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Artificial Neural Networks in Smart Homes

  • Chapter
Designing Smart Homes

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4008))

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Abstract

Many wonderful technological developments in recent years have opened up the possibility of using smart or intelligent homes for a number of important applications. Typical applications range from overall lifestyle improvement to helping people with special needs such as the elderly and the disabled to improve their independence, safety and security at home. Research in the area has looked into ways of making the home environment automatic and automated devices have been designed to help the disabled people. Also, possibilities of automated health monitoring systems and usage of automatic controlled devices to replace caregiver and housekeeper have received significant attention. Most of the models require acquisition of useful information from the environment, identification of the significant features and finally usage of some sort of machine learning techniques for decision making and planning for the next action to be undertaken. This chapter specifically focuses on neural networks applications in building a smart home environment.

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Author information

Authors and Affiliations

  1. Centre for Ageing, Rehabilitation, Exercise & Sport, Victoria University, Melbourne, VIC 8001, Australia

    Rezaul Begg

  2. Department of Computer Science & Software Engineering, The University of Melbourne, VIC 3010, Australia

    Rafiul Hassan

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  1. Rezaul Begg
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  2. Rafiul Hassan
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Editors and Affiliations

  1. School of Computing and Mathematics, University of Ulster, UK

    Juan Carlos Augusto

  2. School of Computing and Mathematics and Computer Science Research Institute, University of Ulster, Northern Ireland

    Chris D. Nugent

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Begg, R., Hassan, R. (2006). Artificial Neural Networks in Smart Homes. In: Augusto, J.C., Nugent, C.D. (eds) Designing Smart Homes. Lecture Notes in Computer Science(), vol 4008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11788485_9

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  • DOI: https://doi.org/10.1007/11788485_9

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