Abstract
abstract Article history:Accepted 21 June 2013Available online xxxxKeywords:RFIDIndoor location identificationRSSITriangulationProximityMaterial tracking Thispaperpresentsalowcostindoorlocationidentificationandmaterialtrackingmethodologyforconstructionprojects using Ultra High Frequency (UHF) passive Radio Frequency Identification (RFID) technology. Onsitelocation aware information is an emerging area that focuses on automating delivery of spatial informationpertinent to location of materials, workforce, and equipment. This spatial information can be used to deriveknowledge about construction project status. A two-step algorithm is presented to automate the process oflocation estimation and material tracking in near-real-time. In this methodology, a number of passive RFIDtags are distributed onsite where work is progressing, and a mobile RFID reader is carried by a worker onsite.Each passive RFID tag is deployed as a reference point with a known location (landmark) within a predefinedzone. Reference tags of known locations are used to determine the location of the worker and eventually locateand track surrounding materials. The methodology uses Received Signal Strength Indicator (RSSI) for signalmeasurements. Two localization methods (triangulation and proximity) were used to identify the location ofthe worker. Testing this methodology was carried out on an actual construction jobsite, where five test bedswere setup at different locations and within different construction time spans. In addition, one test bed wassetupinalabenvironment.Theresultspresentedinthisstudydemonstratethepotentialforalow-costmethodforlocationestimationandmaterialtrackingofindoorconstruction.Theresultsshowameanerrorof1.0 mand1.9 m for user location identification and material tracking using the triangulation method, respectively. Theresults also show a mean error of 1.9 m and 2.6 m for location identification of the worker and for materialtracking using the proximity method, respectively. The proposed methodology detects the zones of workerand material location with 100% accuracy.© 2013 Elsevier B.V. All rights reserved.
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