This paper presents an overview of an autonomic home energy management system which is currently being deployed in the first of three phases in homes in order to validate the system and examine effects of autonomic intelligent decision making in regards to energy consumption and behaviour change.
Autonomically managing energy within the home is a formidable challenge, as any solution needs to interoperate with a decidedly heterogeneous network of sensors and appliances, not just in terms of technologies and protocols but also by managing smart as well as “dumb” appliances. Furthermore, as studies have shown that simply providing energy usage feedback to homeowners is inadequate in realising long-term behavioural change, autonomic energy management has the potential to deliver concrete and lasting energy savings without the need for user interventions. However, this necessitates that such interventions be performed in an intelligent and context-aware fashion, all the while taking into account system as well as user constraints and preferences. Thus, this chapter proposes the augmentation of home area networks with autonomic computing capabilities. Such networks seek to support opportunistic decision-making pertaining to the effective energy management within the home by seamlessly integrating a range of off-the-shelf sensor technologies with a software infrastructure for deliberation, activation, and visualisation.
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