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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM37903
Volume:
8 |
10 |
Oct 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
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.
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Publication Date
12/9/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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