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- W4200609732 abstract "Urban cities in India are becoming smartness when it has properly synchronized with parking lots. In recent years urban cities in India are facing a lot of challenges during the availability of parking areas for their citizens as it has not well organized like assign parking lot at people immediately when it is free, squeeze the parking space according to size of vehicles and many more. In this paper this proposed a model called DCTSPA (Data;Collect;Transmit;Storage;Process;Application) that would be undertaken for the city planner, government and citizen for providing smart parking system in urban cities. This model describes about how data are collected, transmitted, storage, processing and providing good services to their citizen in terms of quality and availability. While providing smart parking system, first of all adding Internet-Of- Things (IoT)-enabled sensors in parking areas that collect the data for processing with help of deep learning algorithms and assigns parking areas as per people's requirement. Smart IoT devices with Deep learning technology delivers powerful performances in smart cities like as able to recognize hazards from many single pictures to give better accuracy. This proposed work mainly focus on two latest technology called as i) Picterra, an Artificial Intelligence (AI) based software designed in such a way that can identify, map objects through satellite and also able to get actionable insights faster and the ii) second one is the CivicSmart, that has smart parking meters programmed with deep learning algorithm which might fix in the residents, malls and any other parking spots to reduce the vehicle waiting time, traffics and many more in Smart City framework." @default.
- W4200609732 created "2021-12-31" @default.
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- W4200609732 date "2021-10-08" @default.
- W4200609732 modified "2023-09-28" @default.
- W4200609732 title "DCTSPA: A Proposed Model for Controlling Parking Spots" @default.
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- W4200609732 doi "https://doi.org/10.1109/apsit52773.2021.9641154" @default.
- W4200609732 hasPublicationYear "2021" @default.
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