Development of integrated framework for automated construction progress sensing, monitoring and evaluation
Loading...
Date
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Abstract
The construction industry is increasingly adopting digital technologies to enhance productivity and efficiency, in alignment with the principles of Construction 4.0 (C4). The progress and advances recorded thus far are largely due to advancements in cyber-physical systems (CPS), computational processing power, deep learning solutions, robotics, and other related technologies. However, a major challenge in this research space is the lack of an integrated solution for both the interior and exterior construction environments, which has led to fragmented data, hindering efficiency. Several researchers have proposed frameworks in recent years that focused on either indoor or outdoor construction environments; this approach has resulted in the creation of siloed information, to the detriment of the C4 ideals and principles. In this study, a comprehensive system architecture for raw data captured using sensors and other inputs to provide useful insight for the construction team and stakeholders was mapped out. This study presents an integrated framework of various technologies for both indoor and outdoor construction environments. The solution provided for localisation algorithms and technologies such as Simultaneous Localisation and Mapping (SLAM), odometry, and inertial measurement unit (IMU) devices. The unified 5-level Cyber-Physical Systems (CPS) architecture was used as the primary architecture, and it was compared with the IoT Architecture layers in terms of data analytics and management perspectives. The Digital Twin (DT), which sits at the cyber level of the architecture, warehouses and tracks in real-time the dynamic complexities of the construction site throughout the project life cycle, serving as the single source of truth for the project. This system architecture and framework presented in this research contributed towards advancing the field of construction automation by offering a scalable solution for efficient construction in project management.
Description
NOTE : Presented at the 12th International Electronic Conference on Sensors and Applications, 12–14 November 2025.
Keywords
Construction 4.0, Deep learning, Cyber-physical systems, Construction progress monitoring and evaluation, Building information modelling, Digital twin, Construction project systems architecture
Sustainable Development Goals
SDG-09: Industry, innovation and infrastructure
SDG-12: Responsible consumption and production
SDG-12: Responsible consumption and production
Citation
Olowe, M.T. & Ayomoh, M. Development of Integrated Framework for Automated Construction Progress Sensing, Monitoring and Evaluation. Engineering Proceedings 2025, 118, 49. https://doi.org/1.0.3390/ECSA-12-26603
