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

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.