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Precision agriculture plays a critical role in enhancing farming efficiency while minimizing environmental impacts. Excess pesticide use harms soil health, crop quality, and human safety. The system divides the field into micro-zones, each monitored by IoT sensors for soil, air, and climate data collected by an ESP32-WROOM-32 microcontroller. The data were transmitted to the ThingSpeak cloud platform, where a Random Forest classifier predicted pesticide usage levels as Low, Medium, or High. When environmental conditions permit, the system suggests natural alternatives, such as neem oil or biopesticides, to reduce chemical dependency. This zonal and data-driven methodology promotes sustainable pesticide use, empowers farmers to make informed decisions, and reduces the ecological footprint of agriculture.

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Smart Zonal Pesticide Control Using IoT Sensors and Machine Learning for Precision Agriculture

  • 会议论文

  • 发表日期：

    2026年

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  • Ch. RaviCharan,
  • Ch. Rupa,
  • Y. Sri Venkateswara Reddy,
  • J. V. N. Ganesh

摘要

Precision agriculture plays a critical role in enhancing farming efficiency while minimizing environmental impacts. Excess pesticide use harms soil health, crop quality, and human safety. The system divides the field into micro-zones, each monitored by IoT sensors for soil, air, and climate data collected by an ESP32-WROOM-32 microcontroller. The data were transmitted to the ThingSpeak cloud platform, where a Random Forest classifier predicted pesticide usage levels as Low, Medium, or High. When environmental conditions permit, the system suggests natural alternatives, such as neem oil or biopesticides, to reduce chemical dependency. This zonal and data-driven methodology promotes sustainable pesticide use, empowers farmers to make informed decisions, and reduces the ecological footprint of agriculture.