Localization of RFID-equipped assets during the operation phase of facilities

  • Authors:
  • Ali Motamedi;Mohammad Mostafa Soltani;Amin Hammad

  • Affiliations:
  • Special Individualized Program (SIP), Concordia University, 2145 Mackay Street, S204, Montreal, Quebec H3G 2J2, Canada;Building, Civil and Environmental Engineering, Concordia University, 1455 de Maisonneuve Blvd. West, EV-6.139, Montreal, Quebec H3G 1M8, Canada;Concordia Institute for Information Systems Engineering, Concordia University, 1515 Ste-Catherine Street West, EV7.643, Montreal, Quebec H3G 2W1, Canada

  • Venue:
  • Advanced Engineering Informatics
  • Year:
  • 2013

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Abstract

Indoor localization has gained importance as it has the potential to improve various processes related to the lifecycle management of facilities and to deliver personalized and location-based services (LBSs). Radio Frequency Identification (RFID) based systems, on the other hand, have been widely used in different applications in construction and maintenance. This paper investigates the usage of RFID technology for indoor localization of RFID equipped assets during the operation phase of facilities. The location-related data on RFID tags attached to assets are extracted from a Building Information Model (BIM) and can provide context-aware information inside the building which can improve Facilities Management (FM) processes. First, using the current location of the assets saved on the tags attached to fixed assets, an FM personnel is able to read tags from a distance and locate them on a floor plan. Fixed tags with known positions act as reference tags for RFID reader localization techniques. In this scenario, the user can also estimate his/her location by scanning the surrounding reference tags. Furthermore, the paper investigates an approach to locate moveable assets using received signals from available reference tags in the building based on pattern matching and clustering algorithms. As a result, a user equipped with an RFID reader is able to estimate his/her location, as well as the location of target assets, without having access to any Real-Time Location System (RTLS) infrastructure. Several case studies are used to demonstrate the feasibility of the proposed methods.