Climate change is driving new solutions to manage water more efficiently. Such solutions involve the development of smart irrigation systems where Internet of Things (IoT) nodes are deployed throughout large areas. In addition, in the mentioned areas, wireless communications can be difficult due to the presence of obstacles and metallic objects that block electromagnetic wave propagation totally or partially. This article details the development of a smart irrigation system able to cover large urban areas thanks to the use of Low-Power Wide-Area Network (LPWAN) sensor nodes based on LoRa and LoRaWAN. IoT nodes collect soil temperature/moisture and air temperature data, and control water supply autonomously, either by making use of fog computing gateways or by relying on remote commands sent from a cloud. Since the selection of IoT node and gateway locations is essential to have good connectivity and to reduce energy consumption, this article uses an in-house 3D-ray launching radio-planning tool to determine the best locations in real scenarios. Specifically, this paper provides details on the modeling of a university campus, which includes elements like buildings, roads, green areas, or vehicles. In such a scenario, simulations and empirical measurements were performed for two different testbeds: a LoRaWAN testbed that operates at 868 MHz and a testbed based on LoRa with 433 MHz transceivers. All the measurements agree with the simulation results, showing the impact of shadowing effects and material features (e.g., permittivity, conductivity) in the electromagnetic propagation of near-ground and underground LoRaWAN communications. Higher RF power levels are observed for 433 MHz due to the higher transmitted power level and the lower radio propagation losses, and even in the worst gateway location, the received power level is higher than the sensitivity threshold (−148 dBm). Regarding water consumption, the provided estimations indicate that the proposed smart irrigation system is able to reduce roughly 23% of the amount of used water just by considering weather forecasts. The obtained results provide useful guidelines for future smart irrigation developers and show the radio planning tool accuracy, which allows for optimizing the sensor network topology and the overall performance of the network in terms of coverage, cost, and energy consumption.

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.

Navantia, one of largest European shipbuilders, is creating a fog computing based Industrial Cyber-Physical System (ICPS) for monitoring in real-time its pipe workshops in order to track pipes and keep their traceability. The deployment of the ICPS is a unique industrial challenge in terms of communications, since in a pipe workshop there is a significant number of metallic objects with heterogeneous typologies. There are multiple technologies that can be used to track pipes, but this article focuses on Bluetooth 5, which is a relatively new technology that represents a cost-effective solution to cope with harsh environments, since it has been significantly enhanced in terms of low power consumption, range, speed and broadcasting capacity. Thus, it is proposed a Bluetooth 5 fog computing based ICPS architecture that is designed to support physically-distributed and low-latency Industry 4.0 applications that off-load network traffic and computational resources from the cloud. In order to validate the proposed ICPS design, one of the Navantia’s pipe workshops was modeled through an in-house developed 3D-ray launching radio planning simulator that allows for estimating the coverage provided by the deployed Bluetooth 5 fog computing nodes and Bluetooth 5 tags. The experiments described in this article show that the radio propagation results obtained by the simulation tool are really close to the ones obtained through empirical measurements. As a consequence, the simulation tool is able to reduce ICPS design and deployment time and provide guidelines to future developers when deploying Bluetooth 5 fog computing nodes and tags in complex industrial scenarios.

In some parts of the world, climate change has led to periods of drought that require managing efficiently the scarce water and energy resources. This paper proposes an IoT smart irrigation system specifically designed for urban areas where remote IoT devices have no direct access to the Internet or to the electrical grid, and where wireless communications are difficult due to the existence of long distances and multiple obstacles. To tackle such issues, this paper proposes a LoRaWAN-based architecture that provides long distance and communications with reduced power consumption. Specifically, the proposed system consists of IoT nodes that collect sensor data and send them to local fog computing nodes or to a remote cloud, which determine an irrigation schedule that considers factors such as the weather forecast or the moist detected by nearby nodes. It is essential to deploy the IoT nodes in locations within the provided coverage range and that guarantee good speed rates and reduced energy consumption. Due to this reason, this paper describes the use of an in-house 3D-ray launching radio-planning tool to determine the best locations for IoT nodes on a real medium-scale scenario (a university campus) that was modeled with precision, including obstacles such as buildings, vegetation, or vehicles. The obtained simulation results were compared with empirical measurements to assess the operating conditions and the radio planning tool accuracy. Thus, it is possible to optimize the wireless network topology and the overall performance of the network in terms of coverage, cost, and energy consumption.

New services and applications within vehicular environments employ multiple wireless communication systems, within a Heterogeneous Network framework. In this context, evaluation of electromagnetic field impact is compulsory, in order to warrant compliance with current exposure limits. In this work, E-field strength distribution within urban transportation buses is studied, in which different types of buses as well as network configurations are considered. E-field estimations are obtained within the complete interior volume of the urban buses, considering all of the characteristics in terms of bus structure and materials employed, by means of an in-house developed deterministic 3D Ray-Launching (3D-RL) code. In this way, relevant phenomena in terms of electromagnetic propagation and interaction are considered, such as multipath propagation and shadowing, which determine exposure levels as a function of transceiver location within the bus scenarios. The behavior in terms of E-field distribution of wireless Public Land Mobile communication systems within transportation buses have been analyzed by means of measurement campaigns employing personal exposimeter devices. In addition, E-field volumetric distributions by means of 3D-RL simulations have been obtained as a function of user distribution within the buses, with the aim of analyzing the impact of user presence within complex intra-vehicular indoor scenarios such as urban transportation buses. A comparison with current exposure limits given by currently adopted standards is obtained, showing that E-field levels were below the aforementioned limits. The use of deterministic simulation techniques based on 3D-RL enables E-field exposure analysis in complex indoor scenarios, offering an optimized balance between accuracy and computational cost. These results and the proposed simulation methodology, can aid in an adequate assessment of human exposure to non-ionizing radiofrequency fields in public transportation buses, considering the impact of the morphology and the topology of vehicles, for current as well as for future wireless technologies and exposure limits.

Surpassing 100 Gbps data throughput is a key objective and an active area of research for sixth-generation (6G) wireless networks that can only be met by exploiting the TeraHertz (THz) frequency band (0.3 - 10 THz). THz channel modeling faces new challenges given the emerging relevance of scattering and molecular absorption in this frequency range as well as the lack of a reliable library of material properties. In this work, we address these challenges by measuring systematically the dielectric properties of 27 common building and office materials and reporting an in-house three-dimensional ray-launching (3D-RL) algorithm that uses the created material library and accounts for rough surface scattering and atmospheric attenuation. In order to validate the proposed algorithm, a channel sounder measurement campaign has been performed in a typical indoor environment at 300 GHz. Simulations and measurements show good agreement, demonstrating the need for modelling scattering and atmospheric absorption in the THz band. The proposed channel model approach enables scenarios at THz frequencies to be investigated by simulation, providing a relevant knowledge for the development of ultra-high-speed wireless communication systems.