IoT-Based Smart Agriculture System Integration of Sensor Networks with AI for Crop Yield Optimization
Year: 2025
Type: article
Abstract: The application of IoT sensor networks based on AI devices in agriculture enables monitoring of the systems and predictive management to determine optimum usage of resources real-time. This paper introduces a smart agriculture system that covers a system that uses a sensor-based monitoring technique, edge computing, and an AI-based crop yield prediction algorithm for improvement of efficient crop production. The system utilizes a process flow at the system level involving data acquisition from the sensors, artificial intelligence decision-making component, and closed feedback loop for high precision farming. Explorations conclude that there is 92% enhancement in the chances of crop yield prediction, 40% enhancement in the use of resources and they also show 35% reduction in operation costs. Integration of edge computing lowers the processing time to 38% hence the ability to attend to crop health complications instantly. These provide an endorsement of IoT & AI integration in the development of efficient and profitable smart farming innovation within a controlled decision-making framework.
DOI: 10.54228/m684bg51
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W4411100434