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Semantic event fusion of computer vision and ambient sensor data for activity recognition to support dementia care

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Abstract

Although many Ambient Intelligence frameworks either address heterogeneous ambient sensing or computer vision techniques, very limited work integrates both techniques in the scope of activity recognition in pervasive environments. This paper presents such a framework that integrates both a computer vision component and heterogeneous sensors with unanimous semantic representation and interpretation, while it also addresses challenges for realistic applications, such as fast, efficient image analysis and ontology-based temporal interpretation models. The framework is validated through an application in clinical dementia assessment yielding positive results and fruitful conclusions for the proposed semantic fusion of vision and sensor observations.

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Notes

  1. Sennheiser FreePORT—http://en-de.sennheiser.com/.

  2. Philips DTI-2 non-commercial wristwatch kindly provided by Philips Research NL—http://www.philips.nl/.

  3. Circle, Cirlce + and Stealth products by Plugwise.nl—https://www.plugwise.nl/.

  4. The ZigBee Alliance—http://www.zigbee.org/.

  5. Tags, PIR KumoSensor, Reed KumoSensor of the Wireless Sensor Tag System—http://wirelesstag.net/.

  6. http://www.loa.istc.cnr.it/ontologies/DUL.owl.

  7. http://www.w3.org/TR/owl-time/.

  8. The native OWL semantics do not support temporal reasoning. However, it can be simulated using custom property assertions, as described in (Riboni et al. 2011).

  9. The ontologies, sample dataset and implementation can be found online at: http://www.demcare.eu/results/ontologies.

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Authors and Affiliations

  1. Center for Research and Technologies, Information Technologies Institute, Hellas, Greece

    Thanos G. Stavropoulos, Georgios Meditskos, Stelios Andreadis, Konstantinos Avgerinakis, Katerina Adam & Ioannis Kompatsiaris

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  1. Thanos G. Stavropoulos
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  2. Georgios Meditskos
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Correspondence to Thanos G. Stavropoulos.

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Stavropoulos, T.G., Meditskos, G., Andreadis, S. et al. Semantic event fusion of computer vision and ambient sensor data for activity recognition to support dementia care. J Ambient Intell Human Comput 11, 3057–3072 (2020). https://doi.org/10.1007/s12652-016-0437-5

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