David Lillis: Smart Home Energy Management

Smart Home Energy Management

David Lillis, Tadhg O'Sullivan, Thomas Holz, Conor Muldoon, Michael J. O'Grady and Gregory M. P. O'Hare

In K. Curran, editor, Recent Advances in Ambient Intelligent and Context-Aware Computing, pages 155--168. IGI Global, 2015.


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.