International Journal of Emerging Research in Science, Engineering, and Management
Vol. 2, Issue 1, pp. 21-27, January 2026.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Safe Movement and Accident Prevention for the Railways
M.Manivannan
G.Hema
P.Manasa
D.Bindhu
D.Mohith
M.Divakar
Department of CSE, Siddartha Institute of Science and Technology, Puttur, India.
Abstract: Railway transportation systems operate in complex and safety-critical environments where accidents may occur due to factors such as human-behavioral risks, trespassing, wildlife intrusion, overcrowding, and operational monitoring limitations. Traditional rule-based surveillance and manual observation methods often fail to identify subtle anomalies or emerging accident-risk situations in real time. This study proposes an intelligent safety-enhancement framework for railway-station and track-side environments, focusing on proactive anomaly detection, risk-event analysis, and safety-aware decision support. The framework integrates multi-source monitoring data, behavioral-pattern assessment, and analytical evaluation to identify unsafe events such as unauthorized track access, congestion-risk formation, and hazardous movement near critical zones. Experimental evaluation is conducted using standard performance metrics including accuracy, precision, recall, F1-score, and error rate to assess detection reliability and operational relevance. The findings demonstrate that intelligent analytical monitoring enhances situational awareness, supports early-stage accident prevention, and strengthens overall railway-safety management capabilities.
Keywords: Railway Safety, Accident Prevention, Intelligent Monitoring, Anomaly Detection, Human Factors.
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