Summary
There are a number of techniques used in modern Location aware systems such as Received Signal Strength Indicator (RSSI), Time of Arrival (TOA), Time Difference of Arrival (TDOA) and Angle of Arrival (AOA). However the benefit of RSSI-based location positioning technologies, is the possibility to develop location estimation systems without the need for specialised hardware.
The human body contains more than 70% water which is causing changes in the RSSI measurements. It is known that the resonance frequency of the water is 2.4 GHz. Thus a human presence in an indoor environment attenuates the wireless signal. Device-free Passive (DfP) localisation is a technique to detect a person without the need for any physical devices i.e. tags or sensors. A DfP Localisation system uses the Received Signal Strength Indicator (RSSI) for monitoring and tracking changes in a Wireless Network infrastructure. The changes in the signal along with prior fingerprinting of a physical location allow identification of a person’s location. This research is focused on implementing DfP Localisation built using a Wireless Sensor Network (WSN). The aim of this paper is the evaluation of various smoothing algorithms for the RSSI recorded in a Device-free Passive (DfP) Localisation scenario in order to find an algorithm that generates the best output. The best output is referred to here as results that can help us decide if a person entered the monitored environment. The DfP scenario considered in this paper is based on monitoring the changes in the wireless communications due to the presence of a human body in the environment. Thus to have a clear image of the changes caused by human presence indoors, the wireless recordings need to be smoothed.We show results using algorithms such as five-point Triangular Smoothing Algorithm, 1-D median filter, Savittzky-Golay filter, and Kalman filter.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kolodziej, K.W., Hjelm, J.: Local positioning systems: LBS applications and services. CRC Press, Boca Raton (2006)
Zhou, R.: Wireless indoor tracking system (WITS). In: Aktuelle Trends in der Soft-wareforschung, Tagungsband zum doIT Software-Forschungtag, dpunkt, Heidelberg, Germany, pp. 163–177 (2006) (to appear)
Krumm, J.: Ubiquitous Computing Fundamentals. CRC Press, Boca Raton (2010)
Kupper, A.: Location-Based Services: Fundamentals and Operation. Wiley, Chichester (2005)
Bensky, A.: Wireless positioning technologies and applications. Artech House, Boston (2007)
Liu, H., Darabi, H., Banerjee, P., Liu, J.: Survey of Wireless Indoor Positioning Techniques and Systems. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 37(6), 1067–1080 (2007)
Yu, K., Sharp, I., Guo, Y.J.: Ground-Based Wireless Positioning. Wiley-IEEE Press (2009)
Ito, S., Kawaguchi, N.: Bayesian Based Location Estimation System Using Wireless LAN. In: Third IEEE International Conference on Pervasive Computing and Communications Workshops, pp. 273–278 (2005)
Nerguizian, C., Despins, C., Affes, S.: Indoor geolocation with received signal strength ingerprinting technique and neural networks. LNCS, pp. 866–875 (2004)
Stoyanova, T., Kerasiotis, F., Prayati, A., Papadopoulos, G.: Evaluation of impact factors on RSS accuracy for localization and tracking applications in sensor networks. Telecommunication Systems 42(3-4), 235–248 (2009)
Curran, K., Furey, E.: Pinpointing users with location estimation techniques and Wi-Fi hotspot technology. International Journal of Network Management 16(5) (2007)
Munoz, D., Lara, F.B., Vargas, C., Enriquez-Caldera, R.: Position Location Techniques and Applications. Academic Press, London (2009)
Addlesee, M., Curwen, R., Hodges, S., Newman, J., Steggles, P., Ward, A., Hopper, A.: Implementing a sentient computing system. Computer, 50–56 (2001)
Steggles, P., Gschwind, S.: The Ubisense smart space platform. In: Adjunct Proceedings of the Third International Conference on Pervasive Computing, vol. 191, pp. 73–76 (2005)
Ubisense. Ubisense System (2010)
Griffth, E.: New Finds in Real-Time Location (2007)
Priyantha, N.B., Chakraborty, A., Balakrishnan, H.: The cricket locationsupport system. In: Proceedings of the 6th annual international conference on Mobile computing and networking, pp. 32–43. ACM, New York (2000)
Curran, K., Norrby, S.: RFID-Enabled Location Determination within Indoor Environments. International Journal of Ambient Computing and Intelligence 1(4), 63–86 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Deak, G., Curran, K., Condell, J. (2010). Evaluation of Smoothing Algorithms for a RSSI-Based Device-Free Passive Localisation. In: ChoraĹ›, R.S. (eds) Image Processing and Communications Challenges 2. Advances in Intelligent and Soft Computing, vol 84. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16295-4_52
Download citation
DOI: https://doi.org/10.1007/978-3-642-16295-4_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16294-7
Online ISBN: 978-3-642-16295-4
eBook Packages: EngineeringEngineering (R0)