To wireless fidelity and beyond — CAPTURE, extending indoor positioning systems

Most of the current research into indoor localization has surrounded the problem of positioning accuracy, with attempts to solve this using a myriad of technologies and algorithms. One of the problems that seems to be somewhat overlooked is the issue of coverage in an indoor localization solution. The mostly unobstructed views of the Global Positioning System (GPS) which requires a mere 30 satellites to provide global coverage never had these problems. Unfortunately unobstructed views are not something that can be achieved in most indoor environments and economical as well as physical barriers can prevent the installation of an infrastructure to achieve total coverage. In this paper we propose a solution to this issue of indoor coverage by deploying a solution to extend the range of a positioning system - Cooperatively Applied Positioning Techniques Utilizing Range Extension (CAPTURE). CAPTURE provides a system to locate devices that cannot be reached by an in-house location based system. It presents a unique contribution to research in this field by offering the ability to utilize devices that currently know their location within a Location Based Solution (LBS), to help evaluate the position of unknown devices beyond the range capacity of the LBS. Effectively extending the locating distances of an Indoor LBS by utilizing the existing mobile infrastructure without the requirement for additional hardware. CAPTURE uses the Bluetooth radios on mobile devices to estimate the distance between devices, before inserting these range estimates into a trilateration algorithm to ascertain position. CAPTURE has been tested through experiments carried out in a real world environment, proving the capacity to provide a solution to the ranging issue.

[1]  Paul Lukowicz,et al.  Emergent Behaviour in Collaborative Indoor Localisation: An Example of Self-organisation in Ubiquitous Sensing Systems , 2011, ARCS.

[2]  Lei Zhang,et al.  Variation of Received Signal Strength in Wireless Sensor Network , 2011, 2011 3rd International Conference on Advanced Computer Control.

[3]  Moustafa Youssef,et al.  Robust WLAN Device-free Passive motion detection , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[4]  Jaime García-Reinoso,et al.  Bluetooth location networks , 2002, Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE.

[5]  Goran M. Djuknic,et al.  Geolocation and Assisted GPS , 2001, Computer.

[6]  Juan C. García,et al.  RSSI distance estimation based on Genetic Programming , 2013, International Conference on Indoor Positioning and Indoor Navigation.

[7]  Kevin Curran,et al.  CAPTURE — Cooperatively applied positioning techniques utilizing range extensions , 2014, 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN).

[8]  Samer S. Saab,et al.  A Standalone RFID Indoor Positioning System Using Passive Tags , 2011, IEEE Transactions on Industrial Electronics.

[9]  Mohamed Aly,et al.  Street view goes indoors: Automatic pose estimation from uncalibrated unordered spherical panoramas , 2012, 2012 IEEE Workshop on the Applications of Computer Vision (WACV).

[10]  Yuwei Chen,et al.  Information filter with speed detection for indoor Bluetooth positioning , 2011, 2011 International Conference on Localization and GNSS (ICL-GNSS).

[11]  Wan-Young Chung,et al.  Enhanced RSSI-Based Real-Time User Location Tracking System for Indoor and Outdoor Environments , 2007, 2007 International Conference on Convergence Information Technology (ICCIT 2007).

[12]  Jari Nurmi,et al.  Hand-grip and body-loss impact on RSS measurements for localization of mass market devices , 2011, 2011 International Conference on Localization and GNSS (ICL-GNSS).

[13]  Shigeo Shioda,et al.  Anchor-free localization: Estimation of relative locations of sensors , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[14]  Prashant Krishnamurthy,et al.  Properties of indoor received signal strength for WLAN location fingerprinting , 2004, The First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services, 2004. MOBIQUITOUS 2004..

[15]  Marika Egyed,et al.  Effects of Age, Season, Gender and Urban-Rural Status on Time-Activity: Canadian Human Activity Pattern Survey 2 (CHAPS 2) , 2014, International journal of environmental research and public health.

[16]  Changseok Bae,et al.  Automatic WBAN area recognition using P2P signal strength in office environment , 2014, 16th International Conference on Advanced Communication Technology.

[17]  Hua Lu,et al.  Improving Wi-Fi Based Indoor Positioning Using Bluetooth Add-Ons , 2011, 2011 IEEE 12th International Conference on Mobile Data Management.

[18]  Ana M. Bernardos,et al.  A fusion method based on bluetooth and WLAN technologies for indoor location , 2008, 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems.

[19]  Sheikh Iqbal Ahamed,et al.  RSSI Based Indoor Localization for Smartphone Using Fixed and Mobile Wireless Node , 2013, 2013 IEEE 37th Annual Computer Software and Applications Conference.

[20]  John K. Pollard,et al.  Position measurement using Bluetooth , 2006, IEEE Transactions on Consumer Electronics.

[21]  Kevin Curran,et al.  Cooperatively extending the range of indoor localisation , 2013 .