This paper aims to analyze the Blockchain level of implementation, focusing on the AEC sector that has always suffered from lack of trust, incomplete sharing, and transparency of information flow throughout the process execution. In this context, the progressive introduction of BIM based on the Blockchain technology can provide a trustworthy infrastructure for information management during the design, tender, and construction phases.

BIM alone would hardly meet the Construction 2025 targets, the Government Strategy aims at enabling a range of wider initiativesincluding Modern Methods of Constructions (MMC). Design for Manufacturing and Assembly (DfMA) is considered one of these advanced forms of construction (Antwi-Afari,

The research aims at analyzing the integration of Waste Management (WM) strategies and Information management in the construction procurement process. The application of Building information modelling (BIM) methodologies for a Most Economically Advantageous Tender could address the digital transition in order to adopt environmentally sustainable practices. Despite the wide regulation regarding waste minimization, an overview of which is provided, AECO is still one of the most polluting industrialized sector. Drivers and barriers to the method, and a literature review are provided: BIM approaches to enable WM practices have been analyzed from the designer and constructor’s point of view, but few studies investigated the role of the Client, in particular the Public Client. The goal of the study was to evaluate the efficiency of Most Economically Advantageous Tender and a BIM methodology to promote WM strategies during the tender phase. Design Built and Design Bid Built procurement models are tested through three case studies of Italian schools’ calls for proposals: the BIM model enabled to verify the bids in terms of WM strategies implementation. Blockchain and Smart contract future applications are also investigated in order to ensure transparency of the whole process. The Public Client could trigger a change in the construction sector regarding the integration of WM practices, as a central and active actor of the construction process, through the application of Green Public Procurement and BIM methodologies.

Both public administrations and private owners of large building stocks need to work out plans for the management of their property, while having to deal with yearly budget limitations. Particularly for the former, this is a rather critical challenge, since public administrations are given the responsibility of sticking to very strict budget distributions over the years. As a consequence, when planning the actions to be taken on their building stocks in order to comply with their current use and the legislation in-force, they need to classify refurbishment priorities. The aim of this paper is to develop a first tool based on Bayesian Networks that offers an effective decision support service for owners even in case some information is incomplete. This tool can be used to evaluate the compliance of existing buildings with the latest standards. The decision support platform proposed includes a multi-criteria evaluation approach combining several performance indicators, each of which related to a specific regulatory area. This tool can be applied to existing buildings, where the building with the lowest score shows the highest priority of intervention. Also, the platform performs an assessment of expected costs for required refurbishment or renovation actions.

This study focuses on calibration and test campaigns of an IoT camera-based sensor system to monitor occupancy, as part of an ongoing research project aiming at defining a Building Management System (BMS) for facility management based on an occupancy-oriented Digital Twin (DT). The research project aims to facilitate the optimization of building operational stage through advanced monitoring techniques and data analytics. The quality of collected data, which are the input for analyses and simulations on the DT virtual entity, is critical to ensure the quality of the results. Therefore, calibration and test campaigns are essential to ensure data quality and efficiency of the IoT sensor system. The paper describes the general methodology for the BMS definition, and method and results of first stages of the research. The preliminary analyses included Indicative Post-Occupancy Evaluations (POEs) supported by Building Information Modelling (BIM) to optimize sensor system planning. Test campaign are then performed to evaluate collected data quality and system efficiency. The method was applied on a Department of Politecnico di Milano. The period of the year in which tests are performed was critical for lighting conditions. In addition, spaces’ geometric features and user behavior caused major issues and faults in the system.