Autonomous Sensor Node System for Table Tennis Officiating

Autonomous Sensor Node System for Table Tennis Officiating: Optimized Placement Using Enhanced Chimp Optimization Algorithm
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Updated 16 May 2025

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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. 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 .

MATLAB Release Compatibility
Created with R2025a
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.0.0