14,819 research outputs found
On the Deployment of Healthcare Applications over Fog Computing Infrastructure
Fog computing is considered as the most promising enhancement of the traditional cloud computing paradigm in order to handle potential issues introduced by the emerging Interned of Things (IoT) framework at the network edge. The heterogeneous nature, the extensive distribution and the hefty number of deployed IoT nodes will disrupt existing functional models, creating confusion. However, IoT will facilitate the rise of new applications, with automated healthcare monitoring platforms being amongst them. This paper presents the pillars of design for such applications, along with the evaluation of a working prototype that collects ECG traces from a tailor-made device and utilizes the patient's smartphone as a Fog gateway for securely sharing them to other authorized entities. This prototype will allow patients to share information to their physicians, monitor their health status independently and notify the authorities rapidly in emergency situations. Historical data will also be available for further analysis, towards identifying patterns that may improve medical diagnoses in the foreseeable future
A Methodology for Trustworthy IoT in Healthcare-Related Environments
The transition to the so-called retirement years, comes with the freedom to pursue old passions
and hobbies that were not possible to do in the past busy life. Unfortunately, that freedom
does not come alone, as the previous young years are gone, and the body starts to feel the
time that passed. The necessity to adapt elder way of living, grows as they become more prone
to health problems. Often, the solution for the attention required by the elders is nursing
homes, or similar, that take away their so cherished independence.
IoT has the great potential to help elder citizens stay healthier at home, since it has the
possibility to connect and create non-intrusive systems capable of interpreting data and act
accordingly. With that capability, comes the responsibility to ensure that the collected data is
reliable and trustworthy, as human wellbeing may rely on it. Addressing this uncertainty is the
motivation for the presented work.
The proposed methodology to reduce this uncertainty and increase confidence relies on
a data fusion and a redundancy approach, using a sensor set. Since the scope of wellbeing
environment is wide, this thesis focuses its proof of concept on the detection of falls inside
home environments, through an android app using an accelerometer sensor and a micro-
phone. The experimental results demonstrates that the implemented system has more than
80% of reliable performance and can provide trustworthy results. Currently the app is being
tested also in the frame of the European Union projects Smart4Health and Smart Bear.A transição para os chamados anos de reforma, vem com a liberdade de perseguir velhas pai-
xões e passatempos que na passada vida ocupada não eram possÃveis de realizar. Infelizmente,
essa liberdade não vem sozinha, uma vez que os anos jovens anteriores terminaram, e o corpo
começa a sentir o tempo que passou. A necessidade de adaptar o modo de vida dos menos
jovens, cresce à medida que estes se tornam mais propensos a problemas de saúde. Muitas
vezes, a solução para a atenção que os mais idosos necessitam são os lares de idosos, ou
similares, que lhes tiram a tão querida independência.
IoT tem o grande potencial de ajudar os cidadãos idosos a permanecerem mais saudá-
veis em casa, uma vez que tem a possibilidade de se ligar e criar sistemas não intrusivos capa-
zes de interpretar dados e agir em conformidade. Com essa capacidade, vem a responsabili-
dade de assegurar que os dados recolhidos são fiáveis e de confiança, uma vez que o bem-
estar humano possa depender dos mesmos. Abordar esta incerteza é a motivação para o tra-
balho apresentado.
A metodologia proposta para reduzir esta incerteza e aumentar a confiança no sistema
baseia-se numa fusão de dados e numa abordagem de redundância, utilizando um conjunto
de sensores. Uma vez que o assunto de bem-estar e saúde é vasto, esta tese concentra a sua
prova de conceito na deteção de quedas dentro de ambientes domésticos, através de uma
aplicação android, utilizando um sensor de acelerómetro e um microfone. Os resultados expe-
rimentais demonstram que o sistema implementado tem um desempenho superior a 80% e
pode fornecer dados fiáveis. Atualmente a aplicação está a ser testada também no âmbito dos
projetos da União Europeia Smart4Health e Smart Bear
RFID Localisation For Internet Of Things Smart Homes: A Survey
The Internet of Things (IoT) enables numerous business opportunities in
fields as diverse as e-health, smart cities, smart homes, among many others.
The IoT incorporates multiple long-range, short-range, and personal area
wireless networks and technologies into the designs of IoT applications.
Localisation in indoor positioning systems plays an important role in the IoT.
Location Based IoT applications range from tracking objects and people in
real-time, assets management, agriculture, assisted monitoring technologies for
healthcare, and smart homes, to name a few. Radio Frequency based systems for
indoor positioning such as Radio Frequency Identification (RFID) is a key
enabler technology for the IoT due to its costeffective, high readability
rates, automatic identification and, importantly, its energy efficiency
characteristic. This paper reviews the state-of-the-art RFID technologies in
IoT Smart Homes applications. It presents several comparable studies of RFID
based projects in smart homes and discusses the applications, techniques,
algorithms, and challenges of adopting RFID technologies in IoT smart home
systems.Comment: 18 pages, 2 figures, 3 table
Middleware Technologies for Cloud of Things - a survey
The next wave of communication and applications rely on the new services
provided by Internet of Things which is becoming an important aspect in human
and machines future. The IoT services are a key solution for providing smart
environments in homes, buildings and cities. In the era of a massive number of
connected things and objects with a high grow rate, several challenges have
been raised such as management, aggregation and storage for big produced data.
In order to tackle some of these issues, cloud computing emerged to IoT as
Cloud of Things (CoT) which provides virtually unlimited cloud services to
enhance the large scale IoT platforms. There are several factors to be
considered in design and implementation of a CoT platform. One of the most
important and challenging problems is the heterogeneity of different objects.
This problem can be addressed by deploying suitable "Middleware". Middleware
sits between things and applications that make a reliable platform for
communication among things with different interfaces, operating systems, and
architectures. The main aim of this paper is to study the middleware
technologies for CoT. Toward this end, we first present the main features and
characteristics of middlewares. Next we study different architecture styles and
service domains. Then we presents several middlewares that are suitable for CoT
based platforms and lastly a list of current challenges and issues in design of
CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268,
Digital Communications and Networks, Elsevier (2017
Middleware Technologies for Cloud of Things - a survey
The next wave of communication and applications rely on the new services
provided by Internet of Things which is becoming an important aspect in human
and machines future. The IoT services are a key solution for providing smart
environments in homes, buildings and cities. In the era of a massive number of
connected things and objects with a high grow rate, several challenges have
been raised such as management, aggregation and storage for big produced data.
In order to tackle some of these issues, cloud computing emerged to IoT as
Cloud of Things (CoT) which provides virtually unlimited cloud services to
enhance the large scale IoT platforms. There are several factors to be
considered in design and implementation of a CoT platform. One of the most
important and challenging problems is the heterogeneity of different objects.
This problem can be addressed by deploying suitable "Middleware". Middleware
sits between things and applications that make a reliable platform for
communication among things with different interfaces, operating systems, and
architectures. The main aim of this paper is to study the middleware
technologies for CoT. Toward this end, we first present the main features and
characteristics of middlewares. Next we study different architecture styles and
service domains. Then we presents several middlewares that are suitable for CoT
based platforms and lastly a list of current challenges and issues in design of
CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268,
Digital Communications and Networks, Elsevier (2017
Trustworthy Federated Learning: A Survey
Federated Learning (FL) has emerged as a significant advancement in the field
of Artificial Intelligence (AI), enabling collaborative model training across
distributed devices while maintaining data privacy. As the importance of FL
increases, addressing trustworthiness issues in its various aspects becomes
crucial. In this survey, we provide an extensive overview of the current state
of Trustworthy FL, exploring existing solutions and well-defined pillars
relevant to Trustworthy . Despite the growth in literature on trustworthy
centralized Machine Learning (ML)/Deep Learning (DL), further efforts are
necessary to identify trustworthiness pillars and evaluation metrics specific
to FL models, as well as to develop solutions for computing trustworthiness
levels. We propose a taxonomy that encompasses three main pillars:
Interpretability, Fairness, and Security & Privacy. Each pillar represents a
dimension of trust, further broken down into different notions. Our survey
covers trustworthiness challenges at every level in FL settings. We present a
comprehensive architecture of Trustworthy FL, addressing the fundamental
principles underlying the concept, and offer an in-depth analysis of trust
assessment mechanisms. In conclusion, we identify key research challenges
related to every aspect of Trustworthy FL and suggest future research
directions. This comprehensive survey serves as a valuable resource for
researchers and practitioners working on the development and implementation of
Trustworthy FL systems, contributing to a more secure and reliable AI
landscape.Comment: 45 Pages, 8 Figures, 9 Table
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