Abstract
In this paper we present a proof-of-concept practical architecture of a system for tracking older adults living alone in an ambient intelligence environment by using multi-modal sensory information, such as audio and video input from Kinect and Arduino devices. This AAL (Ambient Assisted Living) system collects data into a Database of Trajectories, used to automatically generate training examples. We then show how the Database of Trajectories can be used in conjunction with a set of well-trained algorithms to alert remote caregivers in case of an unfortunate event, such as the elder falling down - one of the leading causes of injury and death.
This work was supported by projects ERRIC - Empowering Romanian Research on Intelligent Information Technologies/FP7-REGPOT-2010-1, ID: 264207 and “DocInvest” - POSDRU/107/1.5/S/76813.
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
Catalogue of projects 2012. Ambient Assisted Living Joint Programme
Universal Serial Bus Specification Revision 2.0 (2011) (retrieved September 8, 2012)
Berger, K., Ruhl, K., Brümmer, C., Schröder, Y., Scholz, A., Magnor, M.: Markerless motion capture using multiple color-depth sensors. In: Proc. Vision, Modeling and Visualization (VMV), vol. 2011, p. 3 (2011)
Henry, P., Krainin, M., Herbst, E., Ren, X., Fox, D.: Rgb-d mapping: Using kinect-style depth cameras for dense 3d modeling of indoor environments. The International Journal of Robotics Research 31(5), 647–663 (2012)
Bloom, D.E., Fried, L.P., Hogan, P., Kalache, A., Beard, J.R., Biggs, S., Jay Olshansky, S. (eds.): Global Population Ageing: Peril or Promise. World Economic Forum, Geneva (2011)
Kannus, P., Parkkari, J., Niemi, S., Palvanen, M.: Fall-induced deaths among elderly people. Journal Information 95(3) (2005)
Kushwaha, M., Oh, S., Amundson, I., Koutsoukos, X., Ledeczi, A.: Target tracking in heterogeneous sensor networks using audio and video sensor fusion. In: IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2008, pp. 14–19. IEEE (2008)
Logan, B., Healey, J.: Sensors to detect the activities of daily living. In: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2006, pp. 5362–5365. IEEE (2006)
Lyons, P., Cong, A.T., Steinhauer, H.J., Marsland, S., Dietrich, J., Guesgen, H.W.: Exploring the responsibilities of single-inhabitant smart homes with use cases. Journal of Ambient Intelligence and Smart Environments 2(3), 211–232 (2010)
Piccardi, M.: Background subtraction techniques: a review. In: 2004 IEEE International Conference on Systems, Man and Cybernetics, vol. 4, pp. 3099–3104. IEEE (2004)
Singla, G., Cook, D., Schmitter, M.: Edgecombe. Incorporating temporal reasoning into activity recognition for smart home residents. In: Proceedings of the AAAI Workshop on Spatial and Temporal Reasoning, pp. 53–61 (2008)
Kaushik, P., Intille, S.S., Rockinson, R.: Deploying context-aware health technology at home: Human-centric challenges. In: Human-Centric Interfaces for Ambient Intelligence, pp. 479–503. Elsevier (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Ismail, AA., Florea, AM. (2013). Multimodal Indoor Tracking of a Single Elder in an AAL Environment. In: van Berlo, A., Hallenborg, K., Rodríguez, J., Tapia, D., Novais, P. (eds) Ambient Intelligence - Software and Applications. Advances in Intelligent Systems and Computing, vol 219. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00566-9_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-00566-9_18
Publisher Name: Springer, Heidelberg
Print ISBN: 978-3-319-00565-2
Online ISBN: 978-3-319-00566-9
eBook Packages: EngineeringEngineering (R0)