ETH Zurich :
Computer Science :
Pervasive Computing :
Distributed Systems :
Student Projects :
Automated Energy Consulting for Private Households by Analyzing their Baseload Electricity Consumption (M)
Information and Communication technology can significantly contribute to a more efficient energy use in private households. Smart Meters, for instance, play a huge role as they measure electricity consumption at a fine-grained interval and report it through a communication interface. Processing this data provides valuable context information and thus forms the basis for novel services and applications. These services can be classified into base services, which derive context information directly from smart meter data, and consumer services, which employ base services through a well-defined interface and directly address the end user. Altogether, such a service infrastructure augments raw sensor data and can be employed to provide automated energy consulting to household inhabitants in order to motivate a more thrifty use of electricity.
The goal of this thesis is to design and develop services on top of smart meter data to enable automated energy consulting. In particular the thesis explores a base service called baseload detection, which aims at separating electricity consumption caused by (1) standby or networked appliances (i.e. "always-on appliances", (2) cooling devices, and (3) from anything else. In the context of the thesis an algorithm should be designed, implemented, and evaluated based on real world consumption data. On top of this base service, three consumer services should be implemented to notify household inhabitants about their standby consumption as well as energy waste.
Student/Bearbeitet von: Dominique Im Obersteg
Contact/Ansprechpartner: Christian Beckel