Towards a Smart Home for Elder Healthcare

Staifi, Noureddine; Brahimi, Said; Maamri, Ramdane; Belguidoum, Meriem

doi:10.1109/ficloud.2019.00039

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…The self-organised learning model presented in [22] can adapt its work to a particular patient by using feedback from medical staff and a real-time linear optimisation process. The work presented in [20] proposes a context-aware smart home system that allows older people to live independently. The system provides adapted services in terms of comfort, health and safety considering the user's profile.…”

Section: Related Workmentioning

confidence: 99%

A FaaS Approach for Long-Term Monitoring in Rehabilitation

Serrano-Gutierrez

Ayala

Fuentes

2022

Lecture Notes in Networks and Systems

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The function as a service (FaaS) model, in which the costs are linked to the function time of use, is especially suitable in IoT or similar systems, where the information is collected periodically to consume less energy. A FaaS approach also allows us to fine-tune the application's behaviour at a function level, controlling which functions should be executed at any given time. This makes it possible to apply optimisation processes in an automated way. In this work, a FaaS-based platform is proposed to develop e-Health applications that adapt their behaviour to the different stages of the patient rehabilitation process. Its operation is illustrated by a case study on patients with heart disease. The system's operation will vary throughout the different stages of the rehabilitation, adjusting to the available sensors, the evolution of the patient's physical condition and other parameters such as the required precision.

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Section: Related Workmentioning

confidence: 99%

A FaaS Approach for Long-Term Monitoring in Rehabilitation

Serrano-Gutierrez

Ayala

Fuentes

2022

Lecture Notes in Networks and Systems

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“…The result of an activity recognition process is provided as "activity performed" or "activity not performed." 15 To recognize the completion of an activity or not, it is necessary to merge and analyze the raw data from the sensors.…”

Section: Activity Recognition Modulementioning

confidence: 99%

“…The second kind refers to the long-term knowledge that an expert can provide from the health care center to the SHS, that is, the dependency relationship between activities. 15 The prediction algorithm is based on the following rules:…”

Section: Profile Identification Modulementioning

confidence: 99%

Adapted smart home services based on smart contracts and service level agreements

Staifi

Belguidoum

2021

Concurrency and Computation

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In smart home systems (SHS), devices intercommunicate to create an intelligent environment that can monitor the inhabitant's health state and provide adapted services.However, existing health monitoring systems (HMS) do not provide adapted services to the patient autonomy degree. Furthermore, in these critical systems, the Quality of Service (QoS) aspect is very important; therefore, service level agreements (SLA) are the best solution to define and guarantee the expected QoS levels, nevertheless, existing SLA specification languages lack expressiveness in terms of user preference specification, dynamic service management and pricing. In this work, we propose an elderly health state-aware SHS to offer adapted services according to the elderly health state, it is based on three main parts: (a) the functional autonomy measurement system (SMAF) for calculating the inhabitant's profile or autonomy degree, (b) domain-specific language (DSL) for SLA that aims to increase patient-awareness through the use of preferences, facilitate the SLA management using microservices, and manage the QoS dynamically using multilevel SLA (ML-SLA) concept, and (c) smart contracts for the provision of adapted services and the verification of SLA terms.

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