Throughout human history, agriculture has undergone a series of progressive transformations based on ever-evolving technologies in an effort to increase productivity and profitability. Over the years, farming methods have evolved significantly, progressing from Agriculture 1.0, which relied on primitive tools, to Agriculture 2.0, which incorporated machinery and advanced farming practices, and subsequently to Agriculture 3.0, which emphasized mechanization and employed intelligent machinery and technology to enhance productivity levels. To further automate and increase agricultural productivity while minimizing agricultural inputs and pollutants, a new approach to agricultural management based on the concepts of the fourth industrial revolution is being embraced gradually. This approach is referred to as “Agriculture 4.0” and is mainly implemented through the use of Internet of Things (IoT) technologies, enabling the remote control of sensors and actuators and the efficient collection and transfer of data. In addition, fueled by technologies such as robotics, artificial intelligence, quantum sensing, and four-dimensional communication, a new form of smart agriculture, called “Agriculture 5.0,” is now emerging. Agriculture 5.0 can exploit the growing 5G network infrastructure as a basis. However, only 6G-IoT networks will be able to offer the technological advances that will allow the full expansion of Agriculture 5.0, as can be inferred from the relevant scientific literature and research. In this article, we first introduce the scope of Agriculture 5.0 as well as the key features and technologies that will be leveraged in the much-anticipated 6G-IoT communication systems. We then highlight the importance and influence of these developing technologies in the further advancement of smart agriculture and conclude with a discussion of future challenges and opportunities.

The Internet of Things (IoT) is gaining popularity and market share, driven by its ability to connect devices and systems that were previously siloed, enabling new applications and services in a cost-efficient manner. Thus, the IoT fuels societal transformation and enables groundbreaking innovations like autonomous transport, robotic assistance, and remote healthcare solutions. However, when considering the Internet of Remote Things (IoRT), which refers to the expansion of IoT in remote and geographically isolated areas where neither terrestrial nor cellular networks are available, internet connectivity becomes a challenging issue. Non-Terrestrial Networks (NTNs) are increasingly gaining popularity as a solution to provide connectivity in remote areas due to the growing integration of satellites and Unmanned Aerial Vehicles (UAVs) with cellular networks. In this survey, we provide the technological framework for NTNs and Remote IoT, followed by a classification of the most recent scientific research on NTN-based IoRT systems. Therefore, we provide a comprehensive overview of the current state of research in IoRT and identify emerging research areas with high potential. In conclusion, we present and discuss 3GPP’s roadmap for NTN standardization, which aims to establish an energy-efficient IoRT environment in the 6G era.

The rapidly increasing number of mobile devices and resource-intensive applications poses substantial obstacles to traditional centralized mobile cloud computing, resulting in increased latency and decreased service quality. Edge computing, which places server capabilities at access nodes, provides a promising solution to the aforementioned issues. However, maintaining operational edge service nodes at each access node can be costly and inefficient. We propose and evaluate a scheme that combines a heuristic service node selection algorithm with machine learning based computational load prediction, with the goal of minimizing latency and balancing load among service nodes. Simulation experiments demonstrate that the proposed scheme substantially enhances system performance, paving the way for a more efficient and responsive edge network infrastructure, particularly in 5G and 6G mobile communication environments.

The Network Exposure Function (NEF) is a key component of the 5G and Beyond 5G (B5G) network, providing standardized access for third-party applications to network data and capabilities. Among these capabilities is the Event Monitoring API, which allows external applications to subscribe to specific network events. One such event is the reporting of user equipment (UE) location changes, enabling services that rely on real-time location awareness. In this context, this paper presents the design and implementation of an open-source, cloud-based NEF Event Monitoring Application Programming Interface (API) that adheres to relevant 3rd Generation Partnership Project (3GPP) standards. The proposed architecture minimizes integration complexity and provides a flexible framework for efficient deployment and utilization of future 6G location services, fostering innovation in intelligent environments and enabling a wide range of third-party applications.

The integration of Non-Terrestrial Networks (NTN) with terrestrial 5G networks (TNs) presents unprecedented opportunities for achieving ubiquitous connectivity, particularly for data-intensive and latency-sensitive applications. However, effectively managing multiple network interfaces across heterogeneous terrestrial and non-terrestrial Radio Access Technologies (RATs) remains challenging. In this paper, a Multi-RAT Dual Connectivity enabler for SUNRISE-6G experimentation platform is proposed, that relies on MultiPath TCP (MPTCP) as a key enabler for ubiquitous connectivity over TN-NTN infrastructure. The approach encompasses two complementary experimental setups: a fully virtualized emulation environment and a hybrid setup combining physical devices with emulated NTN elements. Results demonstrate that while MPTCP successfully enables multi-connectivity across terrestrial and satellite networks, optimal performance requires careful consideration of path characteristics and protocol parameters.