Abstract
The increasing elderly population has increased interest in the Ambient Assisted Living systems. This article presents a system for monitoring the disabled or elderly developed from an existing surveillance system. The modularity and adaptability characteristics of the system allow an easy adaptation for a different purpose. The proposed system uses a network of sensors capable of motion detection that includes fall warning, identification of persons and a configurable control system which allows its use in different scenarios.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
The Ambient Assited Living (AAL) Joint Programme, http://www.aal-europe.eu/
Kleinberger, T., Becker, M., Ras, E., Holzinger, A., Müller, P.: Ambient Intelligence in Assisted Living: Enable Elderly People to Handle Future Interfaces. In: Stephanidis, C. (ed.) UAHCI 2007 (Part II). LNCS, vol. 4555, pp. 103–112. Springer, Heidelberg (2007)
de Jesus, J.D., Calvo, J.J.V., Fuente, A.I.: Surveillance system based on data fusion from image and acoustic array sensors. IEEE, Aerospace and Electronic Systems Magazine 15(2), 9–16 (2000)
Hou, J.C., et al.: PAS: A Wireless-Enabled, Sensor-Integrated Personal Assistance System for Independent and Assisted Living. In: 2007 Joint Workshop on High Confidence Medical Devices, Software, and Systems and Medical Device Plug-and-Play Interoperability pp.64–75 (2007)
Rao, S., Cook, D.J.: Predicting Inhabitant Actions Using Action and Task Models with Application to Smart Homes. International Journal of Artificial Intelligence Tools 13(1), 81–100 (2004)
Strobel, N., Spors, S., Rabenstein, R.: Joint audio-video signal processing for object localization and tracking. In: Brandstein, M.S., Ward, D.B. (eds.) Microphone Arrays: Signal Processing Techniques and Applications, pp. 203–225. Springer, Heidelberg (2001)
Van Veen, B., Buckley, K.: Beamforming: A versatile approach to spatial filtering. IEEE ASSP Magazine, 4–24 (1988)
Noury, N., et al.: Fall detection - Principles and Methods., Engineering in Medicine and Biology Society. In: 29th Annual International Conference of the IEEE, pp. 1663–1666 (22-26, 2007)
Cucchiara, R., Grana, C., Piccardi, M., Prati, A.: Detecting moving objects, ghosts, and shadows in video streams. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(10), 1337–1342 (2003)
Miaou, S.-G., Sung, P.H., Huang, C.Y.: A Customized Human Fall Detection System Using Omni-Camera Images and Personal Information. In: 1st Transdisciplinary Conference on Distributed Diagnosis and Home Healthcare, D2H2, pp. 39–42 (2006)
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
Villacorta, J.J., del Val, L., Jimenez, M.I., Izquierdo, A. (2010). Security System Technologies Applied to Ambient Assisted Living. In: Lytras, M.D., Ordonez De Pablos, P., Ziderman, A., Roulstone, A., Maurer, H., Imber, J.B. (eds) Knowledge Management, Information Systems, E-Learning, and Sustainability Research. WSKS 2010. Communications in Computer and Information Science, vol 111. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16318-0_46
Download citation
DOI: https://doi.org/10.1007/978-3-642-16318-0_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16317-3
Online ISBN: 978-3-642-16318-0
eBook Packages: Computer ScienceComputer Science (R0)