As more and more smart cities are planned in India, there is a growing need for smart parking and smart transportation. Parking has been identified as a major challenge to traffic network and urban life quality. Already most of the cities are facing the problem of pollution. Due to drivers struggling for finding the parking area, 30% of traffic congestion occurs according to industry data. There is also a need for secure, efficient, intelligent and reliable systems that can be used for searching the unoccupied parking facilities, guide towards the parking facilities, and negotiate the parking fee. This would help in the proper management of the parking facility. There is no publically available data on parking in India. This work would be useful in creation of such datasets. Image based model has been proposed to identify the slot occupancy status. A prediction model has also been incorporated in the system to predict the occupancy rate and thereby help the management in better management of parking lots. One of the machine learning method, linear regression is used for predicting the number of car parked every hour. A slot based approach was used and the performances of prediction algorithms were compared. © 2018, Springer International Publishing AG.
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K. A. Maheshwari and P. Sivakumar, B., “Use of predictive analytics towards better management of parking lot using image processing”, Lecture Notes in Computational Vision and Biomechanics, vol. 28, pp. 774-787, 2018.