AI-based contactless temperature sensor anomaly detection simulation demo
AI learning infers and displays the degree of anomaly associated with temperature changes.
Temperature data collected by a non-contact temperature sensor (thermal watcher) is used for AI learning inference in the Solist-AI TM simulator to display the degree of abnormality associated with temperature changes. The Solist-AI TM simulator is software that simulates the AI accelerator function of Solist-AI TMIC (ML63Q2557) on Windows. - A demo device that mimics a control panel creates a normal state (initial powered state) and a load state, collecting temperature data from terminal blocks using the thermal watcher (32x32 pixel non-contact temperature sensor). - The temperature data from the normal state is used to train the AI in the simulator. - The temperature data from the load state is inferred by the AI in the simulator, and the degree of abnormality associated with temperature changes is displayed in a graph.
- Company:エスエスシー
- Price:Other