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Employing computational intelligence to generate more intelligent and energy efficient living spaces

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Abstract

Our living environments are being gradually occupied with an abundant number of digital objects that have networking and computing capabilities. After these devices are plugged into a network, they initially advertise their presence and capabilities in the form of services so that they can be discovered and, if desired, exploited by the user or other networked devices. With the increasing number of these devices attached to the network, the complexity to configure and control them increases, which may lead to major processing and communication overhead. Hence, the devices are no longer expected to just act as primitive stand-alone appliances that only provide the facilities and services to the user they are designed for, but also offer complex services that emerge from unique combinations of devices. This creates the necessity for these devices to be equipped with some sort of intelligence and self-awareness to enable them to be self-configuring and self-programming. However, with this “smart evolution”, the cognitive load to configure and control such spaces becomes immense. One way to relieve this load is by employing artificial intelligence (AI) techniques to create an intelligent “presence” where the system will be able to recognize the users and autonomously program the environment to be energy efficient and responsive to the user’s needs and behaviours. These AI mechanisms should be embedded in the user’s environments and should operate in a non-intrusive manner. This paper will show how computational intelligence (CI), which is an emerging domain of AI, could be employed and embedded in our living spaces to help such environments to be more energy efficient, intelligent, adaptive and convenient to the users.

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Authors and Affiliations

  1. Department of Computing and Electronic Systems, Centre for Computational Intelligence, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK

    Hani Hagras

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  1. Hani Hagras
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Correspondence to Hani Hagras.

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Hani Hagras received the B. Sc. and M. Sc. degrees from the Electrical Engineering Department at Alexandria University, Egypt, and the Ph. D. degree in computer science from the University of Essex, UK. He is a professor of computer science, director of the Centre for Computational Intelligence and leader of the Fuzzy Systems Research Group at the University of Essex.

He has authored more than 100 papers in international journals, conferences, and books. He was the principal investigator and co-investigator of many projects. His research has won numerous prestigious international awards where most recently he was awarded by the IEEE Computational Intelligence Society (CIS), the Outstanding Paper Award in IEEE Transactions on Fuzzy Systems. In addition, he was awarded the Institution of Engineering and Technology (IET) Knowledge Networks Award.

He served as the general co-chair of the IEEE International Conference on Fuzzy systems, London, July 2007. He is also the programme chair for the IET International Conference on Intelligent Environments, Seattle, USA in 2008, and the programme chair for the IET International Conference on Intelligent Environments, Ulm, Germany, September 2007. He was also the programme chair for the IET International Conference on Intelligent Environments, Athens, Greece, in 2006, and acted as the co-chair of the organizing committee for the International Symposium on Evolving Fuzzy Systems, 2006. He served as the programme co-chair for the IASTED International Conference on Robotics and Applications, Hawaii, in 2004. He was also the general chair for the IEE International Workshop on Intelligent Environments, Colchester, in 2005. He serves as an associate editor for the International Journal of Robotics and Automation and a guest editor for various special issues in various international journals.

He is a fellow of IET and a senior member of IEEE. He is the chair of the IEEE CIS International Task Force on Intelligent Agents and co-chair of the IEEE CIS International Task Force on Extensions to Type-1 Fuzzy Sets. He is amember of the IEEE CIS Fuzzy Systems Technical Committee. He is also a member of the IEEE Industrial Electronics Society (IES) Technical Committee of the Building Automation, Control and Management. In addition, he is member of the executive committee of the IET Robotics and Mechatronics Technical and Professional Network. He was invited to serve in the International Medical Informatics Association (IMIA) working group on smart homes and ambient assisted living.

His major research interests are in computational intelligence, notably type-2 fuzzy systems, fuzzy logic, neural networks, genetic algorithms, and evolutionary computation. His research interests also include ambient intelligence, pervasive computing, and intelligent buildings. He is also interested in embedded agents, robotics, and intelligent control.

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Hagras, H. Employing computational intelligence to generate more intelligent and energy efficient living spaces. Int. J. Autom. Comput. 5, 1–9 (2008). https://doi.org/10.1007/s11633-008-0001-7

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  • DOI: https://doi.org/10.1007/s11633-008-0001-7

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