Ontology-based smart IoT engine for personal comfort management

Gâteau, Benjamin; Naudet, Yannick; Rykowski, Jarogniew

doi:10.1109/smap.2016.7753381

Cited by 9 publications

(7 citation statements)

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“…[14], [17] and [28] cover majority of the pollutants mentioned in the above standards, while [29] consider 12 pollutants. However, pollutant types are not specified in several studies such as [16], [18] and [30]. Overall, findings from review show that majority of the studies consider carbon oxides or particulate matter which demonstrate significance and widespread nature of the pollutants.…”

Section: Air Pollutantsmentioning

confidence: 99%

“…Therefore, many of the existing studies focus on indoor air quality monitoring. For example, [12], [13], [14], [15] and [16] present different solutions for indoor air quality monitoring, prediction and control. However, recent statistics from WHO [3] on air pollution illnesses and mortality show that number of deaths caused by outdoor air pollution is more than 3 million.…”

Section: A Environment Typementioning

confidence: 99%

“…[28] and [31] provide only locationbased information, while [23] considers time. [14], [15] and [16] consider more context information such as environment and user's personal health features, however, all three researches oriented on indoor air quality.…”

Section: Context Awarenessmentioning

confidence: 99%

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CAVisAP: Context-Aware Visualization of Outdoor Air Pollution with IoT Platforms

Nurgazy

2019

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Recently air pollution became a severe issue in many big cities due to population growth and rapid development of economy and industry. This led to proliferating need to monitor urban air quality in order to avoid personal exposure as well as to make savvy decisions on managing the environment. In the last decades Internet of Things (IoT) is increasingly being applied to environmental challenges, including air quality monitoring and visualization. In this paper we present CAVisAP, a context-aware system for outdoor air pollution visualization with IoT platforms. The system aims to provide context-aware visualization of three air pollutants such as nitrogen dioxide (NO2), ozone (O3) and particulate matter (PM2.5) in the city of Melbourne, Australia. In addition to primary context as location and time, CAVisAP takes into account users’ pollutant sensitivity levels and color vision impairments to provide personalized pollution maps. Experiments are conducted to validate the system and results are discussed.

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Section: Air Pollutantsmentioning

confidence: 99%

Section: A Environment Typementioning

confidence: 99%

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CAVisAP: Context-Aware Visualization of Outdoor Air Pollution with IoT Platforms

Nurgazy

2019

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“…The practical use of semantic procedures and tools requires formulation and availability of explicitly expressed ontologies, represented using a standard ontology language (such as RDF Schema or OWL). Ontologies are responsible for describing and addressing nodes like sensors, objects, actuators, devices, services and providing the essential level and/or layer of abstraction to deal with heterogeneity and interoperability [12], [28]. Additionally, to support higher level operations, ontologies are concerned with data models as well as interpretations and reasoning coming from sensors and other data produced by devices.…”

Section: Ontology-based Iohtmentioning

confidence: 99%

DITrust Chain: Towards Blockchain-Based Trust Models for Sustainable Healthcare IoT Systems

et al. 2020

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Today, internet and device ubiquity are paramount in individual, formal and societal considerations. Next generation communication technologies, such as Blockchains (BC), Internet of Things (IoT), cloud computing, etc. offer limitless capabilities for different applications and scenarios including industries, cities, healthcare systems, etc. Sustainable integration of healthcare nodes (i.e. devices, users, providers, etc.) resulting in healthcare IoT (or simply IoHT) provides a platform for efficient service delivery for the benefit of care givers (doctors, nurses, etc.) and patients. Whereas confidentiality, accessibility and reliability of medical data are accorded high premium in IoHT, semantic gaps and lack of appropriate assets or properties remain impediments to reliable information exchange in federated trust management frameworks. Consequently, We propose a Blockchain Decentralised Interoperable Trust framework (DIT) for IoT zones where a smart contract guarantees authentication of budgets and Indirect Trust Inference System (ITIS) reduces semantic gaps and enhances trustworthy factor (TF) estimation via the network nodes and edges. Our DIT IoHT makes use of a private Blockchain ripple chain to establish trustworthy communication by validating nodes based on their inter-operable structure so that controlled communication required to solve fusion and integration issues are facilitated via different zones of the IoHT infrastructure. Further, C implementation using Ethereum and ripple Blockchain are introduced as frameworks to associate and aggregate requests over trusted zones.

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“…Gâteau et al [15] proposed an IoT system for personal comfort management; in this work, comfort representation with ontologies was addressed relying to classes deriving from the DogOnt ontology [16] and Semantic Sensor Network (SSN) ontology [17]. A similar approach was adopted in [18], where an indoor environmental comfort system takes advantage of a context domain ontology that formalizes concepts for the description of sensors and actuators; comfort metrics are not explicitly modeled in this work, although contextual data are acquired and re-elaborated using semantic rules.…”

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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Ontology-based smart IoT engine for personal comfort management

Cited by 9 publications

References 0 publications

CAVisAP: Context-Aware Visualization of Outdoor Air Pollution with IoT Platforms

CAVisAP: Context-Aware Visualization of Outdoor Air Pollution with IoT Platforms

DITrust Chain: Towards Blockchain-Based Trust Models for Sustainable Healthcare IoT Systems

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

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