ETH Zurich :
Computer Science :
Pervasive Computing :
Distributed Systems :
Student Projects :
Opportunistic Sensing for Domestic Smart Energy Systems (M)
Abstract—With the growing number of smart devices in households, it is possible to determine the occupants' activity by accessing device sensors and status information. This can help to reduce power consumption by automatically turning off unused appliances. A Heating, Ventilation and Air Conditioning (HVAC) system that only heats or cools if a person is home, for instance, can save lots of energy. Such smart energy systems require additional information such as occupancy, which is provided by a sensing infrastructure. The goal of this thesis is to design and evaluate an opportunistic sensing infrastructure that controls an exemplary automated heating system.
Studies by the Swiss Federal Institute for Energy have shown that in domestic houses up to 70% of the total power consumption is caused by the heating process. By turning off the heating when nobody is home, the power consumption could be reduced by 30%. Most of today’s heating systems are time-controlled. Residents, however, almost never adjust the times according to their daily routine, because it is cumbersome or they do not know it is possible. Thus, a smart heating system has still potential to save energy, if it learns the daily schedule and adapts the timer accordingly.
Our designated smart heating system consists of remote-controlled thermostats, different types of sensors, and software that processes the information and operates the thermostats. All components are connected wirelessly with the IPv6 over Low power Wireless Personal Area Networks (6LoWPAN) protocol. To have standardized access method for all devices, their interfaces are RESTful and accessible through the Constrained Application Protocol (CoAP).
The system is supposed to leverage all available sensors in the household that can provide the actual temperature and detect occupancy. For the latter, there are different approaches such as using motion detectors in different rooms, microphones to detect noise, or measuring air pressure to infer movement, but also checking if the mobile phone is associated to the home Wi-Fi and measuring the activity of certain appliances through their power consumption or accessible status information. These approaches differ, however, in accuracy. Hence, the system must learn which sensor reading is suited in which context and weigh them accordingly.
As a first part of thesis, the student shall design a sensing infrastructure that is reusable by different applications, one of them being the smart heating system. Ideally, concurrent applications are supported by harmonized sensor sampling rates and CoAP’s push notifications. The infrastructure design also has to specify the interface between the infrastructure and the applications. The cut between infrastructure and application logic shall consider In particular reliability and safety requirements.
The second part is to extend a digital thermostat to realize the smart heating system. A basic ver-sion providing remote control is available. The student shall improve its scheduling to suffice multiple incoming requests and provide means to use its adjusting knob for intuitive user feed-back.
In a last part, the student shall provide a proof-of-concept implementation of the smart heating system, evaluate the performance and reliability of the sensing infrastructure, and discuss the accuracy of different sensors.
Student/Bearbeitet von: Nico Eigenmann
Contact/Ansprechpartner: Matthias Kovatsch