Smart Safe Navigation Using Machine Learning and Network-Based Location
Abstract
The increasing number of road accidents, unsafe travel routes, and delayed emergency responses has highlighted the need for intelligent safety-oriented navigation systems. This paper presents Smart Safe Navigation Using Machine Learning and Network-Based Location, an AI-powered platform designed to enhance public safety through intelligent route guidance, real-time monitoring, and emergency assistance. The proposed system integrates Machine Learning techniques, GPS-based location tracking, accident datasets, traffic analysis, geofencing, and location-based services to identify accident-prone areas and recommend safer travel routes. The system incorporates several advanced features, including live GPS tracking, crime and accident heatmaps, safe route recommendations, geofence-based safety alerts, SOS emergency services, emergency contact management, incident reporting, and an AI chatbot for user assistance. Historical Maharashtra Road accident data from 2022–2024 is utilized to analyze accident trends, identify dangerous zones, and perform risk prediction. An interactive analytics dashboard is also developed to visualize crashes, fatalities, black spots, peak accident timings, and district-wise accident statistics through graphs and heatmaps. By combining machine learning with network-based location technologies, the proposed system provides users with real-time safety information and emergency support. The platform aims to reduce accident risks, improve situational awareness, enhance emergency response efficiency, and promote safer travel experiences. The results demonstrate the effectiveness of intelligent navigation systems in improving road safety and supporting smart city transportation initiatives.
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