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@article{198069,
        author = {Nilesh Prabhakar Pande and Dimpal Pitambar Alokar and Prof. M. E. Maniyar},
        title = {AI-Driven Predictive Women Safety Monitoring System Using Geospatial Risk Analytics and Automated SOS},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {14761-14767},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198069},
        abstract = {The women safety is a complex and critical problem in current urban environments. Current safety applications available in the market rely mostly on manual trigger for distress situation and seem to focus more on the response phase of a crime after the incidence instead of proactive approaches. In this paper, we exhibit the design of AI-driven intelligent women safety monitoring system with prime focus on predicting risk factors and proactive safety advice. It is achieved by machine learning techniques and geospatial analysis based on predicting the risk factors in a specific location considering previously reported incident reports, current user location coordinates, time of occurrence and user generated reports. Dynamic risk scoring module dynamically assigns a risk status (safe, moderate and high) to any given location with a heat-map based visualization and on-going risk assessment of any user based on the monitoring of their coordinates, provide advance alerts about risky location. Automatic SOS triggers system helps send live emergency alerts with location to pre-specified contacts or authorities. A chatbot based safety assistant provides rapid responses and hands-free control during the emergency situation. Learning continuously with reports and feedback makes it more accurate in future predictions.},
        keywords = {Artificial Intelligence, Women Safety Systems, Geospatial Risk Analysis, Safety Heatmaps, Automated SOS Alerts, Crime Data Analysis, Geofencing, Predictive Safety Applications.},
        month = {April},
        }