A Knowledge-Driven Approach to Activity Recognition in Smart Homes

Chen, Liming; Nugent, Chris; Wang, Hui

doi:10.1109/tkde.2011.51

Cited by 522 publications

(380 citation statements)

References 27 publications

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“…It was developed with the explicit aim of compliance with existing models, to achieve interoperability and applicability of collected datasets beyond the project. It is based on BoxLab's Activity Labels 4 and thus extends their model. A detailed presentation of the SPHERE ADL ontology can be found in [15]; the latest version is available in the OBO 5 format from http://data.bris.ac.uk (DOI: 10.5523/bris.1234ym4ulx3r11i2z5b13g93n7).…”

Section: Adl Ontologymentioning

confidence: 99%

“…In the rest of this section, we focus on a selective subset that is more relevant to our approach, presenting the most recent and noteworthy ADL recognition approaches that incorporate logical modelling and reasoning. Chen et al [4] model both sensors and activities using ontologies and perform ADL recognition via equivalence and subsumption reasoning on these models. Both offline and real-time modes are supported, while recognition becomes incrementally specific, as more and more sensors are activated.…”

Section: Related Workmentioning

confidence: 99%

“…without requiring them to carry or wear a device). Inference of real-time, continuous streams of meaningful and actionable events is also a prerequisite for ADL assistance [4]. Finally, smart homes increase the difficulty in acquiring training data, since data are environment-dependent [10].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Rule-Based Real-Time ADL Recognition in a Smart Home Environment

Baryannis

Woznowski

Antoniou

2016

Rule Technologies. Research, Tools, and Applications

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Abstract. This paper presents a rule-based approach for both offline and real-time recognition of Activities of Daily Living (ADL), leveraging events produced by a non-intrusive multi-modal sensor infrastructure deployed in a residential environment. Novel aspects of the approach include: the ability to recognise arbitrary scenarios of complex activities using bottom-up multi-level reasoning, starting from sensor events at the lowest level; an effective heuristics-based method for distinguishing between actual and ghost images in video data; and a highly accurate indoor localisation approach that fuses different sources of location information. The proposed approach is implemented as a rule-based system using Jess and is evaluated using data collected in a smart home environment. Experimental results show high levels of accuracy and performance, proving the effectiveness of the approach in real world setups.

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Section: Adl Ontologymentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Rule-Based Real-Time ADL Recognition in a Smart Home Environment

Baryannis

Woznowski

Antoniou

2016

Rule Technologies. Research, Tools, and Applications

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“…For the timebeing, context information is inferred from sensor stream by another module using a business rule engine and then used to perform service and device selection semantically. However, the ontological model is currently being extended to infer contextual knowledge using our semantic engine, as defended by Chen et al [5]. In Peacehaven nursing home, three services have been running for six months at the time of writing.…”

Section: Validation: Prototype and Deploymentmentioning

confidence: 99%

Semantic Reasoning in Context-Aware Assistive Environments to Support Ageing with Dementia

Tiberghien

Mokhtari

Aloulou

et al. 2012

The Semantic Web – ISWC 2012

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Abstract. Robust solutions for ambient assisted living are numerous, yet predominantly specific in their scope of usability. In this paper, we describe the potential contribution of semantic web technologies to building more versatile solutions -a step towards adaptable context-aware engines and simplified deployments. Our conception and deployment work in hindsight, we highlight some implementation challenges and requirements for semantic web tools that would help to ease the development of context-aware services and thus generalize real-life deployment of semantically driven assistive technologies. We also compare available tools with regard to these requirements and validate our choices by providing some results from a real-life deployment.

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“…However, to date, usability research has rather focused on people's interaction with single systems [5]. Other studies have researched technical parameters of smart environments, e.g., sensor data [6] and activity recognition [7]. It is of major importance to provide interfaces according to people's habits and intentions [3].…”

Section: Introductionmentioning

confidence: 99%

Welcome to the Future – How Naïve Users Intuitively Address an Intelligent Robotics Apartment

et al. 2016

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Abstract. The purpose of this Wizard-of-Oz study was to explore the intuitive verbal and non-verbal goal-directed behavior of naïve participants in an intelligent robotics apartment. Participants had to complete seven mundane tasks, for instance, they were asked to turn on the light. Participants were explicitly instructed to consider nonstandard ways of completing the respective tasks. A multi-method approach revealed that most participants favored speech and interfaces like switches and screens to communicate with the intelligent robotics apartment. However, they required instructions to use the interfaces in order to perceive them as competent targets for human-machine interaction. Hence, first important steps were taken to investigate how to design an intelligent robotics apartment in a user-centered and user-friendly manner.Keywords: Social robot • smart home • human-robot interaction • use-case scenario • usability • intuitive design • user-centered design.

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A Knowledge-Driven Approach to Activity Recognition in Smart Homes

Cited by 522 publications

References 27 publications

Rule-Based Real-Time ADL Recognition in a Smart Home Environment

Rule-Based Real-Time ADL Recognition in a Smart Home Environment

Semantic Reasoning in Context-Aware Assistive Environments to Support Ageing with Dementia

Welcome to the Future – How Naïve Users Intuitively Address an Intelligent Robotics Apartment

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