IoT and CPS applications based on wearable devices. A case study: Monitoring of elderly and infirm patients

Quarto, Alessandro; Soldo, Domenico; Gemmano, Simona; Dario, Rita; Lecce, Vincenzo Di; Guaragnella, Cataldo; Cardellicchio, Angelo; Lombardi, Angela

doi:10.1109/eesms.2017.8052698

Cited by 4 publications

(2 citation statements)

References 22 publications

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“…AAL technologies may contribute to the preservation of the quality of life of aging population in an affordable way, thus, decreasing the need of social and health-care services [30]. AAL includes systems and services designed to: compensate the age related physical and psychological limitations, guarantee autonomy and safety to the elderly people; constantly monitoring their activities and providing help in case of emergency; improve their life quality, allowing them to continue their life in their own environment with a constant remote supervision also in case of specific diseases [31].…”

Section: Retirement Home Monitoringmentioning

confidence: 99%

SMACovid-19 – Autonomous Monitoring System for Covid-19

Fernandes

Barbosa

2021

Communications in Computer and Information Science

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Atualmente, existe uma pandemia global, COVID-19, que pode provocar consequências devastadoras para a saúde humana. Além disso, pessoas idosas têm uma probabilidade maior de sofrerem os efeitos mais severos da doença. wearable devices podem monitorizar parâmetros biológicos/físicos, e uma análise de previsão aos dados resultantes deve permitir a identificação mais rápida possível de pessoas que possam estar infetadas com o vírus. Para criar um sistema com estas capacidades, desenvolveram-se os módulos health data provider e data analysis para recolher os dados e fazer as previsões, com base nesses dados, respetivamente. A plataforma FIWARE foi usada para implementar o backend do sistema, através de módulos open source ready-to-use para gerir os dados no sistema. Os médicos do Hospital da Terra Quente definiram os parâmetros biológicos/físicos de interesse e, considerando os diferentes tipos de variáveis, implementaram-se três tipos distintos de previsões: última observação, estimador linear de tendência e método aditivo Holt-Winters. As previsões obtidas são usadas para classificar o estado de uma pessoa, para um cenário de pior caso possível: provável que esteja infetado com o vírus ou provável que não esteja infetado com o vírus. As regras de classificação foram definidas pelos médicos do Hospital da Terra Quente.Os resultados obtidos são promissores e trabalho futuro pode ser feito para melhorar o sistema na inclusão de mais fontes de dados, ajuste dos métodos de previsão e na introdução de novas metodologias de classificação final.

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Section: Retirement Home Monitoringmentioning

confidence: 99%

SMACovid-19 – Autonomous Monitoring System for Covid-19

Fernandes

Barbosa

2021

Communications in Computer and Information Science

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“…the physical world are often represented by events [3], [4]. The data obtained by multi-modal sensing node are called multimodal data, and the event model is proposed based on multi-modal data and time and space attribute.…”

Section: Introductionmentioning

confidence: 99%

Efficient Matching of Multi-Modal Sensing Nodes for Collaborative Sense Optimization of Composite Events

2019

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Composite events are sense maximizes collaboration through multiple sensors. Efficient matching of multi-modal sensing nodes in multi-composite events is always a thorny problem. In this paper, the composite event sensing model is first proposed, and then the collaborative-sense problem of multi-modal sensing nodes is translated into a binary matching problem. For these multi-class sensors and multi-class compound events scene, a pruning-grafting and parallel strategy be adopted, which can speed up the traversal speed and find the maximum matching edge quickly. For multi-nodes selection, the distance of the composite event constraints into binarily weighted matching. A collaborative-sense intelligent matching algorithm is suggested. It takes collaborative in various kinds of nodes matching combining with the distribution of the composite event itself around the nodes. Combined with the random distribution of various sensor nodes and composite events, the matching rate of some sensor nodes is sacrificed for the overall event efficiency. Compare to parallel algorithms, it has another effect on perceived efficiency. Finally, by comparing with other algorithms, CSSMA and other proposed algorithms have a certain advantage in the inclusive sense efficiency. In terms of composite events collaborative-sense, this work has nice theoretical significance and practical value.

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