Modeling users, context and devices for ambient assisted living environments.

Eduardo Castillejo,Aitor Almeida,Diego López-De-Ipiña,Liming Chen

doi:10.3390/s140305354

Eduardo Castillejo, Aitor Almeida + Show 2 more

Open Access

https://doi.org/10.3390/s140305354

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Abstract

The participation of users within AAL environments is increasing thanks to the capabilities of the current wearable devices. Furthermore, the significance of considering user's preferences, context conditions and device's capabilities help smart environments to personalize services and resources for them. Being aware of different characteristics of the entities participating in these situations is vital for reaching the main goals of the corresponding systems efficiently. To collect different information from these entities, it is necessary to design several formal models which help designers to organize and give some meaning to the gathered data. In this paper, we analyze several literature solutions for modeling users, context and devices considering different approaches in the Ambient Assisted Living domain. Besides, we remark different ongoing standardization works in this area. We also discuss the used techniques, modeled characteristics and the advantages and drawbacks of each approach to finally draw several conclusions about the reviewed works.

Highlights

Personalization and recommender systems have spread thanks to the growth of heterogeneous connected devices and their increasing possibilities
They are aware of our behavior, preferences and trends. This new and rich situation enhances and improves the way users interact with context, but it makes people more dependent in the use of these technologies. This means that users are becoming a significant and active part of the Ambient Assisted Living (AAL) and Pervasive Computing environments
Heckmann [41] considers that users might evolve, but he takes new context information from the inference process. This opens a new point of view that we address in Section 1.1 and it takes context as a significant user’s environment entity that might directly influence the user’s capabilities

Summary

Introduction

Personalization and recommender systems have spread thanks to the growth of heterogeneous connected devices and their increasing possibilities. We can obtain recommendations while shopping based on the previously purchased items, change the music based on the user’s mood, get notifications of new and interesting releases, receive different alternatives to reach some places considering our current location, even get social advices about people consuming the same or similar products or services. This is not a situation which concerns only researchers.

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Discussion

Conclusion