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Smart Car Parking System Solution for the Internet of Things in Smart Cities

机译:智慧城市物联网智能停车场系统解决方案

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The Internet of Things (IoT) is able to connect billions of devices and services at anytime in any place, with various applications. Recently, the IoT became an emerging technology. One of the most significant current research discussion topics on the IoT is about the smart car parking. A modern urban city has over a million of cars on its roads but it does not have enough parking space. Moreover, most of the contemporary researchers propose management of the data on cloud. However, this method may be considered as an issue since the raw data is sent promptly from distributed sensors to the parking area via cloud and then received back after it is processed. This is considered as an expensive technique in terms of the data transmission as well as the energy cost and consumption. While the majority of proposed solutions address the problem of finding unoccupied parking space and ignore some other critical issues such as information about the nearest car parking and the roads traffic congestion, this paper goes beyond and proposes the alternative method. The paper proposes a smart car parking system that will assist users to solve the issue of finding a parking space and to minimise the time spent in searching for the nearest available car park. In addition, it provides users with roads traffic congestion status. Moreover, the proposed system collects the raw data locally and extracts features by applying data filtering and fusion techniques to reduce the transmitted data over the network. After that, the transformed data is sent to the cloud for processing and evaluating by using machine learning algorithms.
机译:物联网(IoT)能够随时随地通过各种应用程序连接数十亿个设备和服务。最近,物联网成为一种新兴技术。关于物联网,当前最重要的研究讨论主题之一是关于智能停车场。现代化的城市道路上有超过一百万辆汽车,但没有足够的停车位。此外,大多数当代研究人员建议对云上的数据进行管理。但是,由于原始数据会通过云从分布式传感器迅速发送到停车区,然后在经过处理后再接收回来,因此该方法可能会成为问题。就数据传输以及能量成本和消耗而言,这被认为是昂贵的技术。虽然大多数建议的解决方案都解决了寻找空置的停车位的问题,而忽略了一些其他关键问题,例如有关最近的停车位和道路交通拥堵的信息,但本文超越并提出了另一种方法。本文提出了一种智能停车场系统,该系统将帮助用户解决寻找停车位的问题,并最大限度地减少寻找最近的可用停车场所花费的时间。此外,它还为用户提供道路交通拥堵状况。此外,所提出的系统在本地收集原始数据,并通过应用数据过滤和融合技术来减少特征,以减少通过网络传输的数据。之后,将转换后的数据发送到云,以使用机器学习算法进行处理和评估。

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