Cloud Computing Enhanced Service Development Architecture for the Living Usability Lab

Cloud Computing Enhanced Service Development Architecture for the Living Usability Lab

Cláudio Teixeira (Universidade de Aveiro, Portugal), Joaquim Sousa Pinto (Universidade de Aveiro, Portugal), Flávio Ferreira (Universidade de Aveiro, Portugal), André Oliveira (Universidade de Aveiro, Portugal), António Teixeira (Universidade de Aveiro, Portugal) and Carlos Pereira (Universidade de Aveiro, Portugal)
DOI: 10.4018/978-1-4666-3667-5.ch003
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Abstract

As life expectancy increases, so does the number of Ambient Assisted Living (AAL) initiatives. The Living Usability Lab is a user-centered living laboratory aimed at open-innovation and evaluation of new approaches to AAL applications and services, where the different stakeholders may develop and evaluate innovative services for the elderly in near-real life conditions. These AAL initiatives often traverse several research fields, from embedded devices to multiple data streams analysis. Advanced processing, reasoning, and storage of such data streams poses a complex problem usually solved using local processing and storage resources. This chapter presents an overview of the LUL initiative, its services, and applications, and explores the problem of advanced processing, reasoning, and storage from a cloud computing perspective.
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Introduction

Living Usability Lab (LUL) (LUL Consortium, 2010; Teixeira et al., 2011) is a joint academia-industry R&D initiative of industry and research, started in January 2010, aiming at creating the conditions to develop and evaluate innovative services for the Elderly. Essentially, it is a living laboratory to test new approaches to the ambient assisted living initiative.

Nuclear to the project is its attention to usability, multimodal interaction, design for all and the exploration of new opportunities opened by Next Generation Networks (NGN). Multimodality is essential to support intuitive and natural interfaces effectively humanized.

Considering the high demands on the overall AAL system quality and consequently on software and system engineering, user acceptance is an absolute necessity. Therefore, the early involvement of end users in the design process assumes a high importance to meet the actual needs of the future users in their daily life.

Although the importance of the user involvement and user participation in the design process has been recognized as essential, there is a need to further developments in the daily practice, through the use of innovative strategies. LUL provides an emerging research methodology which includes the user involvement by taking into account the micro-context of their daily activities.

Elderly people tend to suffer more with social exclusion, especially in the urban centers. In Portugal, during the winter of 2011, social media reported cases of elderly people found dead in their homes several weeks after passing away. These cases triggered a bigger social awareness with neighbors wondering when they had last seen their elder neighbors. In some cases, they were also found dead.

By addressing the scenario of elderly at home with these specificities, the project is in line with the most recent developments in the broad area of Ambient Assisted Living (AAL). AAL system’s main goal is to supervise or assist elders on their daily activities, contributing to a better quality of life. Each targeted subject, considering its limitations and personal goals, has specific needs and technical requirements on monitoring and every day follow-up from the AAL systems. These are dynamic parameters, affected by the subject’s age, sedentary levels and mobility capacities. There is no standard AAL subject, since subjects may range from fully independent and autonomous subjects, to house-confined, low mobility subjects and, of course, everything in between.

For fully independent users that keep an active lifestyle, AAL systems may operate on a remote monitoring fashion, checking, reporting and enforcing (in some extent) an active lifestyle to the subject. Subject’s everyday activities and exercises are monitored to extract activity information and subject’s achievements (on exercises). This information may be shared with monitoring health professional teams. These teams keep track of the subject’s evolution and of abnormal values, enabling them to act fast when unexpected subject’s parameters are reported.

In the case of low mobility subjects due to age, accident or disability, AAL systems may operate in a close monitoring way, giving real-time information on the subject’s location and health status. Exercise’s results may be acquired to evaluate on the subject’s progression in terms of mobility. This kind of elderly people possess a special set of characteristics (i.e. low mobility, bad sight, bad hearing) that forces developers to look beyond the traditional software development methodologies and look more closely to aspects such as usability rates and other methods of interaction

Many of the AAL applications are targeted for house use, often requiring vigilance using technologies such as video analysis or environmental data reading (temperature, humidity, etc.), and interactivity using speech recognition or touch capabilities. A relevant part of the subjects’ needs can be monitored by a set of common home automation sensors. The most common sensors are: opened doors and windows detectors, flood detectors, gas leak detectors, smoke detectors, movement detectors and stove on detectors.

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