SALT : Source-Agnostic Localization Technique Based on Context Data from Binary Sensor Networks

Localization is a key component for many AAL systems, since the user position can be used for detecting user’s activities and activating devices. While for outdoor scenarios Global Positioning System (GPS) constitutes a reliable and easily available technology, in indoor scenarios, in particular in real homes, GPS is largely unavailable. For this reason, several systems have been proposed for indoor localization. Recently, several algorithms fuse information coming from different sources in order to improve the overall accuracy in monitoring user activities. In this paper we propose a Source-Agnostic Localization Technique, called SALT, that fuses the information (coordinates) provided by a localization system with the information coming from the binary sensor network deployed within the environment. In order to evaluate the proposed framework, we tested our solution by using a previous developed heterogeneous localization systems presented at the international competition EvAAL 2013.

[1]  Philippe Canalda,et al.  A GPS/Wi-Fi/Marker Analysis Based Simultaneous and Hierarchical Multi-Positioning System , 2013, EvAAL.

[2]  T. Teixeira,et al.  A Survey of Human-Sensing : Methods for Detecting Presence , Count , Location , Track , and Identity , 2010 .

[3]  Keith Cheverst,et al.  Developing a context-aware electronic tourist guide: some issues and experiences , 2000, CHI.

[4]  Gregory D. Abowd,et al.  Ubicomp 2001: Ubiquitous Computing , 2001, Lecture Notes in Computer Science.

[5]  K. Takase,et al.  Improvement of performance of localization ID tag using multi-antenna RFID system , 2008, 2008 SICE Annual Conference.

[6]  Alexei V. Soloviev,et al.  RealTrac Technology Overview , 2013, EvAAL.

[7]  Tim Wark,et al.  A Wireless Sensor Network for Real-Time Indoor Localisation and Motion Monitoring , 2008, 2008 International Conference on Information Processing in Sensor Networks (ipsn 2008).

[8]  Amedeo Cesta,et al.  GiraffPlus: Combining social interaction and long term monitoring for promoting independent living , 2013, 2013 6th International Conference on Human System Interactions (HSI).

[9]  Gerald Pirkl,et al.  Indoor Localization Based on Resonant Oscillating Magnetic Fields for AAL Applications , 2013, EvAAL.

[10]  Christopher G. Atkeson,et al.  Simultaneous Tracking and Activity Recognition (STAR) Using Many Anonymous, Binary Sensors , 2005, Pervasive.

[11]  Andreas Braun,et al.  AmbiTrack - Marker-free Indoor Localization and Tracking of Multiple Users in Smart Environments with a Camera-based Approach , 2013, EvAAL.

[12]  Pedro José Marrón,et al.  Enhancements to the LOCOSmotion Person Tracking System , 2013, EvAAL.

[13]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[14]  Stefano Chessa,et al.  Context driven enhancement of RSS-based localization systems , 2011, 2011 IEEE Symposium on Computers and Communications (ISCC).

[15]  Uwe Hansmann,et al.  Pervasive Computing , 2003 .

[16]  Wolfram Burgard,et al.  Modeling RFID signal strength and tag detection for localization and mapping , 2009, 2009 IEEE International Conference on Robotics and Automation.

[17]  Stefano Chessa,et al.  Evaluation of localization and activity recognition systems for ambient assisted living: The experience of the 2012 EvAAL competition , 2013, J. Ambient Intell. Smart Environ..

[18]  Gerhard Goos,et al.  Ambient Intelligence , 2015, Lecture Notes in Computer Science.

[19]  Jorge Dias,et al.  Indoor Localization and Tracking Using 802.11 Networks and Smartphones , 2013, EvAAL.

[20]  P. Pasquina,et al.  Sensor technology for smart homes. , 2011, Maturitas.

[21]  Ted Kremenek,et al.  A Probabilistic Room Location Service for Wireless Networked Environments , 2001, UbiComp.

[22]  Moe Z. Win,et al.  Cooperative Localization in Wireless Networks , 2009, Proceedings of the IEEE.

[23]  Gregory D. Abowd,et al.  Cyberguide: A mobile context‐aware tour guide , 1997, Wirel. Networks.

[24]  Fernando Seco Granja,et al.  Accurate Pedestrian Indoor Navigation by Tightly Coupling Foot-Mounted IMU and RFID Measurements , 2012, IEEE Transactions on Instrumentation and Measurement.

[25]  Eduardo F. Nakamura,et al.  Information fusion for wireless sensor networks: Methods, models, and classifications , 2007, CSUR.

[26]  Paolo Barsocchi,et al.  EvAAL, Evaluating AAL Systems through Competitive Benchmarking, the Experience of the 1st Competition , 2011, EvAAL.

[27]  Silvia Coradeschi,et al.  Sensor Network Infrastructure for a Home Care Monitoring System , 2014, Sensors.

[28]  Stefano Chessa,et al.  Evaluating Ambient Assisted Living Solutions: The Localization Competition , 2013, IEEE Pervasive Computing.

[29]  Abdelhamid Tayebi,et al.  LOCALIZATION APPROACH BASED ON RAY-TRACING INCLUDING THE EFFECT OF HUMAN SHADOWING , 2010 .

[30]  Kostas E. Bekris,et al.  On the feasibility of using wireless ethernet for indoor localization , 2004, IEEE Transactions on Robotics and Automation.

[31]  Stefano Chessa,et al.  Evaluating AAL Systems Through Competitive Benchmarking , 2012, Communications in Computer and Information Science.