Abstract
An automated crowd control system is a service that sends real-time crowd density data from inside the bus to a user's handheld device near the bus stop. It is a cohesive solution when it comes to managing crowds without human intervention. Machine learning is used in the M-Vahitaram app to predict bus crowd density, and a cloud database is used to notify commuters within 200 m of the bus. The choice of whether or not to board the approaching bus can then be made. The suggested approach forecasts crowd density with a 96 percent accuracy. Equipping the commuters or the travelers with the details regarding the present or the current crowd density on a particular bus will benefit them to make educated decisions about which bus to take or whether to seek alternative transportation. As a consequence, there is neither traffic congestion nor unequal crowd distribution among buses, ensuring the most effective use of bus transit.
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Jadhav, P., Sawant, S., Shadi, J., Sonawane, T., Charniya, N., Yeole, A. (2023). M-Vahitaram: AI-Based Android Application for Automated Crowd Control Management in Bus Transport Service. In: Noor, A., Saroha, K., Pricop, E., Sen, A., Trivedi, G. (eds) Proceedings of Emerging Trends and Technologies on Intelligent Systems. Advances in Intelligent Systems and Computing, vol 1414. Springer, Singapore. https://doi.org/10.1007/978-981-19-4182-5_12
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DOI: https://doi.org/10.1007/978-981-19-4182-5_12
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