AN IOT AND DEEP LEARNING–BASED SMART SYSTEM FOR PRECISION AGRICULTURE

Abstract

Precision agriculture has emerged as a modern approach to improve agricultural productivity by integrating advanced technologies such as the Internet of Things (IoT) and Artificial Intelligence. Traditional farming methods rely heavily on manual monitoring and decision-making, which can lead to inefficient resource utilization and reduced crop yield. This paper proposes an IoT and Deep Learning–Based Smart System for Precision Agriculture that enables real-time monitoring and intelligent analysis of agricultural parameters. The proposed system utilizes IoT sensors to collect environmental data such as soil moisture, temperature, and humidity, while deep learning algorithms analyze crop images to detect diseases and assess plant health. The collected data is transmitted to a cloud-based platform for analysis and monitoring. The system assists farmers in making informed decisions regarding irrigation, disease control, and crop management. The proposed solution enhances productivity, reduces resource wastage, and promotes sustainable farming practices.