Construction progress monitoring (CPM) is essential for effective project management, ensuring on-time and on-budget delivery. Traditional CPM methods often rely on manual inspection and reporting, which are time-consuming and prone to errors. This paper proposes a novel approach for automated CPM using state-of-the-art object detection algorithms. The proposed method leverages e.g. YOLOv8's real-time capabilities and high accuracy to identify and track construction elements within site images and videos. A dataset was created, consisting of various building elements and annotated with relevant objects for training and validation. The performance of the proposed approach was evaluated using standard metrics, such as precision, recall, and F1-score, demonstrating significant improvement over existing methods. The integration of Computer Vision into CPM provides stakeholders with reliable, efficient, and cost-effective means to monitor project progress, facilitating timely decision-making and ultimately contributing to the successful completion of construction projects. 

Computer Vision for Construction Progress Monitoring: A Real-Time Object Detection Approach

Current building data is treated as silos from the different building domains. However, this provokes the lack of cross-domain data mixture to provide added-value services, mainly due to lack of interoperability. Data quality is also an issue when collecting data from buildings. The proposed data lake aims to solve these challenges by considering the whole data life-cycle to ensure minimum data quality requirements, providing high-quality services to make better-informed decisions. Heterogeneous building-related data is thus combined to enrich the information, being able to address multiple stakeholders in the smart building context. The data lake is being deployed in the DigiBUILD project, where data from 10 pilots with different purposes are collected to demonstrate the capability and benefits of its application. 

From silos to open, federated and enriched Data Lakes for smart building data management

This paper describes how digital twin technology can be used to develop holistic, standardized building documentation, paving the way from the traditional, national ‘Bauwerksbuch’ to the proposed, international EU-building logbook. The research explores the concept of digital twins and their potential to harmonize long-term data management for facilities, enabling the set-up of international collaborative networks among various stakeholders. The study highlights the benefits of digital twins to support collaboration between property owners, public authorities, building inspectors, and different engineering disciplines for maintenance, energy efficiency, and sustainability. It specifies the steps required for improving data quality, consistency, and accuracy of the ‘digital sibling’ to match reality to the greatest extent possible, ensuring seamless collaboration across networks. The authors highlight the potential of building logbooks to transform the way we manage facilities, improve energy efficiency and sustainability, and deliver decision support for the long-term maintenance of our built environment, through a collaborative network approach. 

Digital Twins as Enabler for Long Term Data Management Using Building Logbooks

Activities on construction sites are dynamic and require high collaboration. Specialist teams from various trades contribute to the core processes, while a wide range of support processes, such as logistics and quality management, complement these activities. As a result, multiple stakeholders collaborate daily in a dynamically changing workplace, which is often exposed to shifting environmental and safety conditions. This paper presents the results of the initial steps taken in the development of a Software Service with the aim of enhancing health and safety on construction sites. The primary objective of this service is to automatically trigger messages when individuals enter dangerous work zones on construction sites. The publication provides a comprehensive analysis of state-of-the-art technologies for dynamically marking hazardous zones and securely and anonymously identifying and alerting relevant personnel. Furthermore, the paper specifies the available sources of information, such as BIM-Models and RFID systems, and proposes alternative approaches for systems integration. Finally, the output of this publication is a construction safety model that describes the workflow of generating and disseminating safety information among stakeholders. 

Improving Safety on Construction Sites by Exploiting IoT, Digital Twins, and Data Fusion

A BPMN-Based Multi-tenant Customizable SaaS Application: A FARUL3S Case Study

Abstract The purpose of Linked Data and ontologies is to achieve semantic interoperability across different systems and agents. As a concrete implementation, Digital Construction Ontologies (DiCon) are meant to provide efficient information sharing and utilization between the tools in the BIM4EEB toolkit. This section explains the motivations, design principles, and organization of DiCon ontologies. 

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Linked Data and Ontologies for Semantic Interoperability

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Linked Data and Ontologies for Semantic Interoperability