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Intelligent IOT Framework for Precision Agriculture using Cloud and AI Based Smart Irrigation

Nafiza1 , N.Ganesh²
¹Assistant Professor, Department of Electronics and Communication Engineering, nafiza.ece@siddhartha.co.in,
Siddhartha Institute of Technology and Sciences
²Assistant Professor, Department of Electronics and Electricals Engineering,
nomula.ganesh@siddhartha.co.in, Siddhartha Institute of Technology and Sciences

Abstract
AI and IoT are turning traditional agriculture into data-driven systems that enhance production and sustainability. Thisresearch introduces AI-powered IoT. Precision farming's smart irrigation and fertilizer management maximizes resourceuse and crop yield in real time. A dense IoT sensor network monitors soil water, nutrient levels, humidity, temperature,and crop phenology in real time in the proposed system. AI approaches like Random Forest, LSTM networks, andReinforcement Learning models analyze these streams for predictive and adaptive decision-making. The Random Forestalgorithm identifies soil conditions and determines nutrient deficiencies, while LSTM models predict irrigation needs bystudying soil moisture and weather patterns. Reinforcement Learning optimises irrigation and fertiliser application using
real-time soil sensor and vegetation response indicator data to maximise water and nutrient supply with minimal waste.Farmers and agricultural stakeholders can use a single dashboard for real-time data processing, remote monitoring, andautonomous control with edge analytics and cloud computing.Field tests show the technique saves 30% water andfertilizer (International Journal Advanced Research, www.ijarp.com). ISSN 2456-9992 Page: 01-25 Research ArticleVolume: 01 Issue: 03 Received: 14 November 2025, Revised: 04 December 2025, Published: 24 December 2025Chandigarh College of Engineering, Chandigarh Group of Colleges, Jhanjeri, Mohali, Punjab, India – 140307,Department of Computer Science and Engineering Associate Professor R Naveenkumar is the corresponding author.International Journal Advanced Research Publications www.ijarp.com 2 Improves yield consistency and soil fertilityabove traditional methods. The modular and extendable design suits small and large farms and adjusts to different crop varieties and weather. This study shows that AI-IoT convergence in precision agriculture can address global food security, resource scarcity, and environmental sustainability. The AI-driven IoT framework automates and optimizes farm choices from soil to harvest, promoting sustainable smart farming.
Keywords: Precision Agriculture, IoT, Artificial Intelligence, Smart Irrigation, Fertilizer Management, Machine Learning, Sustainability.