An Adaptive Automated Monitoring of Construction Activities using Swarm Nodes

Effective progress monitoring of construction activities is always of great value to project stakeholders. It is increasingly being recognized that the success of any project is hinged on the level of awareness of the project status. Although, automated technologies have shown to potentially offer real-time information for quick decision making, there is still resistance to their adoption because of the amount of effort required in obtaining progress data. This calls for investigations into approaches and technologies for creating an adaptive and automated monitoring method. Thus, to address this need, this paper introduces an approach for automatically tracking the status of installed steel components using swarm nodes. The swarm nodes are attached to prefabricated steel components and automatically range to each other in real-time during the steel installation process. In this way, the installation of each steel component and the correctness of the installation are automatically identified and verified in real-time. Particle swarm optimization is used to support an automated arrangement of the swarm nodes for adapting to any steel components configuration. The method of using swarm nodes for data collection, preliminary experiments and results are presented. The potential of the developed method for performance monitoring is also discussed.