The decarbonization of cities is a priority for the European Union (EU). Fossil fuel and gas supplies need to be replaced with local renewable energy sources with a relevant increase in efficiency within 20 years in order to cap environmental, social, and economic negative impacts, and this cannot do significant harm. In this context, smart city development frameworks focused on mitigation, adaptation, and measurement not only collaborate in providing governance for sustainability but also facilitate the materialization of such sustainability along lifecycle engineering processes for decarbonization solutions. To achieve these goals, we must face the interoperability challenge and make information accessible for engineering and sustainability governance systematically. A starting point is to validate the models, data, and harmonized metadata. In this paper, the authors provide results that validate the utility of a conceptual model for interoperable smart and sustainable urban energy systems (ISSUESs). The validation is carried out for an urban energy system with a high potential for decarbonizing southern European smart cities and integrating several commercial solar technologies using academic bibliography and natural language processing (NLP) techniques.

Agriculture and silviculture offer interesting opportunities for food, energy, and construction sectors, but to transform such raw materials into valuable products, multiple engineering works must be carried out within R&D, innovation projects, and programs. The classical official decision to promote or supervise such projects involves many agents and criteria but rarely considers engineering quality, reusability, or other valuable and measurable attributes considered in ISO 25.000 or in value engineering guidelines. Missing them would increase technological, business, and programmatic risks, potentially wasting public money or credibility. Large projects are not free from these risks, and it is not a kind of madness to derive R&D and innovation funds to enable access to such valuable knowledge comprehensively, with models. In this context, communications and services, construction, and renewables play a crucial role in smart rural environments. Model-Based Systems Engineering (MBSE) and generative Artificial Intelligence (AI), combined with Natural Language Processing (NLP), are expected to help Knowledge Management (KM) in engineering and governance to supervise value engineering and their relationship with other metrics. Starting with a motivational and multidisciplinary framework for a smart rural transformation for System of Systems (SoS), the authors conduct specific bibliographic research on MBSE-NLP-AI use for automatizing systems engineering supervision at program governance levels.

Urban planners are involved in designing future urban energy systems as a part of their path toward decarbonization or Net Zero targets before 2050. In this process, new energy and information flows between industrial and urban regions should be considered, as well as safety and security managerial aspects regarding the existing and new infrastructures. This research aims to help engineering professionals and public planners define new collaboration dynamics to make industrial energy systems safer, more secure, and interoperable, surpassing the existing knowledge. Firstly, several recent R&D aspects are analyzed, demonstrating the organizational gap and providing early integration or knowledge reuse opportunities from R&D projects. After that, the authors present a model called Industrial-Interoperable Safe and Secure Urban Energy Systems (i-ISSUES), a multi-disciplinary approach combining classic urban energy planning, information technology use, safety and security management, and systems engineering as the integrated disciplines. The model detects research trends, providing a first set of readings with some improvements.

Smart cities will be smart if they improve their citizens’ quality of life; to do so, it is essential to listen to citizens and collaborate with service and technological companies. For that, digitalization seems essential. Environmental management systems are complex and expensive. If their lifecycle costs are reduced, these systems would be more sustainable. This can be achieved through citizen collaboration (CS), the use of low-cost Internet of Things (IoT) devices, and collaboration with local renewable energy businesses. All this leads to a real interoperability challenge. Systems engineering offers a valid framework for managing information and knowledge for environmental systems. It offers a range of guides for processes that can improve the quality of the related information and the reusability of knowledge throughout the lifecycles of these systems. After quantifying the opportunity and the cost for a motivational case of atmospheric neighborhood odor impact and introducing trends and opportunities in energy management, the authors propose a model for renewable energy-linked interoperable smart and sustainable urban environmental systems (re-ISSUES). The model’s ontology is used to discover research trends and potential for improvements to the model itself, enabling semantic interoperability and knowledge reuse.

Spain has one of Europe’s most extraordinary biodiverse environments and a significant risk of fires in its forests. At the same time, rural areas are affected by several challenges, such as desertification, population decrease, and loss of income. Fortunately, some green sparks arise on the horizon. Among them, we use critical enabling technologies for fire prevention and extinction, renewable energy, and resilience solutions by adopting a system of systems approach given by the systems engineering frameworks. We analyse recent Research and Development (R&D) projects focused on fire prevention to detect (1) the key enabling technologies used and (2) engineering practices. A motivational case is presented, which evaluates the potential interest of the mineral water industry sector in applied R&D with key enabling technologies, including the replicability potential and the replicability potential for using the R&D results. After that, the authors initialize an innovative R-ISSUES model to promote early interoperability between energy and environment systems engineering towards the shared mission of designing digital and rural jobs to preserve our biosphere. The model is used to answer specific research questions and detect gaps or potential improvements for the model itself by using the recent scientific literature.

The public purchase of innovation (PPI) is a type of public purchase that can contribute to sustainability in a significant way. Purchasing solar-powered energy systems can be a social innovation, bringing several opportunities for improving health, encouraging local entrepreneurship, building resilience, and promoting sustainable development. In the purchase decision of innovation, a public purchaser evaluates alternatives based on economic figures and specific risk management actions to obtain those figures. In this work, the authors introduce a motivational public purchase decision case. After that, the authors propose a conceptual model called Public Purchase of Innovation for Sustainable Solar Urban Energy Systems (2p-ISSUES) to allocate risks and opportunities. The model is then used to search for information in several scientific and technical research works about public purchase both, non-solar and solar-based distributed energy systems, promoting interoperability between the research community and public agencies. Potential improvements are given and discussed for future versions of the model, also demonstrating potential knowledge gaps in PPI processes and the importance of conducting systematic research using ontological models and tools.