An ontology-based framework for a Less Invasive Domestic Management System (LIDoMS)

Spoladore, Daniele; Mondellini, Marta; Sacco, Marco; Trombetta, Alberto

doi:10.1109/ie49459.2020.9155023

Cited by 8 publications

(6 citation statements)

References 59 publications

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“…The Age-IT digital layer relies on an EHR representation that comprises the patient's information included in the Electronic Health File-which tracks down the clinical history of a patient [88]-with the addition of clinical information pertaining to the patient's health condition modeled with the World Health Organization standards, International Classification of Functioning, Disability and Health (ICF) [89] and International Classification of Diseases (ICD) [90]. This approach has already been adopted in several knowledge-based systems [91], including some works related to the personalization of smart environments according to occupants' desires and characteristics [48,92,93].…”

Section: Ontologies For Ehr and Personalizationmentioning

confidence: 99%

“…Although Age-IT does not actively monitor the patient, it acquires-and, possibly, modifies-her/his EHR when necessary, raising similar concerns of loss of control. Age-IT adopts a "less-invasive" approach [92] when adapting its solutions to specific patients, allowing the monitoring of the environment surrounding the patient and intervening in that.…”

Section: Challenges and Limitations Of The Age-it Smart Waiting Roommentioning

confidence: 99%

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Smart Waiting Room: A Systematic Literature Review and a Proposal

Spoladore,

Mondellini,

Mahroo

et al. 2024

Electronics

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In the past decade, Internet of Things (IoT) technologies have become more and more pervasive, allowing the development of Ambient Intelligence and Context Awareness applications. While the smart home is the chosen scenario for such technologies, a variety of environments could potentially benefit from the synergies between IoT and digital applications. Among them, the clinical waiting rooms is an environment facing several challenges, particularly after the COVID-19 pandemic. Clinical waiting rooms are crowded places associated with stress and anxiety, often linked to patients’ idling time. Nonetheless, the rise of IoT-enabled telehealth has focused attention on the possibility of changing the functions of clinical waiting rooms. In this work, we conducted a systematic literature review to identify the existing solutions for “smart waiting rooms”. The review process started with 278 works, and it identified 16 papers relevant to the topic of smart clinical waiting rooms. Moreover, the results of this review underlined that waiting rooms are a neglected research area that could take advantage of IoT and Artificial Intelligence (AI) technologies to enhance patients’ experience and support the diagnostic process. Leveraging the research directions identified in the review process, this work proposes a “Smart Waiting Room” that exploits virtual reality (VR), AI, and IoT technologies to support the diagnostic process (via a cognitive assessment) and the personalization of the patient’s context—taking into account the features of the physical environment. The prototypical smart waiting room constitutes an example of the potentialities of novel technologies applied to healthcare and can contribute to shaping the future of clinical waiting rooms.

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Section: Ontologies For Ehr and Personalizationmentioning

confidence: 99%

Section: Challenges and Limitations Of The Age-it Smart Waiting Roommentioning

confidence: 99%

Smart Waiting Room: A Systematic Literature Review and a Proposal

Spoladore,

Mondellini,

Mahroo

et al. 2024

Electronics

Self Cite

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“…Considering the older workers' needs highlighted in Section 2, technologies should be aimed at reducing the health-related risks of the AW, monitoring environmental conditions to prevent the exacerbation or insurgence of any health-threatening or unsafe conditions, and assessing the activity of older workers. These adoptions of sensing technologies are also at the core of AAL solutions [39,40]; AmI requires sensing technologies to be deployed to gather data from different sources, aiming to assess different dimensions. Therefore, a hypothesis (H2) was made on the role AmI technologies played in the articles retrieved.…”

Section: Technologies Involvedmentioning

confidence: 99%

Ambient Assisted Working Solutions for the Ageing Workforce: A Literature Review

Spoladore

Trombetta

2022

Electronics

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The increase in older workers in industrialized countries has become evident in the past two decades. The need to support the ageing workforce to effectively perform their tasks has resulted in Ambient Assisted Working (AAW), consisting of developing “smart” systems that can adapt themselves to workers’ needs by exploiting ambient intelligence (AmI) solutions. In AAW, AmI provides flexible workplace adaptations for a wide range of older workers (including persons characterized by chronic conditions and disabilities), while ensuring the ageing workforce’s safety and comfort within the workplace. This work proposes a systematic literature review with the aim of identifying trends among existing AAW solutions specifically designed for older workers. The review adopted the PRISMA methodology, focusing on journal articles and surveying more than 1500 works. The review underlined an absence of articles completely devoted to this research question. Nonetheless, by extending the research question to existing AmI solutions for workers that could potentially be able to support older workers in performing their working activities, it was possible to draw some considerations on the adoption of AmI for the ageing workforce. Among them, the review identified the different types of supporting AmI solutions provided to AAW, which technologies were adopted, and which workplaces were investigated the most. Finally, this work leveraged the findings of the review process to sketch some future research directions for AAW as a discipline.

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“…It is worth to be noted, that the wireless network traces can reveal sensitive and identifiable information regarding the inhabitants of the smart-home to any eavesdropper. Indeed, any malicious actor in the vicinity of the home premises is capable of capturing the wireless network traffic and compromise the user’s privacy [ 25 ]. From our side, the capturing and analysis of the wireless network traffic takes place in the gateway, while no other external and irrelevant to the smart-home device is deployed.…”

Section: Real World Smart-home Data-setmentioning

confidence: 99%

Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set

Αναγνωστόπουλος

Σπαθούλας

Viano³

et al. 2020

Sensors

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Smart-home installations exponential growth has raised major security concerns. To this direction, the GHOST project, a European Union Horizon 2020 Research and Innovation funded project, aims to develop a reference architecture for securing smart-homes IoT ecosystem. It is required to have automated and user friendly security mechanisms embedded into smart-home environments, to protect the users’ digital well being. GHOST project aims to fulfill this requirement and one of its main functionalities is the traffic monitoring for all IoT related network protocols. In this paper, the traffic capturing and monitoring mechanism of the GHOST system, called NDFA, is presented, as the first mechanism that is able to monitor smart-home activity in a holistic way. With the help of the NDFA, we compile the GHOST-IoT-data-set, an IoT network traffic data-set, captured in a real world smart-home installation. This data-set contains traffic from multiple network interfaces with both normal real life activity and simulated abnormal functioning of the devices. The GHOST-IoT-data-set is offered to the research community as a proof of concept to demonstrate the ability of the NDFA module to process the raw network traffic from a real world smart-home installation with multiple network interfaces and IoT devices.

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An ontology-based framework for a Less Invasive Domestic Management System (LIDoMS)

Cited by 8 publications

References 59 publications

Smart Waiting Room: A Systematic Literature Review and a Proposal

Smart Waiting Room: A Systematic Literature Review and a Proposal

Ambient Assisted Working Solutions for the Ageing Workforce: A Literature Review

Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set

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