Reconstruction of Everyday Life Behaviour based on Noisy Sensor Data

Max Schröder, Sebastian Bader, Frank Krüger, Thomas Kirste

Abstract

The reconstruction of human activities is an important prerequisite to provide assistance. In this paper, we present an activity and plan recognition approach which is based on causal models of human activities. We show, that it is possible to estimate current activities, the underlying goal of the user, and context information about the state of the environment from noisy sensor data. Therefore we use real world data obtained from a smart home system while observing unrestricted activities of daily living in an inhabited flat. We evaluate the accuracy of the recognition for simulated data of different granularity and data obtained from the smart home system. We furthermore show that performance measures solely based on action sequences are not sufficient to evaluate a recognition system.

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Paper Citation


in Harvard Style

Schröder M., Bader S., Krüger F. and Kirste T. (2016). Reconstruction of Everyday Life Behaviour based on Noisy Sensor Data . In Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-172-4, pages 430-437. DOI: 10.5220/0005756804300437


in Bibtex Style

@conference{icaart16,
author={Max Schröder and Sebastian Bader and Frank Krüger and Thomas Kirste},
title={Reconstruction of Everyday Life Behaviour based on Noisy Sensor Data},
booktitle={Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2016},
pages={430-437},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005756804300437},
isbn={978-989-758-172-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Reconstruction of Everyday Life Behaviour based on Noisy Sensor Data
SN - 978-989-758-172-4
AU - Schröder M.
AU - Bader S.
AU - Krüger F.
AU - Kirste T.
PY - 2016
SP - 430
EP - 437
DO - 10.5220/0005756804300437