Learning patterns in ambient intelligence environments: a survey

Aztiria, Asier; Izaguirre, Alberto; Augusto, Juan Carlos

doi:10.1007/s10462-010-9160-3

Cited by 89 publications

(34 citation statements)

References 48 publications

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“…Therefore, the AmI can be seen as the provision of services in the environment, with a very particular nuance: that these services must be personalized, i.e., tailored to the user's preferences and needs. We consistently find that the behaviour of people can effectively be used as an interaction medium with technology, i.e., it is possible to develop AmI systems that are responsive to people's behaviours (Aztiria et al 2010), to model their behaviours (Rodríguez-Fernández et al 2016 or even to predict their future necessities.…”

Section: Introductionmentioning

confidence: 90%

Innovations and practical applications of intelligent systems in ambient intelligence and humanized computing

Camacho

Nováis

2017

J Ambient Intell Human Comput

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systems and frameworks implementations (CampilloSanchez et al. 2015), or ambient-assisted living tools (Rashidi and Mihailidis 2013) amongst others. These, and other related areas, will provide new challenges to AmI and Intelligent Systems in the near future.This special issue on Innovations and Practical applications of Intelligent Systems in Ambient Intelligence and Humanized Computing is devoted to create a multi-disciplinary discussion forum that bring together researchers from the different fields addressed discussing issues in Intelligent Systems topics involved in the Ambient Intelligence environments. A special emphasis is done to the presentation of concrete systems, discussion of implementation and development challenges and sharing of conclusions achieved and relevant results. From previous state of the art, some contributions have been selected in order to take a step forward over different problems and challenges related to AmI.

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Section: Introductionmentioning

confidence: 90%

Innovations and practical applications of intelligent systems in ambient intelligence and humanized computing

Camacho

Nováis

2017

J Ambient Intell Human Comput

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“…Learning and Activity Recognition: the system is capable to detect within the vast amount of data produced by sensor triggering specific patterns of human behaviour which are meaningful to the services that has to provide [16]. Reasoning: cognitive inference is essential for the system to infer whether it has to act or not and what action(s) should be taken.…”

Section: Sensors and Actuatorsmentioning

confidence: 99%

"Intelligent Environments: a manifesto"

Augusto

Callaghan

Cook

et al. 2013

Hum. Cent. Comput. Inf. Sci.

236

176

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We explain basic features of an emerging area called Intelligent Environments. We give a short overview on how it has developed, what is the current state of the art and what are the challenges laying ahead. The aim of the article is to make aware the Computer Science community of this new development, the differences with previous dominant paradigms and the opportunities that this area offers to the scientific community and society. Basic conceptsHere we explain how the area of Intelligent Environments (IE) has developed, what its core values are and how it differs from other areas. By "Environment" we refer here to any space in our surroundings. Although some people may also consider virtual environments here we mostly refer to Physical spaces, in all its diversity, e.g., house, building, street, a field, an area in the sea or space, etc. Our use of the word "Intelligent" applied to Environments mostly refers to Artificial Intelligence, as defined in [1]. An Intelligent Environment is one in which the actions of numerous networked controllers (controlling different aspects of an environment) is orchestrated by self-programming pre-emptive processes (e.g., intelligent software agents) in such a way as to create an interactive holistic functionality that enhances occupants experiences. Historical development of the areaFor centuries humans have witnessed scientific and technological leaps that changed the lives of their generation, and those to come, forever. We are no exception. In fact many of those advances are occurring now, in a more or less unperceivable way. Slowly and silently technology is becoming interwoven in our lives in the form of a variety of devices which are starting to be used by people of all ages and as part of their daily routine. As predicted by M. Weiser [2], this technology is gradually disappearing from our cognitive front, as we increasingly take for granted its existence. But this fact alone could not justify a paradigm shift, as we claim in this manifesto.The emergence of a new paradigm requires the convergence of various domains of human activity, many of which are not technological. It is true that numerous technological advances have taken place during the past two decades worldwide, mainly due to persistent efforts by researchers and systematic funding by governments and markets. Among these advances one could site:

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“…They have done a great job automating the daily tasks of users by applying machine-learning approaches that learn from the past behaviour of users. A survey of the most important works in this area can be found in [11]. The main disadvantage of these approaches is that they may be intrusive for users because they do not usually take into account the users' desires (e.g., the repeated execution of an action does not imply that the user wants this automation).…”

Section: Related Workmentioning

confidence: 99%

“…Context is managed by using the ontology-based context model presented in [25]. This model is represented in Ontology Web Language (OWL) 11 . OWL is an ontology markup language that greatly facilitates knowledge automated reasoning and is a W3C standard.…”

Section: Implementation Detailsmentioning

confidence: 99%

Designing for user attention: A method for supporting unobtrusive routine tasks

Gil¹,

Serral²,

Valderas³

et al. 2013

Science of Computer Programming

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The automation of user routine tasks is one of the most important challenges in the development of Ambient Intelligence systems. However, this automation may be annoying since some tasks may grab users attention in inappropriate situations. Since user attention is a valuable resource, task automation must behave in a considerate manner demanding user attention only when it is required. To address this issue, this work presents a systematic method for supporting the design and automation of unobtrusive routine tasks that can adjust their obtrusiveness level at runtime according to the user attentional resources and context. This method proposes to design the routine tasks that the system must carry out and how they must interact with users in terms of obtrusiveness. The method also provides a software infrastructure that makes the execution of the tasks at the appropriate obtrusiveness degree a reality. Finally, the system has been validated by means of usefulness and performance tests and a practical case study that demonstrates the correctness and applicability of our approach without compromising system performance.

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Learning patterns in ambient intelligence environments: a survey

Cited by 89 publications

References 48 publications

Innovations and practical applications of intelligent systems in ambient intelligence and humanized computing

Innovations and practical applications of intelligent systems in ambient intelligence and humanized computing

"Intelligent Environments: a manifesto"

Designing for user attention: A method for supporting unobtrusive routine tasks

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