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Precision farming makes the most of water resources, particularly in regions with fertile land and dense populations. Redirecting excess water to arid areas is made possible by smart irrigation systems, which increase water efficiency. The intelligent irrigation system suggested in this research maximizes water use, minimizes human intervention, and automates watering. Soil moisture sensors and an Arduino-based system are used to collect data in real time. Soil moisture, crop and soil type, weather, temperature, and the last irrigation date are among the information gathered by a mobile application. To reduce over- and under-irrigation, a 95% accurate machine learning algorithm predicts irrigation requirements. The technology improves water management, lessens physical labour, and offers farmers an affordable option.

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Aqua Detection and Prediction Using IoT and Machine Learning

  • 会议论文

  • 发表日期：

    2026年

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  • Minal Barhate,
  • Harshal Marathe,
  • Mayur Chikhale,
  • Anushka Mangade,
  • Md. Ahsan Imam,
  • Sarthak Mate

摘要

Precision farming makes the most of water resources, particularly in regions with fertile land and dense populations. Redirecting excess water to arid areas is made possible by smart irrigation systems, which increase water efficiency. The intelligent irrigation system suggested in this research maximizes water use, minimizes human intervention, and automates watering. Soil moisture sensors and an Arduino-based system are used to collect data in real time. Soil moisture, crop and soil type, weather, temperature, and the last irrigation date are among the information gathered by a mobile application. To reduce over- and under-irrigation, a 95% accurate machine learning algorithm predicts irrigation requirements. The technology improves water management, lessens physical labour, and offers farmers an affordable option.