Aside from existing data of humidity, temperature and pulse, the new algorithm estimates the level of heat stress based on the amount of activity, as well as data that shifts over time.
A new algorithm is using Fujitsu's Human Centric AI Zinrai to estimate the heat stress in workers, such as security guards.
Previously-developed 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. 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.
Figure 1: Fujitsu has applied its solution incorporating the new algorithm to monitor those entering its Kawasaki Plant as well as security guards on site. (Source: Fujitsu)
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 labour 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.
The new algorithm will be available from the end of July. Fujitsu has also implemented solutions using the algorithm in a field trial with security guards at its Kawasaki plant until September.