Smart Tourist Safety Monitoring and Incident Response System Using AI

Abstract

Tourists travelling through remote, forested, hilly, wildlife, and adventure destinations may encounter disorientation, restricted areas, accidents, health emergencies, crime, or communication failure. Conventional mechanisms often separate location tracking, emergency reporting, identity verification, and authority coordination, which can delay intervention when a tourist cannot communicate or when a location signal lacks behavioural context. This paper proposes a unified Smart Tourist Safety Monitoring and Incident Response System that combines a mobile application, GPS tracking, geo-fencing, artificial-intelligence and machine-learning analytics, blockchain-based digital tourist identity, authority monitoring, and optional IoT wearable devices. After registration, a tourist receives a Digital Tourist ID associated with the mobile application or wearable. Location, movement, activity, and optional health signals are processed to identify unsafe-zone entry, route deviation, prolonged inactivity, fall-like events, and explicit SOS requests. Alerts are delivered to an authority dashboard for verification, prioritisation, escalation, and response recording. The paper presents the research foundation, system architecture, operational methodology, implementation plan, and evaluation framework. It does not claim completed experimental results; accuracy, latency, scalability, privacy, and field effectiveness remain evaluation objectives.