Digital Twins serve as virtual counterparts, replicating the characteristics and functionalities of tangible objects, processes, or systems within the digital space, leveraging their capability to simulate and forecast real-world behavior. They have found valuable applications in smart farming, facilitating a comprehensive virtual replica of a farm that encompasses vital aspects such as crop cultivation, soil composition, and prevailing weather conditions. By amalgamating data from diverse sources, including soil, plants condition, environmental sensor networks, meteorological predictions, and high-resolution UAV and Satellite imagery, farmers gain access to dynamic and up-to-date visualization of their agricultural domains empowering them to make well-informed and timely choices concerning critical aspects like efficient irrigation plans, optimal fertilization methods, and effective pest management strategies, enhancing overall farm productivity and sustainability. This research paper aims to present a comprehensive overview of the contemporary state of research on digital twins in smart farming, including crop modelling, precision agriculture, and associated technologies, while exploring their potential applications and their impact on agricultural practices, addressing the challenges and limitations such as data privacy concerns, the need for high-quality data for accurate simulations and predictions, and the complexity of integrating multiple data sources. Lastly, the paper explores the prospects of digital twins in agriculture, highlighting potential avenues for future research and advancement in this domain.

This paper presents a new hybrid approach that is suitable for application to energy smart meter gateways, based on combining both blockchain and Secure Element (SE) technologies serving the roles of a secure distributed data storage system and an essential component for building a “root of trust” in IoT platforms simultaneously. Blockchain technology alone may not completely secure a transaction because it only guarantees data immutability, while in most cases, the data has to be also secured at the point of generation. The proposed combinational approach aims to build a robust root of trust by introducing the SE, which will provide IoT devices with trusted computed resources. The feasibility of the proposed method is validated by testing three different implementation scenarios, using different Secure Element systems (SES) combined with blockchain and LPWAN communication technologies to encrypt, transmit, and save data. This hybrid approach aids in overcoming the obstructions of using any one technology alone, and its use is demonstrated with a case study for an Energy Smart Metering gateway that enables the implementation of a local Peer to Peer energy trading scheme that is end-to-end secure and decentralized.

Global Navigation Satellite Systems (GNSS) underpin maritime Positioning, Navigation, and Timing (PNT), supporting bridge functions such as the Automatic Identification System (AIS), the Electronic Chart Display and Information System (ECDIS), radar overlays, and track-control systems. This dependence exposes vessels to non-malicious degradation, unintentional interference, jamming, spoofing, and replay-based (meaconing-type) deception. Using a structured scoping review with narrative synthesis, this paper synthesises evidence on maritime GNSS threats and resilience across the receiver-to-bridge chain. The review develops a maritime-oriented taxonomy and maps disruption across the radio-frequency (RF) front-end, acquisition and tracking, navigation-estimation, and integrated-bridge layers. It examines suppression-oriented resilience, including front-end mitigation, spatial anti-jamming, and multi-sensor fusion, alongside deception-oriented detection, integrity monitoring, and authentication, including correlator-domain monitoring, navigation-engine integrity monitoring, Galileo Open Service Navigation Message Authentication (OSNMA), and bridge-level cross-checks. The analytical novelty lies in integrating disruption mechanism, security objective, evidence type, layer of action, and residual protection gap within a maritime cross-layer decision framework spanning the receiver-to-bridge chain. This framework enables resilience measures to be interpreted and compared according to what they protect and what remains unprotected, supporting complementary rather than interchangeable defences. The synthesis shows that maritime GNSS resilience extends beyond the RF receiver to navigation-solution trust and integrated-bridge safety.