Background and Introduction
Background work
Background work
- Human occupancy detection is the core part of building automation systems. For example, people rely on estimated occupancy information to control temperature, light and air flow within buildings.
- Human activities detection is an enhanced version of human occupancy detection, which allows automation system to adopt different power saving strategies based on specific human activities. For example, if the automation system detects the occupants to be using entertainment devices in the living room, it can turn down the lights in bedroom and kitchen.
- Current building automation systems use sensing devices/network logins/GPS trackers to monitor occupancy which may result in extra cost and installation complexity, thus a demand for comprehensive and quantitatively approaches to detect household occupancy based on off-the-shelf electricity meters is highly valued. Therefore, the detection/prediction of human occupancy or human activities using electricity meters data can help save energy not only from the household appliances but also the monitoring system for occupancy detection.
Introduction of our work
Introduction of our work
- In our project, we discuss and quantitatively evaluate the capability of digital electricity meters to be used for human occupancy/human activities prediction in various models based on ECO Data-set house#2. Given the fact that digital meters are widely installed and does not impose additional costs on the residents, there are huge opportunities to implement it on real automation systems.