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.
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【Specifications (Excerpt)】 <DT-EBML63Q2557 Features> ■ Expanded FRAM: 256KByte ■ Analog Input ・ IEPE power supply available ・ 10kHz 3rd order Butterworth filter included ・ Connected internally to the CPU's A/D converter * For more details, please download the PDF or feel free to contact us.
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At SSC, we primarily offer non-contact thermometers. Since they are non-contact, measurements can be taken regardless of the distance between the thermometer and the object being measured, allowing us to expand our usage into various fields, including safety and environmental sectors. As our group company develops and manufactures these products, we can also accommodate custom and OEM requests. We strive daily to ensure that many people can use our products conveniently and with peace of mind, so if you are considering measurement, analysis, or management using infrared sensors, please feel free to consult with us.
