Department of Computer Science, Sam Houston State University, Huntsville, AL 77340, USA.
School of Computer Science, Columbus State University, Columbus, GA 31907, USA.
Sensors (Basel). 2023 Apr 11;23(8):3880. doi: 10.3390/s23083880.
As technology continues to evolve, our society is becoming enriched with more intelligent devices that help us perform our daily activities more efficiently and effectively. One of the most significant technological advancements of our time is the Internet of Things (IoT), which interconnects various smart devices (such as smart mobiles, intelligent refrigerators, smartwatches, smart fire alarms, smart door locks, and many more) allowing them to communicate with each other and exchange data seamlessly. We now use IoT technology to carry out our daily activities, for example, transportation. In particular, the field of smart transportation has intrigued researchers due to its potential to revolutionize the way we move people and goods. IoT provides drivers in a smart city with many benefits, including traffic management, improved logistics, efficient parking systems, and enhanced safety measures. Smart transportation is the integration of all these benefits into applications for transportation systems. However, as a way of further improving the benefits provided by smart transportation, other technologies have been explored, such as machine learning, big data, and distributed ledgers. Some examples of their application are the optimization of routes, parking, street lighting, accident prevention, detection of abnormal traffic conditions, and maintenance of roads. In this paper, we aim to provide a detailed understanding of the developments in the applications mentioned earlier and examine current researches that base their applications on these sectors. We aim to conduct a self-contained review of the different technologies used in smart transportation today and their respective challenges. Our methodology encompassed identifying and screening articles on smart transportation technologies and its applications. To identify articles addressing our topic of review, we searched for articles in the four significant databases: IEEE Xplore, ACM Digital Library, Science Direct, and Springer. Consequently, we examined the communication mechanisms, architectures, and frameworks that enable these smart transportation applications and systems. We also explored the communication protocols enabling smart transportation, including Wi-Fi, Bluetooth, and cellular networks, and how they contribute to seamless data exchange. We delved into the different architectures and frameworks used in smart transportation, including cloud computing, edge computing, and fog computing. Lastly, we outlined current challenges in the smart transportation field and suggested potential future research directions. We will examine data privacy and security issues, network scalability, and interoperability between different IoT devices.
随着技术的不断发展，我们的社会变得更加丰富多彩，拥有越来越多的智能设备，帮助我们更高效、更有效地完成日常活动。我们这个时代最重要的技术进步之一是物联网 (IoT)，它将各种智能设备（如智能手机、智能冰箱、智能手表、智能火灾报警器、智能门锁等）互联起来，使它们能够无缝地相互通信和交换数据。现在，我们使用物联网技术来开展我们的日常活动，例如交通。特别是，智能交通领域引起了研究人员的兴趣，因为它有可能彻底改变我们运输人和货物的方式。物联网为智慧城市中的驾驶员提供了许多好处，包括交通管理、改善物流、高效停车系统和增强安全措施。智能交通是将所有这些好处集成到交通系统应用中的过程。然而，作为进一步提高智能交通所提供的好处的一种方式，已经探索了其他技术，例如机器学习、大数据和分布式账本。它们在交通系统中的一些应用示例包括路线优化、停车、路灯、事故预防、异常交通条件检测和道路维护。在本文中，我们旨在提供对前面提到的应用程序发展的详细了解，并研究基于这些领域的当前研究。我们旨在对当今智能交通中使用的不同技术及其各自的挑战进行自我包容的审查。我们的方法包括识别和筛选有关智能交通技术及其应用的文章。为了确定解决我们综述主题的文章，我们在四个主要数据库中搜索了文章：IEEE Xplore、ACM 数字图书馆、Science Direct 和 Springer。因此，我们检查了使这些智能交通应用程序和系统能够运行的通信机制、架构和框架。我们还探讨了智能交通中使用的通信协议，包括 Wi-Fi、蓝牙和蜂窝网络，以及它们如何促进无缝数据交换。我们深入研究了智能交通中使用的不同架构和框架，包括云计算、边缘计算和雾计算。最后，我们概述了智能交通领域的当前挑战，并提出了潜在的未来研究方向。我们将检查数据隐私和安全问题、网络可扩展性以及不同物联网设备之间的互操作性。
