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@article{176541,
        author = {Mohammed Imran and Sai Kiran Kasarla and Ram Mohan Rao},
        title = {Women Safety Analytics - Protecting Women From Safety Threats},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {8078-8083},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176541},
        abstract = {Women's safety is a major social issue. As
women nowadays are more than ever worried about
being victimized, assaulted, or finding themselves in
dangerous locations, this project aims to examine,
anticipate, and stimulate action through data analysis,
AI, and machine learning. The relevant system
evaluates different data points ranging from past
occurrences of crimes to socioeconomic contribution
through continuous surveillance and geographic
location. It performs real time analysis through data
received from CCTV. The machine learning algorithms
derive correlations and obtain detection to evaluate risk
and recognize real time events like rapid movements.
Through evaluation of past incidents and contributions
of situations, zones can be identified that reflect how
dangerous a zone is for women.},
        keywords = {CNN-Based Gender Classification; deepSORT-Based Person Tracking; MiDaS Monocular Depth Estimation; Nominatim; Optical Flow Analysis; Spatiotemporal Hotspot Analytics; Real-Time Video Processing; YOLOv8},
        month = {May},
        }