Interoperability for Smart Appliances in the IoT World

Daniele, Laura; Solanki, Monika; Hartog, Frank den; Roes, Jasper

doi:10.1007/978-3-319-46547-0_3

Cited by 46 publications

(37 citation statements)

References 4 publications

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“…Along with these research fields, ontologies have been exploited as a means to provide a shareable and formal conceptualization of a variety of domains of knowledge that are related to the SH or its components. However, only a few works tackled the issue of providing a reusable model of indoor comfort metrics, focusing mostly on the description of concepts related to energy consumption and saving [8,9], device descriptions [10,11], human activities within the SH [12], and interoperability among various devices [13,14].…”

Section: Related Workmentioning

confidence: 99%

ComfOnt: A Semantic Framework for Indoor Comfort and Energy Saving In Smart Homes

et al. 2019

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This work introduces ComfOnt, a semantic framework developed within the context of ambient assisted living, context awareness, and ambient intelligence Italian research projects. ComfOnt leverages knowledge regarding Smart Home inhabitants and their particular needs, the devices deployed inside the domestic environment (appliances, sensors, and actuators), the amount of their energy consumption, and indoor comfort metrics to provide dwellers with customized services. Developed reusing widely adopted ontologies, ComfOnt aims at providing inhabitants with the possibility of having personalized indoor comfort in their living environments and at helping them in scheduling their daily activities requiring appliances; in fact, the proposed semantic framework enables the representation of appliances' energy consumption and the energy profile of the Smart Home, thus assisting the dwellers in avoiding power cuts and fostering energy savings. ComfOnt serves as a knowledge base for a prototypical application (DECAM) dedicated to Smart Home inhabitants; the architecture and the functionalities of DECAM are here presented.Although research in the fields of SH, ambient assisted living (AAL), ambient intelligence (AmI), context awareness (CA), and IoT leveraging semantic formalization of knowledge has acquired a growing importance in the last years, only a few works dedicated to the SH tackled the issue of modeling indoor comfort metrics. This work aims at contributing to the field of domain ontologies dedicated to the representation of knowledge necessary to customize services within an SH, including comfort metrics leveraging on already existing models. The proposed set of domain ontologies arises from the experiences of three Italian research projects funded by the Lombardy Region: i-Zeb, Future Homes for Future Communities (FHfFC), and CasAware. i-Zeb [4] is a project aimed at researching and investigating the use of innovative building materials and technological solutions to foster the implementation of Nearly Zero-Energy Buildings. FHfFC [5] focuses on deploying a semantic architecture to enable a set of assistive services aimed at improving inhabitants' daily lives; the services are addressed to an ageing population and encompass a wide range of fields, such as indoor comfort, device interoperability, and domestic rehabilitation. CasAware [6,7] leverages ontological representation of domestic appliances and their energy consumption to foster energy saving behavior, help the dwellers to better schedule their operations with appliances, and avoid domestic power cuts.The set of domain ontologies developed within these three projects-named ComfOnt-allows the formalization of some fundamental indoor comfort metrics, including Italian regulations and laws, and knowledge regarding sensors, actuators, and measurements; ComfOnt can be adopted to describe environmental conditions within the SH and to trigger comfort actuation after detecting an unsafe or uncomfortable situation, exploiting the results deriving from reasoning proc...

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Section: Related Workmentioning

confidence: 99%

ComfOnt: A Semantic Framework for Indoor Comfort and Energy Saving In Smart Homes

et al. 2019

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“…Such objects are also defined by data abstraction processes that include coded artefacts, programming languages, and the environments required for their function (Berry, 2011;Fuller, 2008;Mackenzie, 2005;Mackenzie & Vurdubakis, 2011). Examples include "smart" household appliances (Daniele, Solanki, den Hartog, & Roes, 2016), smartphones (Hsiao, 2013), QS devices (such as FitBits; Cyr, Horn, Miao, & Specter, 2014) and personal computers. Software within these devices manipulates data in powerful yet often invisible ways, which involves data abstraction.…”

Section: Data Abstractionmentioning

confidence: 99%

The myth of the “data‐driven” society: Exploring the interactions of data interfaces, circulations, and abstractions

Lee

Cook

2019

Sociology Compass

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The prominence of data and data technologies in society, such as algorithms, social media, mobile technology, and artificial intelligence, have heralded numerous claims of the revolutionary potential of these systems. From public policy, to business management, to scientific research, a “data‐driven” society is apparently imminent—or currently happening—where “objective” and asocial data systems are believed to be comprehensively improving human life. Through a review of existing sociological literature, in this article, we critically examine the relationship between data and society and propose a new model for understanding these dynamics. “Using the concept of the informatic,” we argue the relationship between data and society can be understood as representing the interaction of several different social trends around data; that of data interfaces (that connect individuals to digital contexts), data circulation (trends in the movement and storage of data), and data abstraction (data manipulation practices). Data and data technologies are founded to be entwined and embedded in numerous social relationships, and while not all are fair and equitable relationships, there is ample evidence of the deeply social nature of data across many streams of social life. Our three‐part informatic framework allows these complex relationships to be understood in the social dynamic through which they are witnessed and experienced.

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“…As a method for information management, the recent years have seen the development of ontologies in related areas such as Internet of Things [10], smart environments including multimedia deployment and contextawareness [11], etc.…”

Section: Related Workmentioning

confidence: 99%

“…The two commonly used ontologies for smart environments are the Smart Appliances REFerence (SAREF) [11] ontology and the Internet of Things Ontology (IoT-O) [29]. In general, the SAREF ontology provides an ontology design for an indoor smart environment scenario.…”

Section: B Ontologiesmentioning

confidence: 99%

Towards adaptive control in smart homes: Overall system design and initial evaluation of activity recognition

Wang

Dogan²,

Stolikj

et al. 2017

2017 Intelligent Systems Conference (IntelliSys)

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Interoperability for Smart Appliances in the IoT World

Cited by 46 publications

References 4 publications

ComfOnt: A Semantic Framework for Indoor Comfort and Energy Saving In Smart Homes

ComfOnt: A Semantic Framework for Indoor Comfort and Energy Saving In Smart Homes

The myth of the “data‐driven” society: Exploring the interactions of data interfaces, circulations, and abstractions

Towards adaptive control in smart homes: Overall system design and initial evaluation of activity recognition

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