Abstract
This book presents significant information and observations about the Ambient Assisted Living (AAL) environment computing technologies that can determine the wellness of an elderly person living independently in their home. There is a world-wide tendency to transform the approach adopted by national healthcare systems to treat elderly people as more and more people choose to live in their own homes; however they still need professional medical supervision. Thus, monitoring important daily activities through the observation of everyday object usages is one way to let medical personnel know about the activities of the elderly, and, if there is a problem, a nurse or doctor can adequately respond in a timely fashion. The elderly people can be monitored continuously in their own home with the set-up of an AAL environment. It is necessary to develop artificially intelligent programs for analysing real-time data coming from heterogeneous smart sensors of the AAL.
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
Khawaja, M.: Population ageing in New Zealand - article. (January 30, 2011), http://www.stats.govt.nz/browse_for_stats/people_and_communities/older_people/pop-ageing-in-nz.aspx (retrieved January 30, 2012)
Alwan, M.: Passive in-home health and wellness monitoring: Overview, value and examples. In: Proceedings of the IEEE Annual International Conference of the Engineering in Medicine and Biology Society, Minneapolis, pp. 4307–4310 (2009)
Armstrong, G.: Alarming Healthcare Costs (August 23, 2009), http://www.stuff.co.nz/national/health/2779009/Addicted-to-healthcare-could-alarming-cost-bankrupt-us (retrieved January 30, 2012)
Ashley-Jones, C.: National Population Projections: 2009 (base)–2061 (October 27, 2009), http://www.stats.govt.nz/browse_for_stats/population/estimates_and_projections/NationalPopulationProjections_HOTP09base-61.aspx (retrieved January 30, 2012)
Beaudin, J.S., Intille, S.S., Morris, M.E.: To Track or Not to Track: User Reactions to Concepts in Longitudinal Health Monitoring. Journal of Medical Internet Research 8(4), 29 (2006)
Demongeot, J., Virone, G., Duchene, F.: Multi-Sensors Acquisition Data Fusion,Knowledge Mining and Alarm Triggering in Health Smart Homes for Elderly People. Comptes Rendus Biologies, 673–682 (2002)
Helal, A., Mann, W., Elzabadani, H., King, J., Kaddourah, Y., Jansen, E.: Gator Tech Smart House: A Programmable Pervasive Space. IEEE Computer Magazine, 64–74 (2005)
Intille, S.S., Larson, K., Tapia, E.M., Beaudin, J.S., Kaushik, P., Nawyn, J., Rockinson, R.: Using a live-in laboratory for ubiquitous computing research. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds.) PERVASIVE 2006. LNCS, vol. 3968, pp. 349–365. Springer, Heidelberg (2006)
Kailas, A.: A Generic Conceptual Model Linking Wellness, Health Lifestyles and User Assistance. In: Proceedings of the 13th IEEE International Confernce on e-Health Networking Applications and Services (Healthcom), Columbia, pp. 266–269 (2011)
Kailas, A., Chong, C.-C., Watanabe, F.: A Simple Iterative Algorithm for Wellness Applications. In: Proceedings of the IEEE Wireless Communications and Networking Conference, Sydney, pp. 1–6 (2010)
National Institute on Aging, National Institutes of Health, World health Organization. Global Health and Aging (October 2011), http://www.nia.nih.gov/sites/default/files/global_health_and_aging.pdf (retrieved January 30, 2012)
Patel, S.N., Kientz, J.A., Jones, B., Price, E., Mynatt, E.D., Abowd, G.D.: An Overview of the Aware Home Research Initiative at the Georgia Institute of Technology. In: Proceedings of the International Future Design Conference on Global Innovations in Macro-and-Micro-Environments for the Future, Seoul, pp. 169–181 (2007)
Pilkington, E.: Population of Older people set to surpass number of children, report finds (July 20, 2009), http://www.theguardian.com/world/2009/jul/20/census-population-ageing-global (retrieved January 30, 2012)
Soomlek, C., Benedicenti, L.: Operational Wellness Model: A Wellness Model Designed for an Agent-Based Wellness Visualization System. In: Proceedings of the Second International Conference on eHealth, Telemedicine and Social Medicine, St.Martin, pp. 45–50 (2010)
Suryadevara, N.K., Mukhopadhyay, S.C.: Determination of Wellness of an Elderly in an Ambient Assisted Living Environment. IEEE Intelligent Systems 29(3), 30–37
Suryadevara, N.K., Mukhopadhyay, S.C., Wang, R., Rayudu, R.K.: Forecasting the behavior of an elderly using wireless sensors data in a smart home. Elsevier: Engineering Applications of Artificial Intelligence 26(10), 2641–2652
Suryadevara, N.K., Mukhopadhyay, S.C.: Wireless Sensor Network Based Home Monitoring System for Wellness Determination of Elderly. IEEE Sensors Journal 12(06), 1965–1972
Suryadevara, N.K., Gaddam, A., Rayudu, R.K., Mukhopadhyay, S.C.: Wireless Sensors Network Based Safe Home to Care Elderly People: Behaviour Detection. Elsevier: Sensors and Actuators: A Physical 186, 277–283 (2012)
Suryadevara, N.K., Mukhopadhyay, S.C., Kelly, S.D.T., Gill, S.P.S.: WSN-Based Smart Sensors and Actuator for Power Management in Intelligent Buildings. IEEE Transactions on Mechatronics (Early Access Article), doi:10.1109/TMECH.2014.2301716
Kelly, S.D.T., Suryadevara, N.K., Mukhopadhyay, S.C.: Towards the Implementation of IoT for Environmental Condition Monitoring in Homes. IEEE Sensors Journal 13(10), 3846–3853
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Suryadevara, N.K., Mukhopadhyay, S.C. (2015). Introduction. In: Smart Homes. Smart Sensors, Measurement and Instrumentation, vol 14. Springer, Cham. https://doi.org/10.1007/978-3-319-13557-1_1
Download citation
DOI: https://doi.org/10.1007/978-3-319-13557-1_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13556-4
Online ISBN: 978-3-319-13557-1
eBook Packages: EngineeringEngineering (R0)