Autonomous Sensor Node System for Table Tennis Officiating: Optimized Placement Using Enhanced Chimp Optimization Algorithm

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Accurate table tennis officiating for side ball decisions and net is challenging due to human error and the high cost of systems like Hawk-Eye, which require numerous sensors and lack adaptability. This study proposes an Autonomous Sensor Node System (ASNS) with three triboelectric nanogenerator (TENG)-powered acceleration sensors, optimized by the Enhanced Chimp Optimization Algorithm (ECOA) for collision point (CP) detection.

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