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Multi-Modal Context-Aware reasoNer (CAN) at the Edge of IoT
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2017 (English)In: The 8th International Conference on Ambient Systems, Networks and Technologies, 2017Conference paper, (Refereed)
Abstract [en]

Future Internet is expected to be driven by prevalence of the Internet of Things (IoT). This prevalence of IoT promises to impact every aspect of human life in the foreseeable future where computing paradigm would witness huge influx of IoT data. Context is gaining growing attention to make sense of the data and it is envisaged that context-aware computing would act as an indispensable enabler for IoT. Contextualizing the collected IoT data enables to reap value from the data and to harvest the knowledge. Reasoning the contextualized data, that is, context information is imperative to the vision of harvesting knowledge. Edge computing is also expected to play a vital role in IoT to reduce dependency on cloud based solution, to achieve faster response, and to provide intelligence close to the IoT things. The combination of context-awareness and edge solution would be inseparable in the future IoT. Furthermore, IoT vision comprises of different IoT applications controlled by a capable controller at the edge, an edge controller necessitates to counter the challenge of providing knowledge for each of the IoT applications. Therefore, such a controller requires to offer different context-aware reasoning to alleviate the intelligence-of-things. In view of this, this paper proposes a multi-modal context-aware reasoner the aim of which is to provide knowledge at the edge for each IoT application. The context-aware reasoning has been verified with rules-based and Bayesian reasoning for three IoT applications and initial results suggest that it is promising to realize such multimodal reasoning at the edge with low latency.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Internet of Things (IoT); context-aware; edge computing; multimodal; reasoning
National Category
Computer Science
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-144910DOI: https://doi.org/10.1016/j.procs.2017.05.360OAI: oai:DiVA.org:su-144910DiVA: diva2:1117557
Available from: 2017-06-29 Created: 2017-06-29

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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