Modular construction provides numerous benefits over traditional methods, especially when combined with digital technologies, offering a faster, safer, leaner, and more sustainable construction environment. This literature review follows the PRISMA method to assess recent advancements in digital-oriented modular construction towards a sustainable and climate-neutral built environment, identifying research trends and gaps based on three pillars: digital tools, building solutions, and environmental sustainability. This review examines the integration of digital technologies with modular construction methods, extending the analysis to circular and bioclimatic efforts, renewable energy sources, and passive building design strategies. While most articles focus on BIM uses, there is an increasing emphasis on IoT applications that leverage real-time data to achieve sustainability goals. However, no full-scale automated Digital Twin was found in this context. Additionally, Building Energy Modelling (BEM) and Life Cycle Assessment (LCA) tools are frequently discussed, reflecting the push for climate-friendly housing. Despite the interest in parametric and generative design, the integration of machine learning and artificial intelligence applications for sustainable modular construction strategies remains underexplored. Only a few papers acknowledged reaching nZEB requirements despite the great emphasis on passive building solutions and renewable energy sources that contribute to this goal. However, material circularity has yet to achieve its full potential for sustainable modular construction. Moreover, there is some interest in off-grid modular buildings, although further research should be undertaken to analyse the modular construction feasibility for sustainable off-grid communities. Furthermore, the findings highlight the potential of digitalisation in modular construction to enhance efficiency and ensure environmental sustainability within the Architecture, Engineering, and Construction (AEC) sector.

Building information modelling (BIM) is the first step towards implementing Building 4.0, where virtual reality and digital twins are key elements. The use of unmanned aircraft systems (UAS/drones) to capture data from buildings is nowadays a very popular method, so a methodology was developed to digitally integrate the photogrammetric surveys of a building into BIM, exclusively with the use of drones. Currently, buildings are responsible for 40% of energy consumption in Europe; therefore, the interconnection between BIM and building energy modelling (BEM) is essential to digitalize the construction sector, increasing competitiveness through cost reduction. In this context, the BlueWoodenHouse Project aims, among other activities, to characterize the solutions/systems of building materials and monitor the temperature, relative humidity and CO₂, as well as energy consumption, of a single-family modular wooden house located in the north of Portugal, with 190 m² and three users. Thus, the experimental monitoring results, of this case study, were used to validate the numerical model developed in the DesignBuilder simulator, which includes the building envelope’s 3D geometrical data obtained by one of those aircraft, in order to demonstrate the usefulness of drones for the optimization of solutions, from the energy point of view.

Os gémeos digitais são cada vez mais relevantes no setor AECO (Arquitetura, Engenharia, Construção, e Operação), no entanto, a sua terminologia é aplicada de forma inconsistente. Mesmo as classificações mais comuns apresentam ambiguidades, dificultando a distinção entre diferentes níveis de maturidade de geminação digital, contribuindo assim para interpretações divergentes. Para além disso, a fase crítica de calibração de modelos digitais com recurso a dados recolhidos in situ carece de um reconhecimento formal como um grau de maturidade distinto, apesar de ser amplamente aplicada na prática. Este artigo propõe a formalização do "Gémeo de Calibração" (Calibration Twin) como uma tipologia intermédia que utiliza dados provenientes de sistemas de monitorização instalados num ativo físico para ajustar e validar modelos virtuais. Esta fase carateriza-se ainda por um fluxo unidirecional de informação sem capacidade de influenciar o ativo real, posicionando-se conceptualmente entre um modelo digital estático e configurações mais avançadas de geminação digital. Ao reconhecer esta etapa como um nível de maturidade distinto, destaca-se o papel fulcral da calibração no desenvolvimento de gémeos digitais, reforçando ainda a precisão terminológica necessária para evitar ambiguidades recorrentes. A proposta contribui também para uma taxonomia mais coerente e com potencial de aplicação transversal a outros setores de atividade.

Open-source methodologies promote broader access to knowledge, tools, and technological development by supporting reproducible and community-driven advancements. By integrating digital surveying into these workflows, it is possible to reduce the existing dependency of the construction field on proprietary software solutions. For this purpose, this study aims to develop an open-source Scan-to-BIM approach, based on multi-sensor surveying. Scan-to-BIM refers to the process of using captured spatial data to create accurate as-built/as-is BIM models, facilitating tasks such as renovation and maintenance throughout the infrastructure lifecycle. This study employs the open-source software Blender, paired with the Bonsai add-on, as the central platform for compiling data gathered from aerial and handheld surveys conducted at FEUP. The case study integrates three major sensing technologies to capture both exterior and interior data: UAV-based photogrammetry and thermography (which enabled an additional Image-to-BIM process), as well as LiDAR scanning via an iOS device. The results prove that an affordable open-source Scan-to-BIM workflow is fully achievable, thus enabling smaller entities to access high-quality 3D documentation. Photogrammetry achieved millimetric-level accuracy relative to the real building, while the LiDAR surveys required little to no scale adjustment to match the results of both sensors, indicating the successful integration of multiple data sources within the open-source workflow. Finally, Blender, along with the Bonsai add-on, proved to be a versatile platform capable of efficiently managing complex Scan-to-BIM processes. Overall, the study demonstrates that open-source tools can support advanced BIM tasks; therefore, offering a practical and cost-effective alternative to proprietary software solutions.