Recently Unmanned Aerial Vehicles (UAVs) have evolved considerably towards real world applications, going beyond entertaining activities and use. With the advent of Fifth Generation (5G) cellular networks and the number of UAVs to be increased significantly, it is created the opportunity for UAVs to participate in the realisation of 5G opportunistic networks by carrying 5G Base-Stations to under-served areas, allowing the provision of bandwidth demanding services, such as Ultra High Definition (UHD) video streaming, as well as other multimedia services. Among the various improvements that will drive this evolution of UAVs, energy efficiency is considered of primary importance since will prolong the flight time and will extend the mission territory. Although this problem has been studied in the literature as an offline resource optimisation problem, the diverse conditions of a real UAV flight does not allow any of the existing offline optimisation models to be applied in real flight conditions. To this end, this paper discusses the amalgamation of UAVs and 5G cellular networks as an auspicious solution for realising energy efficiency of UAVs by offloading at the edge of the network the Flight Control System (FCS), which will allow the optimisation of the UAV energy resources by processing in real time the flight data that have been collected by onboard sensors. By exploiting the Multi-access Edge Computing (MEC) architectural feature of 5G as a technology enabler for realising this offloading, the paper presents a proof-of-concept implementation of such a 5G-enabled UAV with softwarized FCS component at the edge of the 5G network (i.e., the MEC), allowing by this way the autonomous flight of the UAV over the 5G network by following control commands mandated by the FCS that has been deployed at the MEC. This proof-of-concept 5G-enabled UAV can support the execution of real-time resource optimisation techniques, a step-forward from the currently offline-ones, enabling in the future the execution of energy-efficient and advanced missions.

Modern agriculture is increasingly challenged by the need for scalable, sustainable, and connectivity-resilient digital solutions. While existing smart farming platforms offer valuable insights, they often rely heavily on centralized cloud infrastructure, which can be impractical in rural or remote settings. To address this gap, this paper presents AGRARIAN, a hybrid AI-driven architecture that combines IoT sensor networks, UAV-based monitoring, satellite connectivity, and edge-cloud computing to deliver real-time, adaptive agricultural intelligence. AGRARIAN supports a modular and interoperable architecture structured across four layers—Sensor, Network, Data Processing, and Application—enabling flexible deployment in diverse use cases such as precision irrigation, livestock monitoring, and pest forecasting. A key innovation lies in its localized edge processing and federated AI models, which reduce reliance on continuous cloud access while maintaining analytical performance. Pilot scenarios demonstrate the system’s ability to provide timely, context-aware decision support, enhancing both operational efficiency and digital inclusion for farmers. AGRARIAN offers a robust and scalable pathway for advancing autonomous, sustainable, and connected farming systems.

The definition of multiple slicing types in 5G has created a wide field for service innovation in communications. However, the advantages that network slicing has to offer remain to be fully exploited by today’s applications and users. An important area that can potentially benefit from 5G slicing is emergency communications for First Responders. The latter consists of heterogeneous teams, imposing different requirements on the connectivity network. In this paper, the RESPOND-A platform is presented, which provides First Responders with network-enabled tools on top of 5G on-scene planning, with enhanced service slicing capabilities tailored to emergency communications. Furthermore, a mapping of emergency services and communications to specific slice types is proposed to identify the current challenges in the field. Additionally, the proposed tentative mechanism is evaluated in terms of energy efficiency. Finally, the approach is summarized by discussing future steps in the convergence of 5G network slicing in various areas of emergency vertical applications.

This study delves into the potential of 5G and blockchain technologies in smart agriculture, specifically targeting remote farming sectors. A conceptual architecture is proposed, aiming to leverage these cutting-edge technologies while ensuring energy efficiency and sustainable development within the agriculture industry. We provide an in-depth analysis of 5G applications and explore alternative communication channels that could empower remote communities, introducing them to state-of-the-art technological solutions. A unique aspect of our research is the detailed presentation of a parametric insurance business case, designed to align with the proposed architecture, thereby illustrating the practicality of our approach. Moreover, we propose an innovative solution to the challenge of providing internet connectivity in rural areas using Unmanned Aerial Vehicles (UAVs). Current limitations due to the weight of onboard equipment, which includes an access network and a backhaul link for internet provision, are addressed by introducing a lightweight 5G system onboard the UAV. This system serves multiple user equipment on the ground, with one acting as a connection gateway to the internet. This unique approach not only streamlines the process of providing rural internet connectivity but also opens up new markets for service providers and businesses related to lightweight 5G systems and UAV technology. Our work presents an avant-garde solution to technical challenges and offers significant business opportunities in the rapidly evolving telecommunications sector and beyond.

The integration of Artificial Intelligence (AI), Internet of Things (IoT), edge computing, and satellite-based connectivity is revolutionizing modern agriculture by enabling real-time monitoring, data-driven decision-making, and optimized resource management. The AGRARIAN architecture presents a hybrid AI-driven framework designed to enhance precision farming, livestock management, and sustainable agriculture. The system integrates multispectral sensors, UAVs, remote sensing satellites, and ground-based IoT devices, leveraging 5G and satellite networks for seamless connectivity. Data collected from these sources is processed through edge AI and cloud-based analytics, feeding into an Advanced Decision Support System (ADSS) that provides real-time insights for farmers, policymakers, and researchers. This paper presents the AGRARIAN system architecture, detailing its sensor, network, data processing, and application layers, alongside its horizontal and vertical integration approaches. Comparative analysis with existing digital agriculture frameworks highlights AGRARIAN’s scalability, resilience, and efficiency in supporting smart farming practices. The findings suggest that hybrid AI-driven agricultural systems have the potential to improve crop yield predictions, irrigation efficiency, and disease prevention, offering sustainable and scalable solutions for modern agriculture.

The transformation of food production through digital tools and technologies requires not only advanced devices and processing capabilities, but also a holistic agricultural framework that unifies multiple types of stakeholders across the agri-food chain. This paper introduces the AGRARIAN platform, a stakeholder-centric, self-organizing Cyber-Physical System designed to answer the modern and future demands of sustainable agriculture, unifying farmers, developers and policy makers, all in one dynamic and scalable ecosystem. Integrating hybrid communications, lightweight services orchestration, continuous development and cross-farm decision support, the AGRARIAN platform offers a complete solution for the next generation of farm management. For the platform validation, field trials were performed for the use case of livestock monitoring in a remote area, using commercial communication links (5 G, WiFi and satellite) for real-world system evaluation. The measurements and the results analysis confirmed the capacity of the AGRARIAN platform to support the necessary functions and services, opening the way towards modern and sustainable farming.