Abstract
With the advancement in transportation technology, the number of vehicles is increasing rapidly, but concerning that, the number of accidents is also increasing in the same proportion. Accidents are very common nowadays. Infrastructure is redefining and on-road speed of vehicles is increasing. Accident-prone areas are increasing. Millions of people losing their life due to accidents. This article analyses the data of India’s 11 states which are accident prone considering different time zone and proposes a new system that predicts the accident-prone areas and provides the most dangerous time for traveling along that route. A machine learning concept is used to train your system to make the best decisions based on experience. DBSCAN data algorithm with negative sampling is used to apply the machine learning concept in a better way. Through simulation results, it is cleared that number of accidents will reduce after applying the proposed concept.
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Khekare, G., Verma, P. (2021). Prophetic Probe of Accidents in Indian Smart Cities Using Machine Learning. In: Bhateja, V., Satapathy, S.C., Travieso-González, C.M., Aradhya, V.N.M. (eds) Data Engineering and Intelligent Computing. Advances in Intelligent Systems and Computing, vol 1407. Springer, Singapore. https://doi.org/10.1007/978-981-16-0171-2_18
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DOI: https://doi.org/10.1007/978-981-16-0171-2_18
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