Requirements for implementation of localization into real-world assistive environments

Accurate and efficient localization methods in sensor networks are critical to enabling a robust assistive environment where tracking human actions and interactions are needed to predict human behavior and prevent accidents. In this paper we describe an anchor-free localization approach where the sensor motes themselves determine their location without any given starting point or additional hardware. Instead, the location is discovered by allowing sensors to branch out through their connections to each other to establish maps that define their surroundings. We describe a Geographical Distributed Localization (GDL) algorithm which consists of a set of motes that compute local maps based on their hop counts from a special mote called bootstrap. In this paper, we provide a set of requirements for real world conditions, since GDL was developed and tested using the NS2 simulation system using synthetic data. It is now desired to test GDL in a real world assistive environment and generate a set of requirements that are useful in this and other settings. To do this, we chose Tmote Invent wireless sensors and designed ways to transfer the system from simulation to laboratory. Later, we used SunSPOT motes to continue the system. In this paper we report on specific features and requirements discovered that need to be taken into consideration to account for physical limitations of the sensors, when trying to move the system from one environment to another. Also, we provide new directions of research when mapping sensor localization to real-world environments, based on the given resources and the components available.

[1]  Gu-Yeon Wei,et al.  A portable, low-power, wireless two-lead EKG system , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[2]  Matt Welsh,et al.  Sensor networks for medical care , 2005, SenSys '05.

[3]  Yinyu Ye,et al.  Semidefinite programming based algorithms for sensor network localization , 2006, TOSN.

[4]  Mani B. Srivastava,et al.  The bits and flops of the n-hop multilateration primitive for node localization problems , 2002, WSNA '02.

[5]  Yurong Xu,et al.  GDL: A Geographic Distributed Localization Algorithm for Wireless Sensor Networks , 2006, Proceedings of 15th International Conference on Computer Communications and Networks.

[6]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[7]  Matt Welsh,et al.  CodeBlue: An Ad Hoc Sensor Network Infrastructure for Emergency Medical Care , 2004 .

[8]  M. Welsh,et al.  Vital Signs Monitoring and Patient Tracking Over a Wireless Network , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[9]  Michael A. Saunders,et al.  SpaseLoc: An Adaptive Subproblem Algorithm for Scalable Wireless Sensor Network Localization , 2006, SIAM J. Optim..

[10]  Marcos Augusto M. Vieira,et al.  Survey on wireless sensor network devices , 2003, EFTA 2003. 2003 IEEE Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No.03TH8696).

[11]  Yurong Xu,et al.  Mobile Anchor-Free Localization for Wireless Sensor Networks , 2007, DCOSS.

[12]  Matt Welsh,et al.  MoteTrack: A Robust, Decentralized Approach to RF-Based Location Tracking , 2005, LoCA.

[13]  P. Groenen,et al.  Modern Multidimensional Scaling: Theory and Applications , 1999 .

[14]  Matt Welsh,et al.  Ad-hoc multicast routing on resource-limited sensor nodes , 2006, REALMAN '06.

[15]  Andreas Savvides,et al.  XYZ: a motion-enabled, power aware sensor node platform for distributed sensor network applications , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[16]  Eric Becker,et al.  A BP-Neural Network Improvement to Hop-Counting for Localization in Wireless Sensor Networks , 2009, Tools and Applications with Artificial Intelligence.

[17]  Deborah Estrin,et al.  Localization in sensor networks , 2004 .

[18]  Trevor F. Cox,et al.  Metric multidimensional scaling , 2000 .