Abstract
Fog Computing has emerged as a new paradigm where the processing of data and collaborative services are embedded within smart objects, which cooperate between them to reach common goals. In this work, a rule-based Inference Engine based on fuzzy linguistic approach is integrated in the smart devices. The linguistic representation of local and remote sensors is defined by protoforms, which configure the antecedents of the rules in the Inference Engine. A case study where two inhabitants with a wearable device conduct activities in a Smart Lab is presented. Each wearable device infers the daily activities within the wearable devices by means of the rule-based Inference Engine.
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Acknowledgements
This contribution has been supported by European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 734355 together the Spanish government by research project TIN2015-66524-P.
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Medina, J., Espinilla, M., Zafra, D., Martínez, L., Nugent, C. (2017). Fuzzy Fog Computing: A Linguistic Approach for Knowledge Inference in Wearable Devices. In: Ochoa, S., Singh, P., Bravo, J. (eds) Ubiquitous Computing and Ambient Intelligence. UCAmI 2017. Lecture Notes in Computer Science(), vol 10586. Springer, Cham. https://doi.org/10.1007/978-3-319-67585-5_48
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