IOT based Wireless Sensor Network for Retracing the parked Vehicle

IF 1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS International Journal of Communication Networks and Distributed Systems Pub Date : 2019-07-15 DOI:10.30534/IJNS/2019/01842019
Swathi Sadasivan
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Abstract

It is expected to be in the next 100 years, world’s maximum population is going to be living in cities. Hence the usage of vehicle and its related services will be crucial. As the number of vehicles increases, parking of the vehicle in cities are going to be challenging issue, especially in terms of pollution and maintaining the eco system of the area. Many people are not interested to use traditional or automated parking area because of the difficulty they face during the usage. Even people find it difficult to trace the return path to their own vehicle. The larger number of smart car parking systems is implemented in various countries which normally solve the problem of parking space and effective utilization of utilities. But in a highly populated area safety of the people in a parking slot and retracing of the vehicle is going to be very challenging due to its nature of heterogeneous people and variety of vehicles. An IOT enabled Sensor network based Advanced parking space with camera and audio sensors will be able to collect large amount of data which can be utilized to generate interesting pattern using suitable machine learning algorithm. As the environment is complex and heterogeneous; a better optimization always will be able to provide improved safety to the people as well as vehicle in the area.
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基于物联网的无线传感器网络,用于追踪停放车辆
预计在未来100年内,世界上最多的人口将居住在城市。因此,车辆及其相关服务的使用将至关重要。随着车辆数量的增加,在城市停车将是一个具有挑战性的问题,特别是在污染和维护该地区的生态系统方面。由于在使用过程中遇到的困难,许多人对使用传统或自动化停车场不感兴趣。甚至人们也很难找到返回自己车辆的路径。智能停车系统在世界各国得到了广泛的应用,解决了停车空间和公用事业的有效利用问题。但在人口密集的地区,由于人群和车辆的多样性,停车位上人员的安全以及车辆的回溯将是非常具有挑战性的。基于物联网传感器网络的高级停车位,配备摄像头和音频传感器,将能够收集大量数据,这些数据可用于使用合适的机器学习算法生成有趣的模式。由于环境是复杂和异质的;更好的优化总是能够为该地区的人员和车辆提供更好的安全性。
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来源期刊
CiteScore
2.50
自引率
46.20%
发文量
57
期刊介绍: IJCNDS aims to improve the state-of-the-art of worldwide research in communication networks and distributed systems and to address the various methodologies, tools, techniques, algorithms and results. It is not limited to networking issues in telecommunications; network problems in other application domains such as biological networks, social networks, and chemical networks will also be considered. This feature helps in promoting interdisciplinary research in these areas.
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