Internet of Things (IoT) constitutes the next step in the field of technology, bringing enormous changes in industry, medicine, environmental care, and urban development. Various challenges are to be met in forming this vision, such as technology interoperability issues, security and data confidentiality requirements, and, last but not least, the development of energy efficient management systems. In this paper, we explore existing networking communication technologies for the IoT, with emphasis on encapsulation and routing protocols. The relation between the IoT network protocols and the emerging IoT applications is also examined. A thorough layer‐based protocol taxonomy is provided, while how the network protocols fit and operate for addressing the recent IoT requirements and applications is also illustrated. What is the most special feature of this paper, compared to other survey and tutorial works, is the thorough presentation of the inner schemes and mechanisms of the network protocols subject to IPv6. Compatibility, interoperability, and configuration issues of the existing and the emerging protocols and schemes are discussed based on the recent advanced of IPv6. Moreover, open networking challenges such as security, scalability, mobility, and energy management are presented in relation to their corresponding features. Lastly, the trends of the networking mechanisms in the IoT domain are discussed in detail, highlighting future challenges.

Smart Farming is a development that emphasizes on the use of modern technologies in the cyber-physical field management cycle. Technologies such as the Internet of Things (IoT) and Cloud Computing have accelerated the digital transformation of the conventional agricultural practices promising increased production rate and product quality. The adoption of smart farming though is hampered because of the lack of models providing guidance to practitioners regarding the necessary components that constitute IoT-based monitoring systems. To guide the process of designing and implementing Smart farming monitoring systems, in this paper we propose a generic reference architecture model, taking also into consideration a very important non-functional requirement, the energy consumption restriction. Moreover, we present and discuss the technologies that incorporate the seven layers of the architecture model that are the Sensor Layer, the Link Layer, the Encapsulation Layer, the Middleware Layer, the Configuration Layer, the Management Layer and the Application Layer. Furthermore, the proposed Reference Architecture model is exemplified in a real-world application for surveying Saffron agriculture in Kozani, Greece.

The Electric Smart Grid (ESG) is referred to as the next generation electricity power network. The ESG is an intelligent critical infrastructure subject to various security vulnerabilities and especially data privacy breaches. This study presents a comprehensive overview of the latest privacy-preserving mechanisms and policies in the ESG, while promoting the employment of modern access control techniques towards preventing personal data disclosure, affecting both utility companies and consumers. Efficient categorization is provided regarding the proposed privacy preserving methods and characteristics, while focus is also given on the use of the Blockchain technology and the Multi Authority Access Control paradigm in the ESG infrastructure. The study concludes with a discussion upon privacy and access control challenges, as well as future work concerning the ESG.

This study introduces an innovative, resource-efficient architecture that incorporates advanced technologies to create a lightweight, flexible, and scalable framework for remote and limited data collecting and processing in next-generation Internet of Things (IoT) applications. It specifically proposes an integrated Federated LoRaWAN (LoRA-FL) system that combines hierarchical, privacy-preserving Federated Learning (FL), Knowledge Distillation (KD), and a customised Medium Access Control (MAC) protocol, identified as FCA-LoRa, to address the significant limitations of LoRaWAN networks. These encompass strict duty cycle rules, restricted bandwidth, and energy limitations, elements that conventionally hinder the implementation of intelligent IoT devices in rural or isolated settings. The proposed architecture features a hierarchical FL approach enabling multi-tier Artificial Intelligence (AI) model aggregation across edge nodes, gateways, and a central server. The effectiveness of the proposed system is confirmed by two practical applications, smart agriculture and smart livestock farming, which exemplify standard situations for far-edge intelligence. The results indicate that the distilled model consistently attains over 90% packet delivery success, illustrating the architecture’s capacity to provide scalable and energy-efficient intelligence at the edge. This research addresses a significant gap in previous studies that frequently examine FL, communication optimisation, and model compression independently. This study offers a comprehensive, implementable approach that tackles model scalability, and network-layer issues within a cohesive architecture, enhancing the practical implementation of AI-driven IoT deployments over LoRaWAN.