Abstract
Our research group has proposed the measurement concept of multimodal sensing, in which sensors with broad detection characteristics are used to realize the sensing of multiple items, and has developed semiconductor CMOS-based sensors to realize this concept. In this talk, we introduce ion image sensors and odor sensors as examples of CMOS-based sensors suitable for multimodal sensing, and data analysis using machine learning, which is important for this measurement concept will be mentioned and introduce an example of machine learning-based sensing. The application of these sensors to smart agriculture and other fields will also be discussed, as well as the current status and issues for the practical application of sensor systems.
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