The introduction of the Internet of Things (IoT) in the construction industry is evolving facility maintenance (FM) towards predictive maintenance development. Predictive maintenance of building facilities requires continuously updated data on construction components to be acquired through integrated sensors. The main challenges in developing predictive maintenance tools for building facilities is IoT integration, IoT data visualization on the building 3D model and implementation of maintenance management system on the IoT and building information modeling (BIM). The current 3D building models do not fully interact with IoT building facilities data. Data integration in BIM is challenging. The research aims to integrate IoT alert systems with BIM models to monitor building facilities during the operational phase and to visualize building facilities’ conditions virtually. To provide efficient maintenance services for building facilities this research proposes an integration of a digital framework based on IoT and BIM platforms. Sensors applied in the building systems and IoT technology on a cloud platform with opensource tools and standards enable monitoring of real-time operation and detecting of different kinds of faults in case of malfunction or failure, therefore sending alerts to facility managers and operators. Proposed preventive maintenance methodology applied on a proof-of-concept heating, ventilation and air conditioning (HVAC) plant adopts open source IoT sensor networks. The results show that the integrated IoT and BIM dashboard framework and implemented building structures preventive maintenance methodology are applicable and promising. The automated system architecture of building facilities is intended to provide a reliable and practical tool for real-time data acquisition. Analysis and 3D visualization to support intelligent monitoring of the indoor condition in buildings will enable the facility managers to make faster and better decisions and to improve building facilities’ real time monitoring with fallouts on the maintenance timeliness.

Facility Management (FM) regards the management of buildings’ assets and requires the administration of a large amount of data that must always be available, but today, they still consist of paper documents, which are susceptible to loss. This is one of the principal causes for costs increase in the Operation and Maintenance (O&M) phase, together with the lack of interoperability and communication. In recent years, the construction industry has been undergoing a process of digitalization, supported from the advent of new technologies that hit the market at low prices. This study aims to indagate the technologies introduced in in the FM sector, in addition the major authors and sources that are studying them. A bibliometric analysis is conducted on 220 documents belonging to the Scopus DB. The documents were analyzed using bibliometric analysis tools, such as Biblioshiny and VOSviewer. The results show how FM and the implementation of technologies in its practices, such as Building information modelling (BIM), Internet of Things (IoT) and Digital Twin (DT), are fields with exponential growth in recent years. Other technologies, such as blockchain, artificial intelligence (AI), machine learning (ML) and augmented reality (AR), emerged as part of digitalization in FM, which is part of the transition towards Construction 4.0.

In the last few years, modern technologies such as numerical simulations, virtual and augmented reality, and agent-based models represented effective tools to study phenomena, which may not be experimentally reproduced due to costs, inherent hazards, or other constraints (e.g., fire or earthquake emergencies and evacuation from buildings). This paper shows how to integrate a virtual reality platform with numerical simulation tools to reproduce an evolutionary fire emergency scenario. It is computed in real time based on the building information model and a fluid dynamic software. A specific software was also used to simulate in real time the crowd dynamic in the virtual environment during the emergency evacuation process. To demonstrate the applicability of the proposed methodology, the emergency fire evacuation process for an existing school building is presented. The results show that the proposed virtual reality-based system can be employed for reproducing fire emergency scenarios. It can be used to help decision-makers to determine emergency plans and to help firefighters as a training tool to simulate emergency evacuation actions.

All sectors have been affected by digital, economic, and demographic transitions. These will also be completely changing the paradigms of the construction industry, which is increasingly being pressured to implement strategic solutions in order to mitigate its own current environmental impact. Existing environmental standards and voluntary protocols are useful tools for reducing the environmental impact of buildings and infrastructures above all during the operation phase, but there is no consistent methodology for creating a circular and sustainable construction stage at the moment, probably because this represents a small stage in the entire life cycle of a structure; nevertheless, the construction industry impacts a lot on the environment and should be managed in a circular way. A detailed analysis of the current problem is provided, as well as a potential solution involving a transition to a circular economic model for the entire construction lifecycle, supported by innovative models and methodologies. The purpose of this article is to create a “Circular Construction Sites” (CCS) flow using circular concepts and to develop a circular methodology for construction sustainability, considering practical solutions related to materials, water, and waste management. According to the circular economy model, the circular construction site can communicate with other industrial ecosystems to promote external circularity and zero waste production. A set of potential key performance indicators (KPIs) for monitoring circularity processes is presented. Finally, a method is proposed that circularizes not only the building or infrastructure design, but also the construction phase.

The importance of sustainable building maintenance is growing as part of the Sustainable Building concept. The integration and implementation of new technologies such as the Internet of Things (IoT), smart sensors, and information and communication technology (ICT) into building facilities generate a large amount of data that will be utilized to better manage the sustainable building maintenance and staff. Anomaly prediction models assist facility managers in informing operators to perform scheduled maintenance and visualizing predicted facility anomalies on building information models (BIM). This study proposes a Machine Learning (ML) anomaly prediction model for sustainable building facility maintenance using an IoT sensor network and a BIM model. The suggested framework shows the data management technique of the anomaly prediction model in the 3D building model. The case study demonstrated the framework’s competence to predict anomalies in the heating ventilation air conditioning (HVAC) system. Furthermore, data collected from various simulated conditions of the building facilities was utilized to monitor and forecast anomalies in the 3D model of the fan coil. The faults were then predicted using a classification model, and the results of the models are introduced. Finally, the IoT data from the building facility and the predicted values of the ML models are visualized in the building facility’s BIM model and the real-time monitoring dashboard, respectively.

The civil engineering sector operates within a complex ecosystem of stakeholders, requiring efficient management and maintenance of structural and infrastructural assets. In this context, there is an increasing need for robust tools to track critical events (e.g., alerts, unusual behaviors) and support decision-making processes related to maintenance and interventions. At the same time, ensuring secure and prompt payments is essential for timely and effective responses. This paper investigated the potential of smart contracts, integrated with blockchain technology, to automate and optimize asset management and maintenance processes. The proposed framework examines how these technologies can enhance operational efficiency, security, and event traceability, providing a structured approach for both routine operations and emergency interventions. Although smart contracts have been widely applied in the construction phase of infrastructure projects, their use in long-term asset management remains largely unexplored. As a conceptual study, this work does not present a quantitative analysis but instead lays the groundwork for future research and real-world applications of blockchain-based smart contracts in infrastructure management and safety procedures.