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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM20235
Volume:
7 |
5 |
May 2023
Pages:
1-5
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.
Department of Electrical and Electronics Engineering
Ballari Institute of Technology and Management, Ballari, Karnataka, India
Department of Electrical and Electronics Engineering
Ballari Institute of Technology and Management, Ballari, Karnataka, India
Department of Electrical and Electronics Engineering
Ballari Institute of Technology and Management, Ballari, Karnataka, India
Department of Electrical and Electronics Engineering
Ballari Institute of Technology and Management, Ballari, Karnataka, India
Railway transportation is one of the most widely used modes of transportation for both passengers and goods. Although railway systems are generally considered safe, accidents caused by obstacles on railway tracks, fire or smoke inside trains, flooding, track defects, and operational failures may result in collisions, derailments, injuries, loss of life, and property damage. This paper presents an Arduino Uno-based train accident prevention system intended to identify hazardous conditions and provide an early warning to the train operator. The proposed system uses an Arduino Uno as the main processing unit along with sensors for detecting obstacles and other abnormal conditions. An ultrasonic sensor detects objects present in the path of the train, while LEDs and buzzers provide visual and audible warnings. Sensor information is processed by the Arduino in real time so that appropriate warning or preventive action can be initiated. The developed approach provides a simple, economical, and low-power solution for improving railway safety. The experimental implementation demonstrates that the proposed system can detect obstacles and activate warning indications, thereby providing an opportunity for the operator to stop the train before a potential collision.
KEYWORDS
An Arduino Uno-based train accident prevention system has been presented for improving railway safety through real-time detection and warning. The developed prototype primarily employs an ultrasonic sensor to detect obstacles present in the path of the train. When an obstacle is detected, the Arduino Uno processes the sensor information and activates LEDs and buzzers to warn the operator. The project also considers the detection of smoke and flooding as additional safety measures. The implementation demonstrates that a low-cost embedded controller and suitable sensors can be used to develop a basic railway safety system. The Proteus simulation and prototype concept indicate the potential of sensor-based monitoring to improve the reliability of railway safety systems. With further development, integration of automatic braking, long-range communication, and additional sensors could make the proposed approach more effective for practical railway accident prevention.
[1] P. Navaraja, “Crack Detection System for Railway Track Using Ultrasonic and PIR Sensor,” vol. 5, 2014. [2] D. Sinha and F. Feroz, “Obstacle Detection on Railway Tracks Using Vibration Sensors and Signal Filtering Using Bayesian Analysis,” IEEE Sensors Journal, vol. 16, no. 3, Feb. 2016. [3] Krishna, Shashi Yadav, and Nidhi, “Automatic Railway Gate Control Using Microcontroller,” Oriental Journal of Computer Science & Technology, vol. 6, no. 4, Dec. 2013. [4] J. Xuer, “Visual Monitoring Based Railway Grade Crossing Surveillance System,” in Proc. Congress on Image and Signal Processing, 2008. [5] Pololu, sensor and electronic component technical resource. [6] Carnegie Mellon Robotics Academy, ultrasonic sensor technical resource. [7] PiBorg, “HC-SR04 Ultrasonic Sensor,” technical resource. [8] Electrosome, “Interfacing Rain Sensor with Arduino,” technical resource. [9] SainSmart, “MQ-5 Smoke/Gas Detector Sensor,” technical resource.
Publication Date
5/30/2023
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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