A Cost-Efficient 5G Non-Public Network Architectural Approach: Key Concepts and Enablers, Building Blocks and Potential Use Cases.

The provision of high data rate services to mobile users combined with improved quality of experience (i.e., zero latency multimedia content) drives technological evolution towards the design and implementation of fifth generation (5G) broadband wireless networks. To this end, a dynamic network design approach is adopted whereby network topology is configured according to service demands. In parallel, many private companies are interested in developing their own 5G networks, also referred to as non-public networks (NPNs), since this deployment is expected to leverage holistic production monitoring and support critical applications. In this context, this paper introduces a 5G NPN architectural approach, supporting among others various key enabling technologies, such as cell densification, disaggregated RAN with open interfaces, edge computing, and AI/ML-based network optimization. In the same framework, potential applications of our proposed approach in real world scenarios (e.g., support of mission critical services and computer vision analytics for emergencies) are described. Finally, scalability issues are also highlighted since a deployment framework of our architectural design in an additional real-world scenario related to Industry 4.0 (smart manufacturing) is also analyzed.

Towards Autonomous Modular UAV Missions: The Detection, Geo-Location and Landing Paradigm.

Nowadays, various unmanned aerial vehicle (UAV) applications become increasingly demanding since they require real-time, autonomous and intelligent functions. Towards this end, in the present study, a fully autonomous UAV scenario is implemented, including the tasks of area scanning, target recognition, geo-location, monitoring, following and finally landing on a high speed moving platform. The underlying methodology includes AprilTag target identification through Graphics Processing Unit (GPU) parallelized processing, image processing and several optimized locations and approach algorithms employing gimbal movement, Global Navigation Satellite System (GNSS) readings and UAV navigation. For the experimentation, a commercial and a custom made quad-copter prototype were used, portraying a high and a low-computational embedded platform alternative. Among the successful targeting and follow procedures, it is shown that the landing approach can be successfully performed even under high platform speeds.

Cooperative energy harvesting-adaptive MAC protocol for WBANs.

In this paper, we introduce a cooperative medium access control (MAC) protocol, named cooperative energy harvesting (CEH)-MAC, that adapts its operation to the energy harvesting (EH) conditions in wireless body area networks (WBANs). In particular, the proposed protocol exploits the EH information in order to set an idle time that allows the relay nodes to charge their batteries and complete the cooperation phase successfully. Extensive simulations have shown that CEH-MAC significantly improves the network performance in terms of throughput, delay and energy efficiency compared to the cooperative operation of the baseline IEEE 802.15.6 standard.

Smart HVAC control in IoT: energy consumption minimization with user comfort constraints.

Smart grid is one of the main applications of the Internet of Things (IoT) paradigm. Within this context, this paper addresses the efficient energy consumption management of heating, ventilation, and air conditioning (HVAC) systems in smart grids with variable energy price. To that end, first, we propose an energy scheduling method that minimizes the energy consumption cost for a particular time interval, taking into account the energy price and a set of comfort constraints, that is, a range of temperatures according to user's preferences for a given room. Then, we propose an energy scheduler where the user may select to relax the temperature constraints to save more energy. Moreover, thanks to the IoT paradigm, the user may interact remotely with the HVAC control system. In particular, the user may decide remotely the temperature of comfort, while the temperature and energy consumption information is sent through Internet and displayed at the end user's device. The proposed algorithms have been implemented in a real testbed, highlighting the potential gains that can be achieved in terms of both energy and cost.

A cloud-assisted random linear network coding medium access control protocol for healthcare applications.

Relay sensor networks are often employed in end-to-end healthcare applications to facilitate the information flow between patient worn sensors and the medical data center. Medium access control (MAC) protocols, based on random linear network coding (RLNC), are a novel and suitable approach to efficiently handle data dissemination. However, several challenges arise, such as additional delays introduced by the intermediate relay nodes and decoding failures, due to channel errors. In this paper, we tackle these issues by adopting a cloud architecture where the set of relays is connected to a coordinating entity, called cloud manager. We propose a cloud-assisted RLNC-based MAC protocol (CLNC-MAC) and develop a mathematical model for the calculation of the key performance metrics, namely the system throughput, the mean completion time for data delivery and the energy efficiency. We show the importance of central coordination in fully exploiting the gain of RLNC under error-prone channels.

A survey on M2M systems for mHealth: a wireless communications perspective.

In the new era of connectivity, marked by the explosive number of wireless electronic devices and the need for smart and pervasive applications, Machine-to-Machine (M2M) communications are an emerging technology that enables the seamless device interconnection without the need of human interaction. The use of M2M technology can bring to life a wide range of mHealth applications, with considerable benefits for both patients and healthcare providers. Many technological challenges have to be met, however, to ensure the widespread adoption of mHealth solutions in the future. In this context, we aim to provide a comprehensive survey on M2M systems for mHealth applications from a wireless communication perspective. An end-to-end holistic approach is adopted, focusing on different communication aspects of the M2M architecture. Hence, we first provide a systematic review ofWireless Body Area Networks (WBANs), which constitute the enabling technology at the patient's side, and then discuss end-to-end solutions that involve the design and implementation of practical mHealth applications. We close the survey by identifying challenges and open research issues, thus paving the way for future research opportunities.

A comprehensive review of unmanned aerial vehicle-based approaches to support photovoltaic plant diagnosis.

Accurate photovoltaic (PV) diagnosis is of paramount importance for reducing investment risk and increasing the bankability of the PV technology. The application of fault diagnostic solutions and troubleshooting on operating PV power plants is vital for ensuring optimal energy harvesting, increased power generation production and optimised field operation and maintenance (O&M) activities. This study aims to give an overview of the existing approaches for PV plant diagnosis, focusing on unmanned aerial vehicle (UAV)-based approaches, that can support PV plant diagnostics using imaging techniques and data-driven analytics. This review paper initially outlines the different degradation mechanisms, failure modes and patterns that PV systems are subjected and then reports the main diagnostic techniques. Furthermore, the essential equipment and sensor's requirements for diagnosing failures in monitored PV systems using UAV-based approaches are provided. Moreover, the study summarizes the operating conditions and the various failure types that can be detected by such diagnostic approaches. Finally, it provides recommendations and insights on how to develop a fully functional UAV-based diagnostic tool, capable of detecting and classifying accurately failure modes in PV systems, while also locating the exact position of faulty modules.

Smart5Grid Solutions for enhanced TSO grid observability and manageability in massive RES penetration environment.

This article presents the latency minimisation potential provided by the Smart5Grid Open Experimentation Platform (OEP) developed by the Horizon 2020 Smart5Grid Research and Innovation (R&I) project. It discusses the OEP performance and provides experimental data to substantiate its contribution to improving observability and manageability of distributed renewable generation in power grids. That experimental proof is delivered by two pilots running on the OEP: Demo 1 Millisecond Level Precise Distribution Generation Control, and Demo 2 Real-time Wide Area Monitoring (WAM) pilot of 5G virtual Phasor Data Concentrator v(PDC) capabilities for WAM of end-to-end electricity grids. This work reports  two Network Applications (NetApps) created to support both demos and provides experimental evidence that the OEP offers latency of comparable measure to well-established wire-bound communications in addition to availability and reliability on top of by-design flexibility, scalability and modularity, which are especially relevant to power systems with high shares of Distributed Renewable Energy Recourses (DRERs). The software and methods used for the OEP development and experimental testbeds applied to measure its latency performance in both tailored pilot demos are explained at length. The test results are presented and interpreted with a view to discussing potential contributions of the presented 5G-enabled solutions for power grid smartification in conditions of high rollout of distributed renewable generation. All pilot demos generate openly accessible data, except where specific security restrictions are applicable.