Smart Home Energy Management

Abstract

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.

Semantic network management for next‐generation networks

“…To augment these abilities, efforts have been invested in augmenting SIXTH's core benefits with intelligent, agent‐driven, sensor network deployments. Existing work includes running Agent Factory Micro Edition directly on sensor motes to provide in‐network intelligence, using Agent Factory Micro Edition on the middleware gateway to react to sensor data and also in the use of intelligent agents for the autonomic management of the sensor middleware itself . In some cases, it is important for intelligence to be incorporated toward the edges of the network, on or near the nodes themselves.…”