Integration of BIM, IoT and AI for Predictive Construction Management

Digital innovation has revolutionised the construction sector, bringing sophisticated technologies for infrastructure monitoring and predictive management. This study introduces a comprehensive methodology utilising BIM, IoT and AI to enhance the maintenance and operational efficiency of buildings via the deployment of the DT. BIM offers a comprehensive digital representation of structures, whereas IoT sensors gather real-time data on environmental and structural variables, including temperature, humidity, and soil conditions. AI employs machine learning algorithms to analyse data, detect abnormalities, forecast failures, and enhance building management. The ThingsBoard platform facilitates the collection and visualisation of IoT data, producing automatic warnings upon the surpassing of important thresholds. A case study on a single-family residence was conducted to validate the suggested methodology. IoT sensors affixed to the structure continuously monitor the building’s state, supplying data integrated into the BIM model. The analysed data enable the prediction of structural issues and the recommendation of preventive maintenance measures, thereby decreasing costs and enhancing safety. The findings illustrate that the amalgamation of BIM, IoT, and AI can transform the construction industry, enhancing the efficiency, sustainability, and safety of infrastructures. This methodology signifies progress towards more intelligent, robust, and proactively managed buildings.