Analyzing emotions from voice and facial expressions. AI "Safety-kun" for early detection of signs of trouble in manufacturing sites.
In manufacturing sites, employees' physical condition and mental health issues during machine operation and line work can lead to accidents and quality defects. However, it is a challenging task to judge based solely on appearances. The high-precision stress analysis system "Anzen-kun" is an AI system that analyzes employees' voices and facial expressions to understand their condition. It incorporates emotion analysis technology (developed by Emotional Technologies Inc.) that was also utilized in the recently popular "AI Akimoto Yasushi." ■ Main Features - Can be used by simply answering three questions before shift changes - Integrates and analyzes voice and facial expressions - Quantifies 40 categories of emotions in about 15 seconds - Displays results at both individual and team levels on a dashboard - Notifies administrators if any anomalies are detected - Usable with just one tablet, no paper or questionnaires required "Anzen-kun" can be seamlessly integrated into daily operations as an auxiliary tool to prevent accidents and troubles in manufacturing sites.
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Q1. Who can use it? It can be used by one person or at large-scale sites (from 5,000 people and up). Q2. Is a dedicated device necessary? It can be used on an Android tablet. We will deliver it with the system pre-installed on the device. If you would like to install it on your own device, please consult us. Q3. Is a network required? In principle, communication via WiFi or SIM is necessary. However, if you are using it in locations with unstable signals, it is also possible to use it in offline mode. Q4. Can it be used while wearing a mask? Measurements can be taken while wearing a mask, but typically, the analysis focuses on three areas of the face: the forehead, around the eyes, and the mouth, so there may be a slight decrease in measurement accuracy. If you are concerned, please remove the mask while using it. Q5. Can it be used in noisy environments? If the surrounding noise is loud and it is difficult to recognize voices, it is possible to operate the tablet with an external microphone attached.
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Applications/Examples of results
■Check the condition before the shift to prevent operational mistakes with the machinery. ■Understand the physical condition and stress tendencies of workers and utilize this for safety guidance. ■Support early detection of risks that could lead to quality defects or accidents. ■Utilize for health management during night shifts and shift work. ■Easily integrated into existing workflows without increasing the burden on the site.
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