Mundt, Thomas and Wiedenmann, Simeon and Goltz, Johannes and Bauer, Johann and Jung, Maximilian (2011) Detecting intrusive and abnormal behaviour of people in a building through data analysis and anomaly detection in building automation systems. In: NTMS'2019, Gran Canaria, Canary Islands. (Submitted)
Full text not available from this repository.Abstract
Building automation systems provide a lot of data about the current condition of houses. For this purpose, a large number of sensors are usually installed in the building. Such sensors are for example motion detectors and light switches. The sensors detect human actions. They are connected to a network, in our case via a fieldbus network, namely KNX. This makes it possible to evaluate the events at a central location. In this paper we show how data from building automation can be used to detect physical intruders and other ”anomalies” such as unusual human movements. We present how we collected data about the physical location of the sensors and data representing events. We also show what procedures and algorithms we have used to detect anomalies.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | Thomas Mundt |
| Date Deposited: | 14 May 2019 15:05 |
| Last Modified: | 14 May 2019 15:05 |
| URI: | http://eprints.iuk.informatik.uni-rostock.de/id/eprint/706 |
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