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Employing computational intelligence to generate more intelligent and energy efficient living spaces
Authors:Hani Hagras
Affiliation:(1) Department of Computing and Electronic Systems, Centre for Computational Intelligence, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK
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.
Keywords:Computational intelligence(CI)  fuzzy systems  neural networks(NNs)  genetic algorithms(GAs)  intelligent buildings  energy efficiency  
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