A Framework for Real-Time Crop Monitoring and Yield Optimisation: Improving Precision Agriculture with IoT-Driven Sensor Networks and Data Analytics

¹ Department of computers Techniques engineering, College of technical engineering, The Islamic University of Najaf, Iraq The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq The Islamic University of Babylon, Babylon, Iraq
² Ahl Al Bayt University, Karbala, Iraq
³ Department of Information Technology, Gokaraju Rangaraju Institute of Engineering and Technology, JNTUH, Bachupally, Hyderabad, Telangana, India

^* Corresponding author: ammar.hameed.it@gmail.com

Abstract

Using smart data analytics and IoT-driven sensor networks to enhance precision agriculture, the paper provides a whole framework for real-time Crop Monitoring and yield optimization. Using IoT-Driven Sensor Networks (CM-IoT-SN), Crop Monitoring aims to provide farmers practical data for maximizing yields and improving crop condition. Many times, existing precision agricultural technologies suffer from flaws such as poor data granularity, delayed feedback, and the difficulty to provide real-time monitoring across large agricultural fields. These weaknesses lower crop productivity and lead to less than perfect decision-making. To solve these challenges, CM-IoT-SN combines a network of IoT-enabled sensors continuously monitoring key environmental factors such as soil moisture, temperature, and nutrient levels. Advanced algorithms then utilize the realtime data acquired to provide farmers expected insights and quick advise.CM-IoT-SNs adoption across many test locations has proved its effectiveness in producing superior decision-making in crop management by means of exact, real-time monitoring and predictive analytics. Results reveal that this approach not only increases crop productivity however additionally reduces resource waste, therefore providing a sustainable substitute for modern agriculture.