Accident Severity Prediction and Real-Time Alert System Using Environmental and Temporal Factors
Dr. Akula Suneetha,
Tummala Jhansi,
Undrakonda Sriyamini,
Vaddeswarapu Pallavi,
Rathamsetty Renusri,
Vutukuri Sree Naga Lakshmi
Road accidents are among the leading causes of injuries and fatalities worldwide. Early assessment
of accident severity is crucial for prompt action and effective traffic man¬agement. Conventional
accident analysis techniques rely mostly on manual reporting and historical data, resulting in delayed
and inaccurate responses. This paper proposes a machine learning-based system to predict accident
severity using temporal param¬eters such as time of day, day of the week, and season, along with
environmental parameters such as weather, traffic, visibility, and road conditions. The system classifies
accident severity into three levels: low, medium, and high. In addition, a real-time alert mechanism
is integrated to automatically notify local hospitals, traffic authorities, and emergency services. The
proposed system aims to improve road safety, accelerate emergency response, and assist traffic control
authorities in decision-making.
