Authors : Dr. Bharanidharan G, Dr. K. Sankar
DOI : 10.58532/nbennuramlab4p4c1
Volume : 1
Issue : 1
Year : 2026
Page No : 118-130
Rapid agricultural mechanization has boosted output but is hindered by equipment failures and inadequate maintenance, leading to high costs and downtime. This research proposes an IoT and AI-based predictive maintenance architecture for agricultural machinery to address these issues. The system employs IoT sensors to monitor key operational parameters like vibration and temperature, while AI models analyze real-time data to predict maintenance needs. The architecture aims to enhance farm efficiency, reduce maintenance costs, and improve machinery reliability by enabling early problem detection and scheduled maintenance. Its effectiveness is evaluated based on prediction accuracy and reduced unscheduled downtime, making it suitable for sustainable farming practices.