The increase of energy efficiency and reduction of greenhouse gas emissions have become important targets of EU initiatives (European Commission 2014). Emissions from personal vehicles are a key cause of worldwide greenhouse gas emissions with 90% of personal transport emissions being caused by private vehicles (Barkenbus 2010). Energy efficient driving techniques, or eco-driving, can realize energy savings up to 20% (Stillwater et al. 2012). Combined with behavioral approaches, which are increasingly being used by governments (Cabinet Office 2012), these techniques represent a promising way to increase energy efficiency in the transport sector. Yet, practical solutions which are based on scientific findings are scarce. Since mobile apps are versatile in their functionality, characterized by a short time to market and low costs, they can represent a solution. The research question therefore is: How can a mobile application contribute to energy-efficient driving?
The water conservation campaigns in residential households are hindered by the poor understanding of residents of how much water they use. For the better designed interventions new tools are necessary to educate the consumers on the water usage of different consumption events. In this paper we use the fine grained (0.5 Hz) water consumption data that was collected non- intrusively in a household over the period of 21 days to develop such tools. We examine the collected data and disaggregate the consumption events into three different categories: short events (e.g., toilet flush), long regular events (e.g., washing machine) and long irregular events (e.g., showers). To achieve this, we use clustering methods, based on level set trees, to identify groups of events that are similar to each other.
In the promotion of sustainable consumer behaviour, it is important to establish a mental relation be- tween one’s behaviour and its environmental impact. High hopes rest on timely feedback on personal energy consumption in order to create this link. Great efforts are being put into the development of information systems to achieve this, and smart meters are being deployed as an enabling technology worldwide. Recent smart metering trials, which provide feedback on aggregate household electricity consumption, report moderate savings of 2-5%. There is, however, a vivid controversy about consumer interest and continuous use of these technologies in the long run. This uncertainty introduces substantial risk to the deployment of these technologies, as the persistence of savings is crucial for the cost-benefit analyses and scalability of these programs. This paper investigates the long-term stability of the behav- iour change induced by a real-time feedback technology. Our initial study found average energy savings of 22% for the target behaviour. In this study, we analyse 17,612 data points collected in a one-year follow-up field study. The results suggest that the effects of behaviour-specific feedback on energy con- sumption do not exhibit a significant decay, indicating that this kind of technology successfully induces persistent behaviour change.