A COMPREHENSIVE REVIEW ON IOT AND EDGE AI-BASED PRECISION AGRICULTURE SYSTEM FOR WATER OPTIMIZATION

Authors

  • Om Gaikwad UG Student, Department of Electronics and Telecommunication Engineering SKN Sinhgad College of Engineering, Pandharpur, India. Author
  • Shriraj Chavan UG Student, Department of Electronics and Telecommunication Engineering SKN Sinhgad College of Engineering, Pandharpur, India. Author
  • Krushnadev Gaikwad UG Student, Department of Electronics and Telecommunication Engineering SKN Sinhgad College of Engineering, Pandharpur, India. Author
  • Prof. S. R. Takale Assistant Professor, Department of Electronics and Telecommunication Engineering SKN Sinhgad College of Engineering, Pandharpur, India. Author

Keywords:

Internet of Things (IoT), Edge AI, Precision Agriculture, Smart Irrigation, Water Optimisation, Soil Moisture Monitoring, Machine Learning, Real-Time Data Processing, Automated Irrigation System, Sustainable Agriculture, Cloud Integration, Resource Management.

Abstract

Water scarcity and inefficient irrigation practices remain major challenges in modern agriculture, leading to reduced crop yield, resource wastage, and increased production costs. The proposed project, “IoT and Edge AI-Based Precision Agriculture System for Water Optimisation,” aims to develop an intelligent, real-time irrigation management system that optimises water usage through data-driven decision-making at the edge. The system integrates Internet of Things (IoT) sensors such as soil moisture, temperature, humidity, and light intensity sensors to continuously monitor field conditions. The collected data is processed locally using an Edge AI module, enabling real-time analysis and predictive irrigation control without relying entirely on cloud connectivity. By deploying machine learning algorithms at the edge, the system can determine optimal watering schedules based on soil conditions, crop requirements, and environmental factors, thereby minimising water wastage and ensuring efficient irrigation. A cloud platform is incorporated for long-term data storage, visualisation, and remote monitoring via a web or mobile dashboard. This hybrid architecture enhances scalability, reduces latency, and improves reliability in rural areas with limited internet connectivity. Automated irrigation control using smart valves or pumps ensures precise water delivery tailored to specific crop zones.

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Published

08-10-2026

How to Cite

A COMPREHENSIVE REVIEW ON IOT AND EDGE AI-BASED PRECISION AGRICULTURE SYSTEM FOR WATER OPTIMIZATION. (2026). International Journal of Mechanical Engineering Research and Technology , 18(4), 625-657. https://ijmert.com/index.php/ijmert/article/view/316