Machine Accident Analytics and Protection System (MAAPS): An IoT and Data Analytics Based Approach to Enhance Safety in Agricultural Machinery

The agricultural industry is often associated with significant risks, particularly concerning machine-related accidents. This paper presents the Machine Accident Analytics and Protection System (MAAPS), an Internet of Things (IoT) and data analytics-based system designed to enhance safety in the operation of chaff cutters. By integrating PIR sensors and RFID technology, MAAPS aims to prevent accidents through real-time monitoring and immediate machine shutdown when safety limits are breached. The findings reveal that a significant percentage of accidents occur during specific time frames, particularly between 3:00 PM and 6:00 PM, and are often associated with operator fatigue. This paper discusses the system's design, implementation, and implications for improving safety standards in agricultural machinery. Key Words: IoT, data analytics, safety, chaff cutter, machine accidents