Sources, Models and Use of Location: A Special Sort of Context

Part of the Undergraduate Topics in Computer Science book series (UTICS)


Location, as a form of context and as a specialised concern, has been a central consideration of pervasive computing from the start. Location, as a way of indexing data and through distribution of computation, has an even more venerable history in computer science. In this chapter we examine key issues in sensing and using location data, including: coordinate models, human descriptions and relations between locations; sensing of location, including GPS, cellular systems, trilateration and tags; and the storage and indexing of location data with R-Trees.


Global Position System Geographic Information System Locate Object Ubiquitous Computing Global Position System Receiver 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Becker, C., Dürr, F.: On location models for ubiquitous computing. Pers. Ubiquitous Comput. 9(1), 20–31 (2005) CrossRefGoogle Scholar
  2. 2.
    Beckmann, N., Kriegel, H.-P., Schneider, R., Seeger, B.: The R-Tree: an efficient and robust access method for points and rectangles. In: Garcia-Molina, H., Jagadish, H.V. (eds.) SIGMOD Conference, pp. 322–331. ACM Press, New York (1990) Google Scholar
  3. 3.
    Beigl, M., Zimmer, T., Decker, C.: A location model for communicating and processing of context. Pers. Ubiquitous Comput. 6(5/6), 341–357 (2002) CrossRefGoogle Scholar
  4. 4.
    Bulusu, N., Heidemann, J., Estrin, D.: Gps-less low-cost outdoor localization for very small devices. IEEE Pers. Commun. 7(5), 28–34 (2000) [see also IEEE Wireless Communications] CrossRefGoogle Scholar
  5. 5.
    Egenhofer, M.J., Herring, J.R.: A mathematical framework for the definition of topological relationships. In: Brassel, K., Kishimoto, H. (eds.) 4th International Symposium on Spatial Data Handling, pp. 803–813. International Geographical Union, Zurich (1990) Google Scholar
  6. 6.
    Fox, D., Hightower, J., Liao, L., Schulz, D., Borriello, G.: Bayesian filtering for location estimation. IEEE Pervasive Comput. 2(3), 24–33 (2003) CrossRefGoogle Scholar
  7. 7.
    Guttman, A.: R-trees: a dynamic index structure for spatial searching. In: Yormark, B. (ed.) SIGMOD Conference, pp. 47–57. ACM Press, New York (1984) Google Scholar
  8. 8.
    Hightower, J., Borriello, G.: Location systems for ubiquitous computing. IEEE Comput. 34(8), 57–66 (2001) CrossRefGoogle Scholar
  9. 9.
    Hightower, J., Borriello, G.: Particle filters for location estimation in ubiquitous computing: a case study. In: UbiComp 2004: Ubiquitous Computing, pp. 88–106. Springer, Berlin (2004) CrossRefGoogle Scholar
  10. 10.
    Hightower, J., Brumitt, B., Borriello, G.: The location stack: a layered model for location in ubiquitous computing. In: WMCSA, p. 22. IEEE Computer Society, Washington (2002) Google Scholar
  11. 11.
    Jiang, C., Steenkiste, P.: A hybrid location model with a computable location identifier for ubiquitous computing. In: Borriello, G., Holmquist, L.E. (eds.) Ubicomp. Lecture Notes in Computer Science, vol. 2498, pp. 246–263. Springer, Berlin (2002) Google Scholar
  12. 12.
    Kindberg, T., Pederson, T., Sukthankar, R.: Guest editors’ introduction: labeling the world. IEEE Pervasive Comput. 9(2), 8–10 (2010) CrossRefGoogle Scholar
  13. 13.
    LaMarca, A., Chawathe, Y., Consolvo, S., Hightower, J., Smith, I.E., Scott, J., Sohn, T., Howard, J., Hughes, J., Potter, F., Tabert, J., Powledge, P., Borriello, G., Schilit, B.N.: Place lab: device positioning using radio beacons in the wild. In: Gellersen, H.-W., Want, R., Schmidt, A. (eds.) Pervasive. Lecture Notes in Computer Science, vol. 3468, pp. 116–133. Springer, Berlin (2005) Google Scholar
  14. 14.
    Leonhardt, U., Magee, J.: Towards a general location service for mobile environments. In: Third IEEE Workshop on Services in Distributed and Networked Environments, pp. 43–50. IEEE, New York (1996) CrossRefGoogle Scholar
  15. 15.
    Leonhardt, U., Magee, J.: Multi-sensor location tracking. In: 4th ACM/IEEE Conference on Mobile Computing and Networks (MobiCom), pp. 203–214. ACM, New York (1998) CrossRefGoogle Scholar
  16. 16.
    O’Neill, E., Kostakos, V., Kindberg, T., Fatah gen. Schieck, A., Penn, A., Fraser, D.S., Jones, T.: Instrumenting the city: developing methods for observing and understanding the digital cityscape. In: Dourish, P., Friday, A. (eds.) Ubicomp. Lecture Notes in Computer Science, vol. 4206, pp. 315–332. Springer, Berlin (2006) Google Scholar
  17. 17.
    Prakash, R., Baldoni, R.: Causality and the spatial-temporal ordering in mobile systems. Mob. Netw. Appl. 9(5), 507–516 (2004) CrossRefGoogle Scholar
  18. 18.
    Ranganathan, A., Campbell, R.H.: A middleware for context-aware agents in ubiquitous computing environments. In: Middleware, pp. 143–161 (2003) Google Scholar
  19. 19.
    Shekhar, S., Chawla, S.: Spatial Databases—A Tour. Pearson Education, Prentice Hall, Upper Saddle River (2003) Google Scholar
  20. 20.
    Survey, O.: The ellipsoid and the Transverse Mercator projection. Technical Report Geodetic information paper no. 1, version 2.2, Ordnance Survey (1998) Google Scholar
  21. 21.
    Want, R., Hopper, A., Falcao, V., Gibbons, J.: The active badge location system. ACM Trans. Inf. Syst. 10(1), 91–102 (1992) CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.University of SussexBrightonUnited Kingdom

Personalised recommendations