Luckily, new communication technologies and protocols are nowadays designed considering security issues. A clear example of this can be found in the Internet of Things (IoT) field, a quite recent area where communication technologies such as ZigBee or IPv6 over Low power Wireless Personal Area Networks (6LoWPAN) already include security features to guarantee authentication, confidentiality and integrity. More recent technologies are Low-Power Wide-Area Networks (LP-WAN), which also consider security, but present initial approaches that can be further improved. An example of this can be found in Long Range (LoRa) and its layer-two supporter LoRa Wide Area Network (LoRaWAN), which include a security scheme based on pre-shared cryptographic material lacking flexibility when a key update is necessary. Because of this, in this work, we evaluate the security vulnerabilities of LoRaWAN in the area of key management and propose different alternative schemes. Concretely, the application of an approach based on the recently specified Ephemeral Diffie–Hellman Over COSE (EDHOC) is found as a convenient solution, given its flexibility in the update of session keys, its low computational cost and the limited message exchanges needed. A comparative conceptual analysis considering the overhead of different security schemes for LoRaWAN is carried out in order to evaluate their benefits in the challenging area of LP-WAN.

The arrival of the Internet of Things (IoT) paradigm has opened the door to a variety of services for building users. Considering the long-lasting issue of high energy use by buildings and low-energy literacy, it is tempting to use this new technology for increasing the literacy of users. This paper shows the results of a study performed in two pilot buildings with real users that have interacted with a series of energy educational interventions that encourage them in a timed and personalised way to reduce their energy consumption. The interventions aimed at reducing the consumption of energy and a close follow-up of the intervention from a behavioural aspect has been performed. The results show that the users, when interacting with the intervention and staying active, can reduce the energy consumption in the building by more than 30%, but the average savings are of 20%. This is in consensus with the literature, but in our case, the intervention has been one showing that personalised methods can result in energy reductions as large as those of more standard interventions.

Virtualization technologies are key enablers of softwarized 5G networks, and their usage in the vehicular domain can provide flexibility and reliability in real deployments, where mobility and processing needs may be an issue. Next-generation vehicular services, such as the ones in the area of urban mobility and, in general, those interconnecting on-board sensors, require continuous data gathering and processing, but current architectures are stratified in two-tier solutions in which data is collected by on-board units (OBU) and sent to cloud servers. In this line, intermediate cache and processing layers are needed in order to cover quasi-ubiquitous data-gathering needs of vehicles in scenarios of smart cities/roads considering vehicles as moving sensors. The SURROGATES solution presented in this paper proposes to virtualize vehicle OBUs and create a novel Multi-Access Edge Computing (MEC) layer with the aim of offloading processing from the vehicle and serving data-access requests. This deals with potential disconnection periods of vehicles, saves radio resources when accessing the physical OBU and improves data processing performance. A proof of concept has been implemented using OpenStack and Open Source MANO to virtualize resources and gather data from in-vehicle sensors, and a final traffic monitoring service has been implemented to validate the proposal. Performance results reveal a speedup of more than 50% in the data request resolution, with consequently great savings of network resources in the wireless segment. Thus, this work opens a novel path regarding the virtualization of end-devices in the Intelligent Transportation Systems (ITS) ecosystem.

A common practice is applying security after a network has been designed or developed. We have the opportunity of not committing this error in vehicular networks. Apart from particular works in the literature, ETSI TC ITS has defined general security services for (vehicular) cooperative systems. However, existent efforts do not pay the needed attention to the integration of IPv6 yet. The potential of IPv6 in the field is being described within ISO TC 204, above all, but further work is needed for a proper integration of security. This work follows this direction, and a reference vehicular communication architecture considering ETSI/ISO regulations, uses Internet Protocol security (IPsec) and Internet Key Exchange version 2 (IKEv2) to secure IPv6 Network Mobility (NEMO). A key advance is also the implementation and experimental evaluation of the proposal in a challenging vertical handover scenario between 3G and 802.11p. The performance of the secured NEMO channel is widely analyzed in terms of the movement speed, bandwidth, traffic type or signal quality, and it is concluded that the addition of IPv6 security only implies a slight reduction in the overall performance, with the great advantage of providing confidentiality, integrity and authenticity to the communication path.

While satellite or cellular positioning implies dedicated hardware or network infrastructure functions, indoor navigation or novel IoT positioning techniques include flexible storage and computation requirements that can be fulfilled by both end‐devices or cloud back‐ends. Hybrid positioning systems support the integration of several algorithms and technologies; however, the common trend of delegating position calculation and storage of local geoinformation to mobile devices or centralized servers causes performance degradation in terms of delay, battery usage, and waste of network resources. The strategy followed in this work is offloading this computation effort onto the network edge, following a Mobile Edge Computing (MEC) approach. MEC nodes in the access network of the mobile device are in charge of receiving navigation data coming from both the smart infrastructure and mobile devices, in order to compute the final position following a hybrid approach. With the aim of supporting mobility and the access to multiple networks, an Information Centric Networking (ICN) solution is used to access generic position information resources. The presented system currently supports WiFi, Bluetooth LE, GPS, cellular and NFC technologies, involving both indoor and outdoor positioning, using fingerprinting and proximity for indoor navigation, and the integration of smart infrastructure data sources such as the door opening system within real smart campus deployment. Evaluations carried out reveal latency improvements of 50%, as compared with a regular configuration where position fixes are computed by mobile devices; at the same time the MEC solution offers extra flexibility features to manage positioning databases and algorithms and move extensive computation from constrained devices to the edge.

Positioning capabilities have become essential in context-aware user services, which make easier daily activities and let the emergence of new business models in the trendy area of smart cities. Thanks to wireless connection capabilities of smart mobile devices and the proliferation of wireless attachment points in buildings, several positioning systems have appeared in the last years to provide indoor positioning and complement GPS for outdoors. Wi-Fi fingerprinting is one of the most remarkable approaches, although ongoing smart deployments in the area of smart cities can offer extra possibilities to exploit hybrid schemes, in which the final location takes into account different positioning sources. In this paper we propose a positioning system that leverages common infrastructure and services already present in smart spaces to enhance indoor positioning. Thus, GPS and WiFi are complemented with access control services (i.e., ID card) or Bluetooth Low Energy beaconing, to determine the user location within a smart space. Better position estimations can be calculated by hybridizing the positioning information coming from different technologies, and a handover mechanism between technologies or algorithms is used exploiting semantic information saved in fingerprints. The solution implemented is highly optimized by reducing tedious computation, by means of opportunistic selection of fingerprints and floor change detection, and a battery saving subsystem reduces power consumption by disabling non-needed technologies. The proposal has been showcased over a smart campus deployment to check its real operation and assess the positioning accuracy, experiencing the noticeable advantage of integrating technologies usually available in smart spaces and reaching an average real error of 4.62 m.