure data such as humidity, temperature, as well as increases in pulse, and were primarily used in manufacturing and at construction sites. As the new algorithm can now estimate heat stress levels that accumulate over time, it is suitable for employees who continually work outdoors in the summer. Combined with the previous algorithm, it can be used to manage safety in a wide variety of situations.
In order to estimate the level of accumulated heat stress, and because a diverse range of data is handled in which correlations are difficult to discern, the new system uses AI technology to execute machine learning based on expert knowledge. In so doing, Fujitsu developed a logic in which AI can extract the characteristics of high heat stress to enable estimates such as those made by labor science experts.
In addition to the existing data of humidity, temperature and pulse, the new algorithm estimates the level of heat stress based on new data, such the amount of activity, as well as data that shifts over time.Since machine learning is appropriate for making estimates from a wide variety of data with unclear correlations, Fujitsu developed a logic in which AI can extract the characteristics of high heat stress from the stock of actual data and data evaluated by experts. This has enabled the algorithm to estimate accumulated heat stress in the same way that labor science experts would, enabling users to observe the status of individual employees in situations that do not require a great deal of activity, such as security guards who must spend long hours standing in the hot sun.