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@article{172672,
        author = {Kishan M. Gopale and Dr. Gayatri Bhanadari and Gunjan G. Ahirrao and Nivas K. Bidave and Nikita T. Hajare},
        title = {Traffic Accident Data Analysis: Patterns and Hotspots},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {9},
        pages = {752-761},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=172672},
        abstract = {Traffic mishaps posture a critical open wellbeing issue, causing over 1.19 million passings yearly and coming about in serious wounds and financial misfortunes all inclusive. This audit synthesizes later headways in activity mishap information investigation, centering on distinguishing designs and mishap hotspots utilizing factual, machine learning, and profound learning strategies. The audit emphasizes the significance of combining spatial investigation, highlight extraction, and prescient modeling to progress street security. It moreover talks about the challenges of information quality, show generalization, and the integration of differing information sources. This paper points to supply a roadmap for future inquire about within the field of activity mishap forecast and avoidance.},
        keywords = {Traffic mischance investigation, designs, hotspots, machine learning, spatial examination, data-driven approaches, profound learning.},
        month = {February},
        }