Abstract
Emerging technologies in building automation have the potential to increase the quality and cost effectiveness of services in the building industry. However, insufficient range of collected data and models of the physical and behavioural aspects of the facilities limit the capabilities of building automation systems. We describe a project for improving building services by collecting comprehensive data from variable sources and generating high-resolution models of buildings. In this context, location sensing is critical not only for data collection, but also for constructing models of buildings as dynamic environments. We first examine a range of existing location sensing technologies from the building automation perspective. We then outline the implementation of a specific location sensing system together with respective test results.
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References
Mahdavi, A.: Self-organizing building models for sentient buildings (to be published)
Mahdavi, A.: Computational building models: Theme and four variations (Keynote). In: Augenbroe, G., Hensen, J. (eds.) Proceedings of the Eight International IBPSA Conference (Eindhoven, Netherlands), vol. 1, pp. 3–18 (2003) ISBN 9038615663
Mahdavi, A.: Aspects of self-aware buildings. International Journal of Design Sciences and Technology. Europia: Paris, France 9(1), 35–52 (2001) ISSN 1630 - 7267
Mahdavi, A.: Simulation-based control of building systems operation. Building and Environment 36(6), 789–796 (2001) ISSN: 0360-1323
Mahdavi, A., Suter, G.: Sensorgestützte Modelle für verbesserte Gebäudeservices. FWF proposal (2002)
Polhemus, Inc., http://www.polhemus.com/
Ekahau, Inc., http://www.ekahau.com/
Hightower, J., Borriello, G., Want, R.: SpotON: An indoor 3D location sensing technology based on RF signal strength. UW CSE Technical Report 2000-02-02 (February 2000)
Ni, L.M., Liu, Y., Lau, Y.C., Patil, A.P.: LANDMARC: indoor location sensing using active RFID. In: Proceedings of the 2003 IEEE Annual Conference on Pervasive Computing and Communications (PerCom 2003), Dallas, Texas (March 2003)
Ryburg, J.: New churn rates: people, walls, and furniture in restructuring companies. Facility Performance Group, Inc. (1996)
Werb, J., Lanzl, C.: Designing a positioning system for finding things and people indoors. IEEE Spectrum 5(9), 71–78 (1998)
WhereNet, http://www.wherenet.com/
Ward, A.: Sensor-driven Computing. PhD dissertation, University of Cambridge (1998)
Priyantha, N.B., Chakraborty, A., Balakrishnan, H.: The Cricket location-support system. In: Proc. of the Sixth Annual ACM International Conference on Mobile Computing and Networking (MOBICOM) (August 2000)
Sonitor Technologies AS, http://www.sonitor.com/
Krumm, J., Harris, S., Meyers, B., et al.: Multi-camera multi-person tracking for EasyLiving. In: Proceedings of Third IEEE International Workshop on Visual Surveillance, Dublin, Ireland (July 1, 2000)
Geodata GmbH, http://www.geodata.at/
Arc Second, Inc., http://www.constellation3di.com/
Mitsubishi Electric Research Laboratories, Detecting Visual Tags, http://www.merl.com/projects/visual-tags/
López de Ipiña, D.: Visual Sensing and Middleware Support for Sentient Computing. PhD dissertation, University of Cambridge (2002)
López de Ipiña, D., Mendonca, P.S., Hopper, A.: Visual Sensing and Middleware Support for Sentient Computing. Personal and Ubiquitous Computing 6(3), 206–219 (2002) ISSN: 1617- 4909
Microsoft Corp., COM Technologies, http://www.microsoft.com/com/
Battiato, S., Castorina, A., Guarnera, M., Vivirito, P.: An Adaptive Global Enhancement Pipeline for Low Cost Imaging Sensors. In: IEEE International Conference on Consumer Electronics, Los Angeles, USA. pp. 398–399 (June 2003)
Battiato, S., Gallo, G., Stanco, F.: A New Edge-Adaptive Algorithm for Zooming of Digital Images. IASTED Signal Processing and Communications, Marbella, Spain. September 2000, pp. 144–149, ISBN: 0-88986-302-4
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Icoglu, O., Brunner, K.A., Mahdavi, A., Suter, G. (2004). A Distributed Location Sensing Platform for Dynamic Building Models. In: Markopoulos, P., Eggen, B., Aarts, E., Crowley, J.L. (eds) Ambient Intelligence. EUSAI 2004. Lecture Notes in Computer Science, vol 3295. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30473-9_13
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DOI: https://doi.org/10.1007/978-3-540-30473-9_13
Publisher Name: Springer, Berlin, Heidelberg
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