Scholarlink

This paper discusses on development of an integrated IoT and machine learning system for monitoring solar energy on small farms, aiming to boost energy efficiency through real-time data analytics and predictive modeling. Leveraging Firebase for data storage and ESP32 microcontrollers, the system gathers solar panel measurements via IoT sensors. The Long Short-Term Memory (LSTM) model developed using Python and TensorFlow, forecasts solar power generation. Data preprocessing involves loading, cleaning, resampling, and normalizing historical solar data. A user-friendly interface developed with Flask allows seamless interaction, enabling farmers to input parameters and view predictions. The AI model effectively captures solar generation patterns, optimizing energy use and reducing grid dependence. Future enhancements include improving hardware configuration and incorporating advanced sensors for increased accuracy and reliability.

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Integrated IoT and Machine Learning System for Solar Energy Monitoring on Small Farms

  • 会议论文

  • 发表日期：

    2025年

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  • Muhammad Amen Mohd Shahid,
  • Siti Zuraidah Ibrahim,
  • Faridah Hanim Mohd Noh,
  • Wasana Boonsong

摘要

This paper discusses on development of an integrated IoT and machine learning system for monitoring solar energy on small farms, aiming to boost energy efficiency through real-time data analytics and predictive modeling. Leveraging Firebase for data storage and ESP32 microcontrollers, the system gathers solar panel measurements via IoT sensors. The Long Short-Term Memory (LSTM) model developed using Python and TensorFlow, forecasts solar power generation. Data preprocessing involves loading, cleaning, resampling, and normalizing historical solar data. A user-friendly interface developed with Flask allows seamless interaction, enabling farmers to input parameters and view predictions. The AI model effectively captures solar generation patterns, optimizing energy use and reducing grid dependence. Future enhancements include improving hardware configuration and incorporating advanced sensors for increased accuracy and reliability.