Localization for the resources and workers on construction sites is significant and essential for effective construction projects management. Since global positioning system (GPS) usually does not work indoor, indoor localization is critical for jobsite indoor resource and labor management. However, due to the complex and variable environment situation on construction jobsites, accuracy and quick deployment remains to be two primary challenges for practical and wide adoption of localization technology on jobsites. As radio signal strength index (RSSI) based indoor localization techniques have relatively low costs and easy deployments comparing to other techniques (e.g., Ultra Wide Band, Ultrasonic), RSSI-based localization technologies have attracted much attention in construction industry. However, the accuracy of existing RSSI-based technologies is still not satisfactory. Therefore, the authors proposed to improve the accuracy of RSSI-based indoor localization technology by utilizing the information extracted from BIM in the localization algorithm. A lab with BIM model is used as the testbed for the algorithm’s validation at 19 discrete locations and one continuous moving path. The test results indicate that the localization accuracy can be improved by filtering up to 25.6% of the infeasible positions based on building information modelling (BIM).


Resource management, Labor, Global positioning systems, Algorithms, Building information modeling, Construction sites, Construction costs, Model accuracy


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