Autonomous Sensor Node System for Table Tennis Officiating
Version 1.0.0 (6.8 KB) by
Mohammad Khishe
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. ECOA integrates adaptive group dynamics, chaos-based seeding, and a dual exploration–exploitation strategy to balance global and local search refinement.
Cite As
Mohammad Khishe (2025). Autonomous Sensor Node System for Table Tennis Officiating (https://ch.mathworks.com/matlabcentral/fileexchange/181161-autonomous-sensor-node-system-for-table-tennis-officiating), MATLAB Central File Exchange. Retrieved .
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Code
| Version | Published | Release Notes | |
|---|---|---|---|
| 1.0.0 |
