Safe-Walk AI:A Proactive Multi-Model Intelligent Framework For Real-Time Last-Mile Personal Safety Using Vision, Audio, And Community Intelligence

Abstract

Even now, staying safe on short trips remains tough, particularly for women and those working late shifts once buses or trains stop. Most apps people rely on today only respond after something already went wrong - requiring a conscious tap for help once danger shows up. These setups fall short when someone cannot act fast enough because fear takes over, arms get locked, or surprise strikes happen. A fresh approach to staying safe rolls out through Safe Walk AI - one that acts ahead of trouble. Instead of reacting, it watches for warning signs before they grow. Instant responses come not from guesswork but from processed data in real time. Risk levels shift based on where someone goes, who they are, what they carry. Routes change automatically when conditions turn uncertain. Sounds around you can reveal hidden risks if patterns get analyzed on the fly. Cameras spot odd behavior earlier because software learns what normal looks like. Neighbors near and far contribute knowledge that shapes how warnings spread. Live video feeds get analyzed using a YOLO-style model to spot odd actions - like people hanging around too long, bunching up, or sticking behind others. Meanwhile, strange sounds possibly linked to stress or hostility are caught through an audio flag system. Context shapes how risky each moment feels: clock settings, darkness levels, user history, even local warning notices all influence the alert level assigned to every scene. When warning signs rise, Safe Walk AI kicks off safety steps - like turning on companion tracking, adjusting paths, or sending urgent alerts - by pushing live position updates. Unlike older systems using single panic buttons, tests in fake urban routes found better insight into threats, faster help arrival, and sharper reaction times. You might see this setup woven into urban networks, tech clusters, or school grounds - it bends without breaking, grows as needed.