MoSIoT: Modeling and Simulating IoT Healthcare-Monitoring Systems for People with Disabilities

The need to remotely monitor people with disabilities has increased due to growth in their number in recent years. The democratization of Internet of Things (IoT) devices facilitates the implementation of healthcare-monitoring systems (HMSs) that are capable of supporting disabilities and diseases....

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:International journal of environmental research and public health Ročník 18; číslo 12; s. 6357
Hlavní autoři: Meliá, Santiago, Nasabeh, Shahabadin, Luján-Mora, Sergio, Cachero, Cristina
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 11.06.2021
MDPI
Témata:
ISSN:1660-4601, 1661-7827, 1660-4601
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:The need to remotely monitor people with disabilities has increased due to growth in their number in recent years. The democratization of Internet of Things (IoT) devices facilitates the implementation of healthcare-monitoring systems (HMSs) that are capable of supporting disabilities and diseases. However, to achieve their full potential, these devices must efficiently address the customization demanded by different IoT HMS scenarios. This work introduces a new approach, called Modeling Scenarios of Internet of Things (MoSIoT), which allows healthcare experts to model and simulate IoT HMS scenarios defined for different disabilities and diseases. MoSIoT comprises a set of models based on the model-driven engineering (MDE) paradigm, which first allows simulation of a complete IoT HMS scenario, followed by generation of a final IoT system. In the current study, we used a real scenario defined by a recognized medical publication for a patient with Alzheimer’s disease to validate this proposal. Furthermore, we present an implementation based on an enterprise cloud architecture that provides the simulation data to a commercial IoT hub, such as Azure IoT Central.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1660-4601
1661-7827
1660-4601
DOI:10.3390/ijerph18126357