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@article{154092,
        author = {Deepthi VS and Venkat Chavan N and Sandhya Shanbhag and Sakshi S Dandappala},
        title = {Study on Crowd Density Estimation and Location Prediction in Public Transport System},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {10},
        pages = {30-36},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=154092},
        abstract = {Existing and Emerging technologies help to solve real-time problems without manual interference. Crowd analysis and location prediction in transport systems is an essential topic for research. It not only helps in transport system management but also in urban planning, public safety, and environment management. These Intelligent systems provide a vital role in extracting the location of transport and calculating the number of passengers, with the shortest path of travel. This survey paper covers different approaches for crowd density estimation such as deep learning, IoT, algorithms, image, and video-based and for location prediction using GPS tracking, smartphone technology, and so on. Therefore, an appropriate method has to be chosen to get maximum accuracy with solutions for all the existing problems with few enhancements.},
        keywords = {Crowd Density, IOT, Location Tracking, Prediction, GPS.},
        month = {},
        }