Improving the adaptation process for a new smart home user

Ali, S. M. Murad, Augusto, Juan Carlos ORCID: https://orcid.org/0000-0002-0321-9150 and Windridge, David ORCID: https://orcid.org/0000-0001-5507-8516 (2019) Improving the adaptation process for a new smart home user. Bramer, Max and Petridis, Miltos, eds. Artificial Intelligence XXXVI 39th SGAI International Conference on Artificial Intelligence (AI-2019), Cambridge, UK, December 17–19, 2019, Proceedings. In: 39th SGAI International Conference on Artificial Intelligence (AI-2019)., 17-19 Dec 2019, Cambridge, UK.. pbk-ISBN 9783030348847, e-ISBN 9783030348854. ISSN 0302-9743 [Conference or Workshop Item] (doi:10.1007/978-3-030-34885-4_32)

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Abstract

Artificial Intelligence (AI) has been around for many years and plays a vital role in developing automatic systems that require decision using a data- or model-driven approach. Smart homes are one such system; in them, AI is used to recognize user activities, which is a fundamental task in smart home system design.There are many approaches to this challenge, but data-driven activity recognition approaches are currently perceived the most promising to address the sensor selection uncertainty problem. However, a smart home using a data-driven approach exclusively cannot immediately provide its new occupant with the expected functionality, which has reduced the popularity of the datadriven approach. This paper proposes an approach to develop an integrated personalized system using a user-centric approach comprising survey, simulation, activity recognition and transfer learning. This system will optimize the behaviour of the house using information from the user’s experience and provide required services. The proposed approach has been implemented in a smart home and validated with actual users. The validation results indicate that users benefited from smart features as soon as they move into the new home

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