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Today's increasingly complex energy systems require innovative approaches to integrate and optimize different energy sources and technologies. In this paper, we explore the system of systems (SoS) approach, which provides a comprehensive framework for improving energy systems' interoperability, efficiency, and resilience. By examining recent advances in various sectors, including photovoltaic systems, electric vehicles, energy storage, renewable energy, smart cities, and rural communities, this study highlights the essential role of SoSs in addressing the challenges of the energy transition. The principal areas of interest include the integration of advanced control algorithms and machine learning techniques and the development of robust communication networks to manage interactions between interconnected subsystems. This study also identifies significant challenges associated with large-scale SoS implementation, such as real-time data processing, decision-making complexity, and the need for harmonized regulatory frameworks. This study outlines future directions for improving the intelligence and autonomy of energy subsystems, which are essential for achieving a sustainable, resilient, and adaptive energy infrastructure. [ABSTRACT FROM AUTHOR]

The transport of Dangerous Goods (DG) in Italy occurs mainly via road networks as part of supply chain logistics. Although they account for a relatively small proportion of overall freight, accidents involving DG can have significant consequences and are classified as Low Probability High Consequence (LPHC) events. These events, although rare, present considerable risks for both the environment and the public, particularly in the face of the increase in industrial disasters. This paper presents a data-driven analysis aimed at quantifying the rates and frequencies of accidents associated with the transport of DG in the Genoa district. Using a deterministic risk approach, the study identifies the least DG transport routes and assesses risk levels accordingly. The integration of the Internet of Things (IoT) and Information and Communication Technologies (ICT) allows realtime monitoring of the transport of DG, enabling the identification of accident frequencies within defined spatial and temporal parameters. Using ICT tools and the database of National Fire and Rescue Service (NFRS), accidents involving trucks transporting DG are identified and analyzed. The study highlights the importance of rapid and effective emergency response processes to minimize individual damage and mitigate environmental and property damage. This research provides valuable information for risk assessment and emergency response planning in the Genoa district and highlights the importance of taking advantage of data-driven approaches to improve DG transport safety. [ABSTRACT FROM AUTHOR]

Precision agriculture, driven by the convergence of smart sensors and advanced technologies, has emerged as a transformative force in modern farming practices. The present review synthesizes insights from a multitude of research papers, exploring the dynamic landscape of precision agriculture. The main focus is on the integration of smart sensors, coupled with technologies such as the Internet of Things (IoT), big data analytics, and Artificial Intelligence (AI). This analysis is set in the context of optimizing crop management, using resources wisely, and promoting sustainability in the agricultural sector. This review aims to provide an in-depth understanding of emerging trends and key developments in the field of precision agriculture. By highlighting the benefits of integrating smart sensors and innovative technologies, it aspires to enlighten farming practitioners, researchers, and policymakers on best practices, current challenges, and prospects. It aims to foster a transition towards more sustainable, efficient, and intelligent farming practices while encouraging the continued adoption and adaptation of new technologies. [ABSTRACT FROM AUTHOR]

The transportation of dangerous goods by road is the most accident-prone mode of transportation, even if accidents involving road transportation of dangerous goods are considered as a Low Probability and High Consequence event (LPHC event). However, several dangerous goods are transported by road networks, such as petroleum products and chemicals, which can generate major dangerous consequences such as spills, explosions, fires, or toxic clouds. In this context, this article presents a method to calculate and quickly quantify the sizes of impact zones characterized by high lethality and irreversible injuries to people in the case of a hazardous materials transport accident. This method is used as a module for the analysis of the consequences of different potential accident scenarios, for the Web-GIS platform proposed by LOSE+LAB, that implements appropriate ICT tools and systems for monitoring the flow of goods that would enable a continuous monitoring system at the cross-border level and transmit data and information to the territory actors involved in the management of dangerous goods according to the ADR standard. The proposed method provides the user with a visualization of the possible outcomes of an event by reproducing the impact area for different accident scenarios, which can provide quick maps of the hazard and represents a decision support system for territorial governance in terms of intervention and response protocols for emergency management in the cases of dangerous goods accidents. [ABSTRACT FROM AUTHOR]