Fraga-Lamas Paula, Celaya-Echarri Mikel, Lopez-Iturri Peio, Castedo Luis, Azpilicueta Leyre, Aguirre Erik, Suárez-Albela Manuel, Falcone Francisco, Fernández-Caramés Tiago M
Department of Computer Engineering, Faculty of Computer Science, Centro de investigación CITIC, Universidade da Coruña, 15071 A Coruña, Spain.
School of Engineering and Sciences, Tecnologico de Monterrey, 64849 Monterrey, NL, Mexico.
Sensors (Basel). 2019 Jul 26;19(15):3287. doi: 10.3390/s19153287.
A smart campus is an intelligent infrastructure where smart sensors and actuators collaborate to collect information and interact with the machines, tools, and users of a university campus. As in a smart city, a smart campus represents a challenging scenario for Internet of Things (IoT) networks, especially in terms of cost, coverage, availability, latency, power consumption, and scalability. The technologies employed so far to cope with such a scenario are not yet able to manage simultaneously all the previously mentioned demanding requirements. Nevertheless, recent paradigms such as fog computing, which extends cloud computing to the edge of a network, make possible low-latency and location-aware IoT applications. Moreover, technologies such as Low-Power Wide-Area Networks (LPWANs) have emerged as a promising solution to provide low-cost and low-power consumption connectivity to nodes spread throughout a wide area. Specifically, the Long-Range Wide-Area Network (LoRaWAN) standard is one of the most recent developments, receiving attention both from industry and academia. In this article, the use of a LoRaWAN fog computing-based architecture is proposed for providing connectivity to IoT nodes deployed in a campus of the University of A Coruña (UDC), Spain. To validate the proposed system, the smart campus has been recreated realistically through an in-house developed 3D Ray-Launching radio-planning simulator that is able to take into consideration even small details, such as traffic lights, vehicles, people, buildings, urban furniture, or vegetation. The developed tool can provide accurate radio propagation estimations within the smart campus scenario in terms of coverage, capacity, and energy efficiency of the network. The results obtained with the planning simulator can then be compared with empirical measurements to assess the operating conditions and the system accuracy. Specifically, this article presents experiments that show the accurate results obtained by the planning simulator in the largest scenario ever built for it (a campus that covers an area of 26,000 m 2 ), which are corroborated with empirical measurements. Then, how the tool can be used to design the deployment of LoRaWAN infrastructure for three smart campus outdoor applications is explained: a mobility pattern detection system, a smart irrigation solution, and a smart traffic-monitoring deployment. Consequently, the presented results provide guidelines to smart campus designers and developers, and for easing LoRaWAN network deployment and research in other smart campuses and large environments such as smart cities.
智能校园是一种智能基础设施，智能传感器和执行器在其中协同工作，收集信息并与大学校园中的机器、工具和用户进行交互。与智能城市一样，智能校园对物联网（IoT）网络来说是一个具有挑战性的场景，特别是在成本、覆盖范围、可用性、延迟、功耗和可扩展性方面。到目前为止，用于应对这种场景的技术还无法同时管理所有上述苛刻要求。然而，诸如雾计算（将云计算扩展到网络边缘）等最新范式使低延迟和位置感知的物联网应用成为可能。此外，低功耗广域网（LPWAN）等技术已成为一种有前途的解决方案，可为分布在广大区域的节点提供低成本和低功耗的连接。具体而言，远距离广域网（LoRaWAN）标准是最新的发展之一，受到了业界和学术界的关注。在本文中，提出了一种基于LoRaWAN雾计算的架构，用于为部署在西班牙拉科鲁尼亚大学（UDC）校园中的物联网节点提供连接。为了验证所提出的系统，通过内部开发的3D射线发射无线电规划模拟器逼真地重建了智能校园，该模拟器甚至能够考虑到诸如交通信号灯、车辆、人员、建筑物、城市设施或植被等小细节。所开发的工具可以在智能校园场景中就网络的覆盖范围、容量和能源效率提供准确的无线电传播估计。然后，可以将规划模拟器获得的结果与经验测量结果进行比较，以评估运行条件和系统准确性。具体而言，本文介绍的实验表明，规划模拟器在为其构建的最大场景（一个面积为26,000平方米的校园）中获得了准确的结果，这些结果得到了经验测量的证实。然后，解释了如何使用该工具为三种智能校园户外应用设计LoRaWAN基础设施的部署：移动模式检测系统、智能灌溉解决方案和智能交通监控部署。因此，所呈现的结果为智能校园设计师和开发者提供了指导方针，并有助于在其他智能校园和诸如智能城市等大型环境中进行LoRaWAN网络部署和研究。
