Localization of Bluetooth Smart Equipped Assets Based on Building Information Models

Indoor positioning systems are utilized to locate physical objects indoors without using GPS. Their applications include but are not limited to industry, business, and healthcare. This paper provides an analysis of a model and simulation of an indoor localization method which tracks physical assets relying on Bluetooth Smart. The system receives the desired building’s floor plan and the materials of all walls and surfaces from the Building Information Model. The walls and surfaces have their own particular radio frequency (RF) absorption efficiency and transmission loss; when any propagated wave signal reaches a barrier, some of the signal will be reflected, some will be absorbed, and the rest will be transmitted through the barrier. This study implements the floor plan of a building and simulates the reflection and transmission of all signals (building’s RF fingerprint map). To do so, the system generates a mesh for each Bluetooth reader, and calculates the level of received signal strength indicator (RSSI) for any points on the mesh. For each of these points, the simulation shows the propagation of RF signals in all directions and finds the summation of signals that may reach the reader to find the RSSI of that point.

[1]  Niall Twomey,et al.  An RSSI-based wall prediction model for residential floor map construction , 2015, 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT).

[2]  Filip Maly,et al.  Improving Indoor Localization Using Bluetooth Low Energy Beacons , 2016, Mob. Inf. Syst..

[3]  Yunhao Liu,et al.  Smartphones Based Crowdsourcing for Indoor Localization , 2015, IEEE Transactions on Mobile Computing.

[4]  Jie Liu,et al.  A realistic evaluation and comparison of indoor location technologies: experiences and lessons learned , 2015, IPSN.

[5]  Igor Bisio,et al.  A new asset tracking architecture integrating RFID, Bluetooth Low Energy tags and ad hoc smartphone applications , 2016, Pervasive Mob. Comput..

[6]  Sen Wang,et al.  Keyframe based large-scale indoor localisation using geomagnetic field and motion pattern , 2016, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[7]  Imrich Chlamtac,et al.  Indoor location tracking using RSSI readings from a single Wi-Fi access point , 2007, Wirel. Networks.

[8]  Rosdiadee Nordin,et al.  Recent Advances in Wireless Indoor Localization Techniques and System , 2013, J. Comput. Networks Commun..

[9]  Juan Manuel Górriz,et al.  RF fingerprint measurements for the identification of devices in wireless communication networks based on feature reduction and subspace transformation , 2014 .

[10]  Tom Chau,et al.  A Review of Indoor Localization Technologies: towards Navigational Assistance for Topographical Disorientation , 2010 .

[11]  Moustafa Youssef,et al.  A Robust Zero-Calibration RF-Based Localization System for Realistic Environments , 2016, 2016 13th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON).

[12]  Thierry Val,et al.  BLE localization using RSSI measurements and iRingLA , 2015, 2015 IEEE International Conference on Industrial Technology (ICIT).

[13]  Amin Hammad,et al.  Localization of RFID-equipped assets during the operation phase of facilities , 2013, Adv. Eng. Informatics.

[14]  Zulfazli Hussin Fast-converging indoor mapping for wireless indoor localization , 2014, 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS).

[15]  Sanjay Jha,et al.  Received signal strength indicator and its analysis in a typical WLAN system (short paper) , 2013, 38th Annual IEEE Conference on Local Computer Networks.

[16]  Yunhao Liu,et al.  Locating in fingerprint space: wireless indoor localization with little human intervention , 2012, Mobicom '12.

[17]  Shaojie Tang,et al.  Wi-Fi Fingerprint Based Indoor Localization without Indoor Space Measurement , 2013, 2013 IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems.

[18]  Robert Schulcz,et al.  Indoor location services and context-sensitive applications in wireless networks , 2010, 2010 International Conference on Indoor Positioning and Indoor Navigation.

[19]  Prathima Agrawal,et al.  ARIADNE: a dynamic indoor signal map construction and localization system , 2006, MobiSys '06.

[20]  Jörg Stückler,et al.  Cosero, Find My Keys! Object Localization and Retrieval Using Bluetooth Low Energy Tags , 2014, RoboCup.