Ambient intelligence

Aarts, Ehl Emile; Wichert, Reiner

doi:10.1007/978-3-540-88546-7_47

Cited by 109 publications

(59 citation statements)

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“…The Ambient Intelligence (AmI) paradigm represents the future vision of intelligent computing where environments support the people inhabiting them [1], [2], [3]. In this new computing paradigm, the conventional input and output media no longer exist, rather the sensors and processors will be integrated into everyday objects, working together in harmony in order to support the inhabitants [4].…”

Section: Introductionmentioning

confidence: 99%

A Survey on Ambient Intelligence in Healthcare

et al. 2013

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Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people’s capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users’ goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.

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Section: Introductionmentioning

confidence: 99%

A Survey on Ambient Intelligence in Healthcare

et al. 2013

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“…RFID, as all other mobile and ubiquitous computing technologies, enables a seamless and non-intrusive integration of IT applications and services into everyday life environments Resatsch et al 2008;Schweiger et al 2007;Uhrich et al 2008). Examples of research on ubiquitous computing technology as the basis of AAL systems are documented in the literature (Aarts and Wichert 2009;Mufti et al 2009;Postolache et al 2009;Rogers 2006).…”

Section: Related Workmentioning

confidence: 98%

Reaching into patients’ homes – participatory designed AAL services

Menschner¹,

Prinz²,

Koene³

et al. 2011

Electron Markets

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Ambient Assisted Living (AAL) offers possibilities for promising new IT-based health care services that are resulting in new challenges for its design process. We introduce a novel approach for engineering AAL services (AALSDA) which combines methods from service engineering and participatory design. We demonstrate this approach by developing and implementing an electronic data capture system, NuTrack, for self-reporting of nutrition status. The approach uses different concepts for AAL service design and delivery: service engineering for standardizing and structuring service processes, reasonable IT-support for automation of parts of services that need no person-toperson interaction, participatory design to integrate end-users in the development process, and patient integration for personalizing and improving the depth of performance of service providers' service delivery. For illustration, we present the case of chronic disease patients suffering from impaired fine motor skills. Our approach is applied in a pilot study with prototypes tested in focus groups and workshops with patients, caregivers and physicians. The results demonstrate good applicability and feasibility of the concept, and provide new insights for the future design, development and implementation of AAL services.

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“…AmI is a discipline where numerous technologies, such as pervasive computing, ubiquitous computing, and context awareness, have been combined to create systems or environments that sense or adapt to the actions or demands of people or objects within an environment (Aarts and Wichert 2009). During the initial stages of AmI development, the most frequently discussed scope of application has involved the application of AmI in daily life, including the development of smart cars, smart homes, and health and entertainment devices (Cook et al 2009).…”

Section: Introductionmentioning

confidence: 99%

An ambient intelligence system for water release scheduling in cascade hydropower systems

Tseng

Lee

Chou

2014

J Ambient Intell Human Comput

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This study designed an ambient intelligence (AmI)-based decision support system that combined an electromagnetism-like mechanism (EM) and sensory data to aid human operators in making decisions regarding the management of cascade hydropower systems. Currently, cascade hydropower systems are the primary source of hydropower in Taiwan, and the Dajia Hydropower System is the largest one in Taiwan. The operational considerations of the various plants in this system include water levels constraints, minimal water release constraints, and maximal water release constraints. These considerations must be emphasized to plan the hourly water release rate and to maximize the power generation profitability of the overall system. Although extant operations are viable, an accurate calculation method for maximizing the economic efficiency of hydropower generation is yet to be developed. The AmI-based system proposed in this study can be used to determine the periodic water release at each plant in the system, thereby maximizing the company's power-generation profit. In addition, the proposed system was compared with the scheduling system currently employed by the Dajia Hydropower System. The scheduling operations of the Dajia Hydropower System for 23 nonsummer days and a whole year were examined, respectively, and the hydropower plant's original scheduling method was compared with that of the proposed system. Test results indicated that the scheduling plan obtained from the proposed system increased the profit of the Taiwan Power Company.

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Ambient intelligence

Cited by 109 publications

References 0 publications

A Survey on Ambient Intelligence in Healthcare

A Survey on Ambient Intelligence in Healthcare

Reaching into patients’ homes – participatory designed AAL services

An ambient intelligence system for water release scheduling in cascade hydropower systems

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