The need for high-quality communications networks is urgent in data-based farming. A particular challenge is how to achieve reliable, cost-efficient, secure, and broadband last-mile data transfer to enable agricultural machine control. The trialed ad hoc private communications networks built and interconnected with different alternative wireless technologies, including 4G, 5G, satellite and tactical networks, provide interesting practical solutions for connectivity. A remotely controlled tractor is exemplified as a use case of machine control in the demonstrated private communication network. This paper describes the results of a comparative technology analysis and a field trial in a realistic environment. The study includes the practical implementation of video monitoring and the optimization of the control channel for remote-controlled unmanned agricultural tractors. The findings from this study verify and consolidate the requirements for network technologies and for cybersecurity enablers. They highlight insights into the suitability of different wireless technologies for smart farming and tractor scenarios and identify potential paths for future research.

The European Commission requires all European Union (EU) Member States to use telecommunications networks to alert the population of an ongoing crisis or an upcoming threat by June 2022. Public Warning System in Long Term Evolution (LTE) and 5G System currently supports a text-based warning using Cell Broadcast technology. Cell Broadcast does not support multimedia warning message delivery. This paper analyses requirements that need to be fulfilled to support multimedia warning message delivery in the 5G System and describes trials of a broadcast multimedia public warning alert system. The trials demonstrate delivery of multimedia public warning messages using Evolved Multimedia Broadcast Multicast Service (eMBMS), dynamic spectrum management and bonded connections. By using eMBMS the public warning messages can be sent with additional robustness and in multicast mode, resulting also in less congestion to the network as the messages do not need to be sent separately to each user. Dynamic spectrum management system allows to dynamically obtain spectrum resources for the public warning system messages and the bonded connections improves the throughput and reliability of the delivery by combining the capacity of several different networks.

This article provides a survey and a general methodology for coexistence studies between digital terrestrial television (DTT) and mobile broadband (MBB) systems in the ultra high frequency (UHF) broadcasting band. The methodology includes characterization of relevant field measurement scenarios and gives a step-by-step guideline on how to obtain reliable field measurement results to be used in conjunction with link budget analyses, laboratory measurements, and simulations. A survey of potential European coexistence scenarios and regulatory status is given to determine feasible future use scenarios for the UHF television (TV) broadcasting band. The DTT reception system behavior and performance are also described as they greatly affect the amount of spectrum potentially available for MBB use and determine the relevant coexistence field measurement scenarios. Simulation methods used in determining broadcast protection criteria and in coexistence studies are briefly described to demonstrate how the information obtained from field measurements can be used to improve their accuracy. The presented field measurement guidelines can be applied to any DTT-MBB coexistence scenarios and to a wide range of spectrum sharing and cognitive radio system coexistence measurements.

In response to the global megatrends of digitalization and transportation automation, Turku University of Applied Sciences has developed a test platform to advance autonomous maritime operations. This platform includes the unmanned surface vessel eM/S Salama and a remote operations center, both of which are detailed in this article. The article highlights the importance of collecting and annotating multi-modal sensor data from the vessel. These data are vital for developing deep learning algorithms that enhance situational awareness and guide autonomous navigation. By securing relevant data from maritime environments, we aim to enhance the autonomous features of unmanned surface vessels using deep learning techniques. The annotated sensor data will be made available for further research through open access. An image dataset, which includes synthetically generated weather conditions, is published alongside this article. While existing maritime datasets predominantly rely on RGB cameras, our work underscores the need for multi-modal data to advance autonomous capabilities in maritime applications.

This chapter studies the Licensed Shared Access (LSA) concept, which was initially developed to enable the use of the vacant spectrum resources in 2.3–2.4 GHz band for mobile broadband (MBB) through long-term static licenses. The LSA system was developed to guarantee LSA licensees a predictable quality of service (QoS) and exclusive access to shared spectrum resources. This chapter describes the development and architecture of LSA for 2.3–2.4 GHz band and compares the LSA briefly to the Spectrum Access System (SAS) concept developed in the USA. 5G and its new use cases require a more dynamic approach to access shared spectrum resources than the LSA system developed for 2.3–2.4 GHz band can provide. Thus, a concept called LSA evolution is currently under development. The novel concepts introduced in LSA evolution include spectrum sensing, short-term license periods, possibility to allocate spectrum locally, and support for co-primary sharing, which can guarantee the quality of service (QoS) from spectrum perspective. The chapter also describes a demonstration of LSA evolution system with spectrum user prioritization, which was created for Programme Making and Special Events (PMSE) use case.