智能停车系统中的物联网回归技术:调查

Kaleeem Shaik Kaleeem, Anuradha Samkham Raju, Nabil Giweli, A. Dawoud, P. Prasad, Mousa Abu Kashef
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引用次数: 2

摘要

智慧城市是物联网取得巨大成功的主要领域之一,它收集和处理大量数据以促进不同的应用。智能停车是不断发展的智慧城市应用之一。人口的快速增长也导致了大量的车辆,这可能会导致城市交通拥堵。这种交通拥堵加剧了城市交通的问题。城市流动性可能对生活质量和经济产生不利影响。通过对停车系统的有效管理,这个问题可以得到缓解。本研究旨在回顾智能停车系统中使用的基于物联网的回归技术,以克服城市交通问题。利用基于物联网的回归技术对停车区域的车位进行预测,使驾驶员能够及时获得停车位,缓解城市交通问题。结果表明,回归技术可以有效地预测车位可用性。本研究全面回顾了物联网智能停车应用中使用的回归技术。为了更好地理解这项工作,还介绍了系统架构。
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IoT Regression Techniques In Smart Parking Systems: Survey
Smart cities are one of the main areas where IoT showed great success, collecting and processing enormous amounts of data to facilitate different applications. Smart parking is one of the evolving smart cities applications. The rapid increase in the population also results in a high number of vehicles that may lead to traffic congestion in urban cities. This traffic congestion is increasing the problem of urban mobility. Urban mobility may have an adverse impact on the quality of life as well as the economy. This problem can be mitigated with the efficient management of the parking systems. This work aims to review the IoT-based regression techniques used in smart parking systems to overcome the problem of urban mobility. IoT-based regression techniques are used to predict parking space in the parking area so that the drivers can get parking space on time and the problem of urban mobility can be mitigated. It was identified that regression techniques efficiently predicted parking space availability. This study provides a comprehensive review of regression techniques used in IoT smart parking applications. The system architecture was also presented to get a better understanding of this work.
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