Ambient Intelligence—the Next Step for Artificial Intelligence

Ramos, Carlos; Augusto, Juan Carlos; Shapiro, Daniel

doi:10.1109/mis.2008.19

Cited by 363 publications

(162 citation statements)

References 3 publications

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“…To achieve this purpose we follow the guiding lines of Ambient Intelligence (AmI) [14], in which the technological aspects are hidden in the environment and the user is placed in the middle of the paradigm. There is also a focus on non-intrusiveness, with acquisition of information taking place without the need for explicit or conscious user interactions.…”

Section: Frameworkmentioning

confidence: 99%

Non-intrusive quantification of performance and its relationship to mood

et al. 2016

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The number of jobs that takes place entirely or partially in a computer is nowadays very signi cant. These workplaces, as many others, often o er the key ingredients for the emergence of stress and the performance drop of its long-term e ects: long hours sitting, sustained cognitive e ort, pressure from competitiveness, among others. This has a toll on productivity and work quality, with signi cant costs for both organizations and workers. Moreover, a tired workforce is generally more susceptible to negative feelings and mood, which results in a negative environment. This paper contributes to the current need for the development of non-intrusive methods for monitoring and managing worker performance in real time. We propose a framework that assesses worker performance and a case study in which this approach was validated. We also show the relationship between performance and mood.

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Section: Frameworkmentioning

confidence: 99%

Non-intrusive quantification of performance and its relationship to mood

et al. 2016

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“…The agent-based paradigm is particularly appropriate for the implementation of Ambient Intelligence [6,16], because agents offer features that originate from the field of Artificial Intelligence and that are vital to the needs of Ambient Intelligence [11]. Autonomy is useful because individual devices in an Ambient Intelligence environment must be able to act on their own, without the need for user intervention or permanent control from centralized components.…”

Section: Mobile Multi-agent Systemsmentioning

confidence: 99%

“…The agent-oriented paradigm is also useful in modeling real-world and social systems, where optimal solutions are not needed and problems are solved by cooperation and communication, in a fully distributed fashion [11]. Currently, several agent-oriented programming languages exist [2], that allow the programmer to describe an application only by specifying the behaviour of individual agents.…”

Section: Mobile Multi-agent Systemsmentioning

confidence: 99%

Ao Dai: Agent Oriented Design for Ambient Intelligence

Seghrouchni¹,

Олару²,

Thuy³

et al. 2012

Principles and Practice of Multi-Agent Systems

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ISBN 978-3-642-25919-7 (ISI Proceedings)International audienceIn this paper we present mobile Multi-Agent Systems (MAS) as a specific paradigm to design intelligent and distributed applications in the context of Ambient Intelligence (AmI). We discuss how mobility, coupled with MAS, can be useful to meet the requirements of AmI. Indeed, the main features of mobile MAS, such as natural distribution of the system, inherent intelligence of the agents, and their mobility help to address a large scope of distributed applications in the domain of AmI. Other features of MAS, like multi-agent planning, context-awareness and self-adaptation are also very useful to bring an added value to AmI applications. They allow the implementation of both intelligent and collaborative agent behavior. This paper presents the Ao Dai project, that employs the mobile MAS paradigm, and serves as a prototype AmI environment. We also illustrate the functioning of the application through a scenario of user guidance in a smart environment

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“…Agents and multiagent systems have been suggested as an important paradigm in the design of intelligent environments [19]. Agents are specially good at modelling real world and social systems due to their social abilities (agents, by definition, are social entities [30]).…”

Section: Interruptions In Pervasive Awarenessmentioning

confidence: 99%

To Be or Not to Be Aware: Reducing Interruptions in Pervasive Awareness Systems

Petersen

Cassens

Kofod-Petersen

et al. 2008

2008 the Second International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies

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In this paper we look at awareness systems that use mobile and ambient devices for collecting or presenting awareness information and operate within an Ambient Intelligence Environment. Our focus is on Pervasive Awareness Systems (PAS) that mediate awareness with the aim to improve the feeling of being connected. In particular, we concentrate on the challenges that are connected to participation in multiple communities, requiring a continuous balancing between the need to "keep in touch" and to reduce interruptions. In the paper, we discuss software agents as a possible solution and identify the different roles that agents can play in reducing interruptions.

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Ambient Intelligence—the Next Step for Artificial Intelligence

Cited by 363 publications

References 3 publications

Non-intrusive quantification of performance and its relationship to mood

Non-intrusive quantification of performance and its relationship to mood

Ao Dai: Agent Oriented Design for Ambient Intelligence

To Be or Not to Be Aware: Reducing Interruptions in Pervasive Awareness Systems

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