Wireless indoor tracking network based on Kalman filters with an application to monitoring dairy cows

Computers and Electronics in Agriculture

Volumn 72, Issue 2, 2010, Pages 119-126

  Tøgersen, Frede Aakmann ^a,c   Skjøth, Flemming ^b   Munksgaard, Lene ^c   Højsgaard, Søren ^c  

^a VESTAS WIND SYSTEMS A S   (Denmark)

^b AgroTech A/S   (Denmark)

^c AARHUS UNIVERSITY   (Denmark)

Author keywords

Fraser Potter algorithm; Geolocation; Indoor tracking; Kalman filters; Localisation; Pre smoothing; Received signal strength indicator; RSSI; Sensor networks; Time interpolation

Indexed keywords

GEOLOCATIONS; INDOOR TRACKING; LOCALISATION; PRE-SMOOTHING; RECEIVED SIGNAL STRENGTH INDICATOR; RECEIVED SIGNAL STRENGTH INDICATORS; TIME INTERPOLATION;

ALGORITHMS; INTERPOLATION; KALMAN FILTERS; SENSOR NETWORKS; SIGNAL TO NOISE RATIO;

SIGNAL PROCESSING;

ALGORITHM; CATTLE; INTERPOLATION; KALMAN FILTER; MONITORING; SENSOR; SIGNAL-TO-NOISE RATIO; TRACKING;

BOS;

EID: 77954864486     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2010.03.006     Document Type: Article

References (31)

1. Bluetooth Special Interest Group, I., 2007. Bluetooth basics. URL http://www. bluetooth. com/Bluetooth/Learn/.
2. Brown R.G., Hwang P.Y.C. Introduction to Random Signals and Applied Kalman Filtering 1997, Wiley & Sons, New York. 3rd Edition.
3. Burrell J., Brooke T., Beckwith R. Vineyard computing: sensor networks in agricultural production. IEEE Pervasive Computing 2004, 3(1):38-45.
4. Catrein D., Hellebrandt M., Mathar R., Serrano M.P. Location tracking of mobiles: a smart filtering method and its use in practice. Proceedings of Vehicular Technology Conference, 2004, vol. 5 2004, 2677-2681.
5. Chen Y.-C., Chiang J.-R., Chu H.-h., Huang P., Tsui A.W. Sensor-assisted Wi-Fi indoor location system for adapting to environmental dynamics. Proceedings of the 8th ACM International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems Table of Contents. ACM: Association for Computing Machinery 2005, 118-125.
6. Christensen R. Linear Models for Multivariate, Time Series and Spatial Data 1997, Springer Texts in Statistics, Springer, New York. second ed.
7. de Jong P., MacKinnon M.J. Covariances for smoothed estimates in state space models. Biometrika 1988, 75(3):601-602.
8. Forno F., Malnati G., Portelli G. Design and implementation of a Bluetooth ad hoc network for indoor positioning. Software, IEEE Proceedings of, vol. 152 2005, 223-228.
9. Fraser D.C., Potter J.E. The optimum linear smoother as a combination of two optimal linear filters. IEEE Transaction on Automatic Control 1969, 14(4):387-390.
10. Gami S., Krishnakumar A.S., Krishnan P. Infrastructure-based location estimation in WLAN. Wireless Communications and Networking Conference, vol. 1 2004, 465-470. IEEE.
11. Hart B.L. The behaviour of sick animals. Veterinary Clinics of North America-Small Animal Practice 1991, 21:225-237.
12. Hellebrandt M., Mathar R. Location tracking of mobiles in cellular radio networks. Vehicular Technology, IEEE Transactions on 1999, 48(5):1558-1562.
13. Huhtala A., Suhonen K., Mäkelä P., Hakojärvi M., Ahokas J. Evaluation of instrumentation for cow positioning and tracking indoors. Biosystems Engineering 2007, 96(3):399-405.
14. Kaemarungsi K., Krishnamurthy P. Modeling of indoor positioning systems based on location fingerprinting. INFOCOM 2004. Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies, vol. 2 2004, 1012-1022.
15. Kalman R.E. A new approach to linear filtering and prediction problems. Transactions of the ASME, Journal of Basic Engineering 1960, 82:34-45.
16. Kerbrat S., Disenhaus C. A proposition for an updated behavioural characterization of the oestrus period in dairy cows. Applied Animal Behaviour Science 2004, 87:223-238.
17. Kumar K.R., Apte V., Powar Y.A. Improving the accuracy of wireless LAN based location determination systems using Kalman filter and multiple observers, vol. 1. Wireless Communications and Networking Conference, 2006 2006, 463-468.
18. LaViola J.J.J. A comparison of unscented and extended Kalman filtering for estimating quaternion motion. Proceedings of the 2003 American Control Conference, vol. 3 2003, 2435-2440.
19. LaViola J.J.J. An experiment comparing double exponential smoothing and Kalman filterbased predictive tracking algorithms. IEEE Proceedings of Virtual Reality 2003 2003, 283-284.
20. Lee, Y.K., Jung, Y.J., Ryu, K.H., 2007. Advances in Web and Network Technologies, and Information Management. Vol. 4537/2007 of Lecture Notes in Computer Science. Springer Berlin/Heidelberg, Ch. Design and Implementation of a System for Environmental Monitoring Sensor Network, 223-228.
21. Lim H., Kung L.-C., Hou J.C., Luo H. Zero-configuration, robust indoor localization: Theory and experimentation. Proceedings on INFOCOM 2006. 25th IEEE International Conference on Computer Communications 2006, 1-12.
22. Mainwaring A., Culler D., Polastre J., Szewczyk R., Anderson J. Wireless sensor networks for habitat monitoring. WSNA'02: Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications 2002, 88-97.
23. Mayer K., Taylor K., Ellis K. Cattle health monitoring using wireless sensor networks. Second IASTED International Conference on Communication and Computer Networks. 2004.
24. Motley, A., Keenan, J., 1988. Personal communication radio coverage in buildings at 900MHz and 1700MHz. Electronics Letter 24.
25. Prasithsangaree P., Krishnamurthy P., Chrysanthis P. On indoor position location with wireless LANs. Personal, Indoor and Mobile Radio Communications, 2002. The 13th IEEE International Symposium on, vol. 2 2002, 720-724.
26. Wireless Sensor Networks: Third European Workshop, EWSN 2006 2006, Birkhäuser, Zurich, Switzerland. K. Römer, Karl, H., F. Mattern (Eds.).
27. Sejerøe T.H., Poulsen N.K., Ravn O. A new evaluation platform for navigation systems. Proceedings of 16th IFAC world Congress, 2005. 2005, URL http://www2.imm.dtu.dk/pubdb/p.php?3342.
28. Seybold J.S. Introduction to RF Propagation 2005, John Wiley & Sons, Hoboken, New Jersey.
29. van der Merwe, R., Wan, E.A., 2006. ReBEL: a matlab toolkit for sequential Bayesian inference in general state space models. URL http://choosh.csee.ogi.edu/rebel.
30. Wahba G. Spline models for observational data. CBMS-NSF Regional Conference Series in Applied Mathematics 1990.
31. West M., Harrison J. Bayesing Forecasting and Dynamic Models 1989, Springer-Verlag New York Inc. second ed.