Abstract
Situation awareness is a key feature of pervasive computing and requires external knowledge to interpret data. Ontology-based reasoning approaches allow for the reuse of predefined knowledge, but do not provide the best reasoning capabilities. To overcome this problem, a hybrid model for situation awareness is developed and presented in this paper, which integrates the Situation Theory Ontology into Context Space Theory for inference. Furthermore, in an effort to rely as much as possible on open IoT messaging standards, a domain-independent framework using the O-MI/O-DF standards for sensor data acquisition is developed. This framework is applied to a smart neighborhood use case to reduce food waste at the consumption stage.
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Notes
- 1.
The relevance belongs to context attributes, but an attribute can have a different weight for different facts about situations.
- 2.
Yummly Recipe API: https://developer.yummly.com/.
- 3.
Smart Locks slock.it: https://slock.it.
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Acknowledgments
Authors acknowledge support from EMM PERCCOM, IoT EPI bIoTope Project, which is co-funded by the European Commission under H2020-ICT-2015 program, Grant Agreement 688203, as well as financial support from Ministry of Science & Education of Russian Federation, Grant RFMEFI58716X0031.
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Kolbe, N., Zaslavsky, A., Kubler, S., Robert, J. (2016). Reasoning over Knowledge-Based Generation of Situations in Context Spaces to Reduce Food Waste. In: Galinina, O., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. ruSMART NEW2AN 2016 2016. Lecture Notes in Computer Science(), vol 9870. Springer, Cham. https://doi.org/10.1007/978-3-319-46301-8_9
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