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Surveying Human Habit Modeling and Mining Techniques in Smart Spaces

Author

Listed:
  • Francesco Leotta

    (Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti, Sapienza Università di Roma, 00185 Rome, Italy)

  • Massimo Mecella

    (Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti, Sapienza Università di Roma, 00185 Rome, Italy)

  • Daniele Sora

    (Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti, Sapienza Università di Roma, 00185 Rome, Italy)

  • Tiziana Catarci

    (Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti, Sapienza Università di Roma, 00185 Rome, Italy)

Abstract

A smart space is an environment, mainly equipped with Internet-of-Things (IoT) technologies, able to provide services to humans, helping them to perform daily tasks by monitoring the space and autonomously executing actions, giving suggestions and sending alarms. Approaches suggested in the literature may differ in terms of required facilities, possible applications, amount of human intervention required, ability to support multiple users at the same time adapting to changing needs. In this paper, we propose a Systematic Literature Review (SLR) that classifies most influential approaches in the area of smart spaces according to a set of dimensions identified by answering a set of research questions. These dimensions allow to choose a specific method or approach according to available sensors, amount of labeled data, need for visual analysis, requirements in terms of enactment and decision-making on the environment. Additionally, the paper identifies a set of challenges to be addressed by future research in the field.

Suggested Citation

  • Francesco Leotta & Massimo Mecella & Daniele Sora & Tiziana Catarci, 2019. "Surveying Human Habit Modeling and Mining Techniques in Smart Spaces," Future Internet, MDPI, vol. 11(1), pages 1-23, January.
    • Handle: RePEc:gam:jftint:v:11:y:2019:i:1:p:23-:d:199242
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