Recently, there has been growing attention to the power grid management due to the increasing concerns on global warming. With the advancement in electric vehicles (EV) industry and the evolution in batteries, EVs become an important contributor to the grid with capability of bidirectional power exchange with the grid. In this context, Vehicle-to-Grid (V2G) systems enable multiple functionalities between EVs and the corresponding aggregator. Thus, reliable, long-range communication capabilities between aggregator and EVs is compulsory. In this paper, wireless channel analysis for aggregator and electrical vehicle communication using Long-Range Wide Area Network (LoRaWAN) technology in V2G is presented, in order to test a low-cost solution with large coverage and reduced power consumption profile. Wireless channel and system-level measurements have been performed in a real urban scenario between EV’s charging station in Pamplona (Spain) and a vehicle in motion using LoRaWAN 868 MHz devices. Wireless channel characterization is performed by implementing a full 3D urban scenario model, including elements such as buildings, vehicles, users and urban infrastructure such as lamp posts and benches. By means of in-house developed 3D Ray Launching algorithm with hybrid simulation capabilities, estimations of received power levels, signal to noise ratio and time domain parameters have been obtained, for the complete volume of the scenario under test in dense urban conditions. V2G end to end communication has been validated by implementing an intra-vehicle Controller Area Network-BUS (CAN BUS) data gathering system connected to the vehicle LoRaWAN transceiver and subsequently, to a cloud-based web service. The results show that the accurate deterministic based radio channel analysis enables to optimize the network design of LoRaWAN networks in a vehicular environment, considering inter-vehicular and infrastructure links, enabling scalable, low cost end to end data exchange for the deployment of ancillary V2G services.

In the last decades, the cities' capacity for generating digital information has grown exponentially. In this context, the successful implementation of smart cities' concept depends on the current possibility of handling the significant volumes of sensed data. This is particularly notorious in the case of urban mobility. Researchers in the field of urban planning have shown a great interest in urban mobility problems, proposing different route recommendation services towards making it easier and safer to move around the city. This paper addresses the development of an urban data platform and how to obtain and integrate information from sensors and other data sources to provide aggregated and intelligent views of raw data to support urban mobility. With the aim of evaluating the efficiency of the developed platform, we present an intelligent urban mobility solution, where the context-awareness, user preferences, and environmental factors play a significant role in the process of route planning. Finally, our work provides an experiment to assess different long-range wireless communication technologies to enable its implementation within an urban environment.

The significant growth of wireless communications systems in the last years has led to the adoption of a wide range of applications not only for the general public but, also, including utilities and administrative authorities. In this context, the notable expansion of new services for smart cities requires, in some specific cases, the construction of underground tunnels in order to enable the maintenance and operation works of utilities, as well as to reduce the visual impact within the city center. One of the main challenges is that, inherently, underground service tunnels lack coverage from exterior wireless communication systems, which can be potentially dangerous for maintenance personnel working within the tunnels. Accordingly, wireless coverage should be deployed within the underground installation in order to guarantee real-time connectivity for safety maintenance, remote surveillance or monitoring operations. In this work, wireless channel characterization for complex urban tunnel environments was analyzed based on the assessment of LoRaWAN and ZigBee technologies operating at 868 MHz. For that purpose, a real urban utility tunnel was modeled and simulated by means of an in-house three-dimensional ray-launching (3D-RL) code. The utility tunnel scenario is a complex and singular environment in terms of radio wave propagation due to the limited dimensions and metallic elements within it, such as service trays, user pathways or handrails, which were considered in the simulations. The simulated 3D-RL algorithm was calibrated and verified with experimental measurements, after which, the simulation and measurement results showed good agreement. Besides, a complete wireless sensor network (WSN) deployment within the tunnels was presented, providing remote cloud data access applications and services, allowing infrastructure security and safety work conditions. The obtained results provided an adequate radio planning approach for the deployment of wireless systems in complex urban utility scenarios, with optimal coverage and enhanced quality of service.

Increasing competitiveness as well as levels of sustainability are some of the main challenges that the packaging sector is facing. The introduction of information and communication technologies provides new functionalities, such as traceability within logistic processes. In this context, RFID technologies can play a key role but can also pose hurdles, owing to increased cost, as well as to difficulties in relation with recycling and complying with product circularity. In this sense chipless RFID opens new possibilities, by avoiding the use of information coded chips, reducing costs in material and placement, as well by improving recyclability. In this work, a frequency based chipless RFID solution is presented, in which 2D geometrical patterns printed with conductive ink, resembling transmitive or reflective metasurfaces, are designed and integrated within paper-based substrates. An in-house reader system is implemented based on conventional Software Defined Radio platforms in the 0-6GHz and in the 0-12GHz range, in which received signal post-processing is performed to increase reader sensitivity, without the need of using Vector Network Analyzer equipment. Moreover, in order to reduce material waste, an automatic fault detection system based on artificial vision coupled to a robot arm is designed and tested. Different prototypes in paper substrates as well as in reference printed circuit boards have been fabricated and measured, showing good agreement. The proposed solution provides a feasible chipless RFID system with a portable low-cost reader which can be embedded in paper/cardboard materials in packaging applications.

In this paper we consider the D2D (Device-to-Device) communication taking place between Wireless Sensor Networks (WSN) elements operating in vegetation environments in order to achieve the radio channel characterization at 2.4 GHz, focusing on the radio links blocked by oak and pine trees modelled from specimens found in a real recreation area located within forest environments. In order to fit and validate a radio channel model for this type of scenarios, both measurements and simulations by means of an in-house developed 3D Ray Launching algorithm have been performed, offering as outcomes the path loss and multipath information of the scenarios under study for forest immersed isolated trees and non-isolated trees. The specific forests, composed of thick in-leaf trees, are called Orgi Forest and Chandebrito, located respectively in Navarre and Galicia, Spain. A geometrical and dielectric model of the trees were created and introduced in the simulation software. We concluded that the scattering produced by the tree can be divided into two zones with different dominant propagation mechanisms: an obstructed line of sight (OLoS) zone far from the tree fitting a log-distance model, and a diffraction zone around the edge of the tree. 2D planes of delay spread value are also presented which similarly reflects the proposed two-zone model.

Patients admitted to Intensive Care Units (ICU) are transported from and to other units. Knowing their location is strategic for a sound planning of intra-hospital transports as well as resources management. This is even more crucial in big hospital complexes, comprised of several buildings often connected through tunnels. In this work, a patient tracking application in a multi-building, tunnel-connected hospital complex (the Hospital Complex of Navarre) is presented. The system leverages Internet of Medical Things (IoMT) communication technologies, such as Long Range Wide-Area Network (LoRaWAN) and Near Field Communication (NFC). The locations of the LoRaWAN nodes were selected based on several factors, including the situation of the tunnels, buildings services and medical equipment and a literature review on intra-hospital ICU patients' trips. The possible locations of the LoRaWAN gateways were selected based on 3D Ray Launching Simulations, in order to obtain accurate characterization. Once the locations were set, a LoRaWAN radio coverage studio was performed. The main conclusion drawn is that just one LoRaWAN gateway would be enough to cover all overground LoRaWAN nodes deployed. A second one would be required for underground coverage. In addition, a remote, private cloud infrastructure together with a mobile application was created to manage the information generated. On-field tests were performed to assess the technical feasibility of the system. The application provides with on-demand ICU patients' movement flow around the complex. Although designed for the ICU-admitted patients' context, the system could be easily extrapolated to other use cases.