Audio-Based Telemetry Using HT Radios for Remote Monitoring of Renewable Energy Systems

Effective monitoring of renewable energy systems, such as wind turbines and photovoltaic arrays, is essential for optimizing energy production. However, traditional wired monitoring systems are expensive and lack flexibility. This study develops a reliable wireless monitoring system that addresses the limitations of wired alternatives, using a PZEM-004T power meter, Arduino Uno R3, and BF-888S HT radios. The system employs audio-modulated binary encoding for long-range, low-cost data transmission, enabling real-time monitoring of key power parameters, including voltage, current, and power factor. This solution offers scalability and cost-effectiveness by eliminating the need for extensive infrastructure. The methodology involves designing both hardware and firmware for the transmitter and receiver components and developing a communication algorithm to optimize data transfer efficiency. The system was tested in various environments: indoor, outdoor, and radio communication scenarios. Performance varied across environments, with outdoor and higher-floor tests experiencing more significant interference, which impacted transmission quality. The system achieved an average transmission time of 42.64 seconds and an error rate of 0.56% across 16 channels, demonstrating competitive reliability compared to existing wireless systems. Future research could explore adaptive modulation techniques to enhance data reliability in high-interference environments, improving the system's robustness for large-scale deployments.

Authors

Publication Details

Journal
Control Systems and Optimization Letters
Published
2025-03-08
DOI
https://doi.org/10.59247/csol.v3i1.181
Primary Topic
Speech and Audio Processing
Type
article
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article

Audio-Based Telemetry Using HT Radios for Remote Monitoring of Renewable Energy Systems

Ahmad Rahmad Muzadi, Prisma Megantoro, V. Samuthira Pandi, Sigit Dani Perkasa
Control Systems and Optimization Letters
Speech and Audio Processing
article

Audio-Based Telemetry Using HT Radios for Remote Monitoring of Renewable Energy Systems

Ahmad Rahmad Muzadi, Prisma Megantoro, V. Samuthira Pandi, Sigit Dani Perkasa
article en

Abstract

Effective monitoring of renewable energy systems, such as wind turbines and photovoltaic arrays, is essential for optimizing energy production. However, traditional wired monitoring systems are expensive and lack flexibility. This study develops a reliable wireless monitoring system that addresses the limitations of wired alternatives, using a PZEM-004T power meter, Arduino Uno R3, and BF-888S HT radios. The system employs audio-modulated binary encoding for long-range, low-cost data transmission, enabling real-time monitoring of key power parameters, including voltage, current, and power factor. This solution offers scalability and cost-effectiveness by eliminating the need for extensive infrastructure. The methodology involves designing both hardware and firmware for the transmitter and receiver components and developing a communication algorithm to optimize data transfer efficiency. The system was tested in various environments: indoor, outdoor, and radio communication scenarios. Performance varied across environments, with outdoor and higher-floor tests experiencing more significant interference, which impacted transmission quality. The system achieved an average transmission time of 42.64 seconds and an error rate of 0.56% across 16 channels, demonstrating competitive reliability compared to existing wireless systems. Future research could explore adaptive modulation techniques to enhance data reliability in high-interference environments, improving the system's robustness for large-scale deployments.

Control Systems and Optimization LettersVol. 3(1)
Openalex Percentile: Top 90%
Speech and Audio Processing
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Audio-Based Telemetry Using HT Radios for Remote Monitoring of Renewable Energy Systems — Ahmad Rahmad Muzadi, Prisma Megantoro, et al. · Control Systems and Optimization Letters (2025) | TGRS Research Map | TGRS