SMART PEST GUARDIAN: IOT AND AI-DRIVEN INSECT DETECTION WITH IOT

Abstract

The increasing demand for precision agriculture has brought forward the necessity for intelligent systems capable of early pest detection and intervention. This paper introduces the "Smart Pest Guardian," an IoT-based framework that integrates Artificial Intelligence (AI) for real-time insect detection in agricultural fields. The system utilizes an array of sensors deployed across fields, collecting environmental and motion data to monitor pest activity. Through a convolutional neural network (CNN)-based image classification model, combined with data from ultrasonic sensors, the system efficiently identifies insect species and their infestation levels. The IoT architecture facilitates seamless communication between sensors, a central processing unit, and a cloud-based platform, allowing for the real-time analysis and alert generation. The proposed model offers enhanced precision, scalability, and reduces the dependency on manual inspection. The effectiveness of the Smart Pest Guardian is evaluated through several field tests, showing significant improvements in pest management efficiency and timely intervention. This research highlights the potential of integrating IoT and AI technologies to revolutionize pest control methods in precision agriculture.