Epistemic Model to Monitor the Position of Mobile Sensing Nodes on Construction Sites with Rough Location Data

Abstract

Construction organizations are rapidly engaging in the utilization of infrastructureless identification and localization technologies with the purpose of increasing the visibility of their site resources and, more specifically, of their nonbulk materials. With such infrastructureless technologies, a wireless identification device attached to a nonbulk material becomes a mobile sensing node. Even though relatively inexpensive, infrastructureless technologies result in rough node locations that prevent a reliable assessment of the actual node positions. Thus, an opportunity to characterize multiple handling of materials and, by extension, materials handling processes is being missed. However, efficiently monitoring the position of mobile sensing nodes—the coordinates of which remain unknown—with low-accuracy locations is a nontrivial problem that cannot be likely solved using deterministic or classic probability approaches. This study presents an epistemic model based on belief functions that can feasibly monitor the positions of mobile sensing nodes. The feasibility of the model is compared to empirical evidence. The results demonstrate that epistemic functions can, to a large extent, correctly filter location uncertainties and monitor the movements of mobile sensing nodes.