A System of IoT Devices to prevent Overloading and Underloading of Railway Wagons
The ever-increasing demand for railway freight transportation necessitates improved operational efficiency and safety. However, underloading and overloading of wagons pose significant challenges, leading to inefficiencies and safety hazards. This research work presents a novel IoT based system to tackle this issue. The proposed system employs weight sensors strategically placed under wagons. These continuously monitor the load in real-time, capturing valuable data on weight distribution and total cargo mass. Leveraging an IoT network, the collected data is transmitted to a central monitoring system. This system analyses the weight data and identifies any deviations from permissible loading limits, including both underloading and overloading. For effective analysis, it is imperative that the load sensors undergo thorough calibration to mitigate the likelihood of errors. Ensuring the precise calibration of every load sensor utilized for research is paramount to mitigating potential disruptions. Upon detecting such anomalies, the system triggers automated alerts. The real-time monitoring and intelligent management of wagon load offered by this IoT system provides a multifaceted solution. It not only enhances the safety by preventing accidents caused by improper loading but also optimizes operational efficiency by ensuring wagon utilization and reducing unnecessary delays. Thus, contributing significantly to a safer and more efficient railway freight transportation system.
Authors
- Rajat Sharma (ORCID: https://orcid.org/0000-0003-2599-8551)
- Navjot Rathour (ORCID: https://orcid.org/0000-0002-7003-2257)
- Himanshu Himanshu (ORCID: https://orcid.org/0000-0003-2579-1585)
- Deepesh Gorai
- Princy Maurya
Institutions
- Chandigarh University (IN)
Publication Details
- Published
- 2024-08-29
- DOI
- https://doi.org/10.1109/iceect61758.2024.10739189
- Citations
- 1
- Primary Topic
- Transportation Systems and Safety
- Type
- article
- Field-Weighted Citation Impact
- 0.63