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Interpreting Information in Smart Environments with Social Patterns

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Book cover Multi-Agent Systems (EUMAS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11450))

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Abstract

Smart Environments (SEs) work in close interaction with their users. To perform properly, these systems need to process their information (both from sensing and to act) considering its meaning for people. For instance, when they manage workflows that represent users’ activities or consider the tradeoffs between alternative actions. Introducing social knowledge about the human context helps SEs to better interpret information, and thus people’ needs and actions. However, working with this knowledge faces several difficulties. Its level of abstraction is different from that directly related to system components. Moreover, it belongs to a background that is not frequent among engineers. In order to address these issues, this paper proposes the use of Social Context-Aware Assistants (SCAAs). These Multi-Agent Systems (MASs) manage explicitly social information using specifications conform to a domain-specific Modelling Language (ML). The ML aims at describing human aspects and their changes in a given context related to a SE. Social properties describe reusable knowledge using a template with these specifications and textual explanations. Working with the ML facilitates the semi-automated transformation of specifications to integrate social and other system information, derive new one, and check properties. Specific agents are responsible for managing information, and translating data from sensors to the ML, and from this to data for actuators. A case study on an alert system to monitor group activities, extended with social knowledge to interpret people’ behaviour, illustrates the approach.

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Acknowledgment

This work has been done in the context of the mobility plan for the mobility of researchers “Subprograma de Movilidad del Programa Estatal de Promoción del Talento y su Empleabilidad, en el marco del Plan Estatal de Investigación Científica y Técnica y de Innovación” (grant PRX17/00613) supported by the Spanish Ministry for Education, Culture, and Sports, the projects “Collaborative Ambient Assisted Living Design (ColoSAAL)” (grant TIN2014-57028-R) supported by the Spanish Ministry for Economy and Competitiveness, MOSI-AGIL-CM (grant S2013/ICE-3019) supported by the Autonomous Region of Madrid and co-funded by EU Structural Funds FSE and FEDER, and the “Programa de Creación y Consolidación de Grupos de Investigación” (UCM-BSCH GR35/10-A).

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Authors and Affiliations

  1. Research Group on Agent-Based, Social and Interdisciplinary Applications (GRASIA), Universidad Complutense de Madrid, Madrid, Spain

    Rubén Fuentes-Fernández & Jorge J. Gómez-Sanz

Authors
  1. Rubén Fuentes-Fernández
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  2. Jorge J. Gómez-Sanz
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Correspondence to Rubén Fuentes-Fernández .

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Editors and Affiliations

  1. University of Bergen, Bergen, Norway

    Marija Slavkovik

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Fuentes-Fernández, R., Gómez-Sanz, J.J. (2019). Interpreting Information in Smart Environments with Social Patterns. In: Slavkovik, M. (eds) Multi-Agent Systems. EUMAS 2018. Lecture Notes in Computer Science(), vol 11450. Springer, Cham. https://doi.org/10.1007/978-3-030-14174-5_4

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  • DOI: https://doi.org/10.1007/978-3-030-14174-5_4

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