Ontology-Based Decision Support Systems for Health Data Management to Support Collaboration in Ambient Assisted Living and Work Reintegration

Spoladore, Daniele

doi:10.1007/978-3-319-65151-4_32

Cited by 19 publications

(18 citation statements)

References 18 publications

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“…In this regard, the SH needs to encompass also dwellers' data regarding their needs and health conditions, and ontologies can provide the means to formalize this non-static information. In [31,33], semantic representations of people's health conditions are used to trigger environmental adaptations, so that the environment is able to meet its occupants' needs. Following a different approach, Heckmann et al [34] revisited the General User Model Ontology (GUMO) [35], taking into account Web 2.0, thus enriching it with tags and folksonomies provided by user-generated contents on the Web.…”

Section: Related Workmentioning

confidence: 99%

“…Following an ODP described in [31] and [33], each dweller is assigned to his/her health condition, which is detailed recurring to the ICF ontology. Figure 2 provides a graphical representation of a 68-year-old dweller and his health condition, which is characterized by a severe impairment in light sensitivity (b21020) and a moderate impairment in sustaining attention (b1400).…”

Section: Inhabitants' Modulementioning

confidence: 99%

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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%

Section: Inhabitants' Modulementioning

confidence: 99%

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

et al. 2019

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“…However, there are sectors where algorithms cannot be completely automatized because of the high risks associated with possibly wrong decisions (e.g. medical diagnosis Decision Support System (DSS), or health-related DSSs [141]).…”

Section: Barriersmentioning

confidence: 99%

Key Research Priorities for Factories of the Future—Part I: Missions

Tolio

Copani

Terkaj

2019

Factories of the Future

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This chapter investigates research priorities for factories of the future by adopting an approach based on mission-oriented policies to support manufacturing innovation. Missions are challenging from a scientific and technological point of view and, at the same time, are addressing problems and providing results that are understandable by common people. Missions are based on clear targets that can help mitigating grand challenges. Based on the results of the Italian Flagship Project Factories of the Future, this chapter proposes seven missions while identifying the societal impact, the technological and industrial challenges, and the barriers to be overcome. These missions cover topics such as circular economy, rapid and sustainable industrialisation, robotic assistant, factories for personalised medicine, internet of actions, factories close to the people, and turning ideas into products. The accomplishment of missions asks for the support of a proper research environment in terms of infrastructures to test and demonstrate the results to a wide public. Research infrastructures together with funding mechanisms will be better addressed in the next chapter of this book. 20.1 Mission-Oriented Research and Innovation Policies The importance of the manufacturing industry both for developed and developing countries has been assessed in several works [1-4], which highlight the need of continuous innovation to cope with societal grand challenges [5]. The results of inno-T. Tolio Director of the Italian Flagship Project "Factories of the Future", Direttore del Progetto Bandiera "La Fabbrica del Futuro",

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“…Therefore, the qualified code b21020.2 indicates a moderate impairment in the "Colour vision". ICF is often exploited as a practical tool to ease the communication between health professionals and other stakeholders [59,62]; moreover, the classification is suited also to describe each context where health and environment interact: work reintegration [63], domestic age-care [64], AAL [65]. ICF has also been represented into an ontological model in RDF/OWL [56], which can be used as reference in the modelling of more complex ontologies.…”

Section: A Holistic Framework For Guest's Health Status Descriptionmentioning

confidence: 99%

RoomFort: An Ontology-Based Comfort Management Application for Hotels

et al. 2018

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Business traveling is attracting growing attention due to the expansion of international markets. This fact calls for an increasing attention of the tourism sector toward the needs of business travellers, who often require services that are different from the ones desired by leisure tourists. The application of smart solutions coming from Context Awareness and Ambient Intelligence aimed at promoting guests' comfort and well-being, also in cases in which they have special needs, represents a promising solution to tackle business travellers' requirements and thus, to increase hotels attractiveness and incomes. In this context, this work introduces RoomFort, a smart comfort management system aimed at enhancing comfort of hotel room guests and leveraging on semantic representations of comfort, environment, and sensors. RoomFort provides a set of domain ontologies to formalize comfort-related metrics and to exploit the automatic reasoning capabilities provided by Semantic Web technologies, while gathering data through a network of sensors to ensure guests are provided with tailored comfort profiles during their stays in the hotel. Particular focus has been placed on visual comfort, since indoor lighting features constitute one of the main factors influencing the two main activities that most business travellers accomplish in their hotel room: working and relaxing.

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Ontology-Based Decision Support Systems for Health Data Management to Support Collaboration in Ambient Assisted Living and Work Reintegration

Cited by 19 publications

References 18 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

Key Research Priorities for Factories of the Future—Part I: Missions

RoomFort: An Ontology-Based Comfort Management Application for Hotels

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