The existence, usage and benefits of digital technologies in nursing care are relevant topics in the light of the current discussion on technologies as possible solutions to problems such as the shortage of skilled workers and the increasing demand for long-term care. A lack of good empirical overviews of existing technologies in the present literature prompted us to conduct this review. Its purpose was to map the field of digital technologies for informal and formal care that have already been explored in terms of acceptance, effectiveness and efficiency (AEE), and to show the scope of the used methods, target settings, target groups and fields of support. A systematic literature search was conducted using Medline, Scopus, CINAHL, Cochrane Library, ACM Digital Library, IEEE Xplore, the Collection of Computer Science Bibliographies, GeroLit and CareLit. In addition, project websites were manually screened for relevant publications. Seven hundred fifteen papers were included in the review. Effectiveness studies have been most frequently performed for ICT, robots and sensors. Acceptance studies often focussed on ICT, robots and EHR/EMR. Efficiency studies were generally rare. Many studies were found to have a low level of evidence. Experimental designs with small numbers and without control groups were the most common methods used to evaluate acceptance and effectiveness. Study designs with high evidence levels were most commonly found for ICT, robots and e-learning. Technologies evaluated for informal caregivers and children or indicated for formal care at home or in cross-sectoral care were rare. We recommend producing high-quality evaluations on existing digital technologies for AEE in real-life settings rather than systematic reviews with low-quality studies. More focus should be placed on research into efficiency. Future research should be devoted to a closer examination of the applied AEE evaluation methods. Policymakers should provide funding to enable large-scale, long-term evaluations of technologies in the practice of care, filling the research gaps for technologies, target settings and target groups identified in this review.

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Digital technology and nursing care: a scoping review on acceptance, effectiveness and efficiency studies of informal and formal care technologies

There has been a rapid increase in the number of Internet of Things (IoT) devices in the last few years, providing a wide range of services such as camera feeds, light controls, and door locks for remote access. Access to IoT devices, whether within the same environment or remotely via the Internet, requires proper security mechanisms in order to avoid disclosing any secure information or access privileges. Authentication, on which other security classes are built, is the most important part of IoT security. Without ensuring that the authorized party is who it claims to be, other security factors would be useless. Additionally, with the increased mobility of IoT devices, traditional authentication mechanisms, such as a username and password, are less effective. Numerous security challenges in the IoT domain have resulted in the proposal of many different approaches to authentication. Many of these methods require either carrying an authentication token, such as a smartcard, or restricting access to a particular physical location. Considering that most IoT devices contain a wide array of sensors, a large amount of contextual information can be provided. Thus, real-time security mechanisms can protect user access by, for example, utilizing contextual information to validate requests. A variety of contextual information can be retrieved to strengthen the authentication process, both at the time of access request and throughout the entire access session, without requiring user interaction, which avoids the risk of being discovered by attackers of these features. In this paper, we introduce a continuous authentication framework that integrates contextual information for user authentication in smart homes. The implementation and evaluation show that the framework can protect smart devices against unauthorized access from both anonymous and known users, either, locally or remotely, in a flexible manner and without requiring additional user intervention.

Design and Implementation of a Contextual-Based Continuous Authentication Framework for Smart Homes

Large cities around the world face numerous challenges to guarantee the quality of life of its citizens. A promising approach to cope with these problems is the concept of Smart Cities, of which the main idea is the use of Information and Communication Technologies to improve city services. Being able to simulate the execution of Smart Cities scenarios would be extremely beneficial for the advancement of the field. Such a simulator, like many others, would need to represent a large number of various agents (e.g. cars, hospitals, and gas pipelines). One possible approach for doing this in a computer system is to use the actor model as a programming paradigm so that each agent corresponds to an actor. The Erlang programming language is based on the actor model and is the most commonly used implementation of it. In this paper, we present the first version of InterSCSimulator, an open-source, extensible, large-scale Traffic Simulator for Smart Cities developed in Erlang, capable of simulating millions of agents using a real map of a large city. Future versions will be extended to address other Smart City domains.

InterSCSimulator: Large-Scale Traffic Simulation in Smart Cities Using Erlang

Context aware systems are able to adapt their behavior according to the environment in which the user is. They can be integrated into an Internet of Things (IoT) infrastructure, allowing a better perception of the user's physical environment by collecting context data from sensors embedded in devices known as smart objects. An IoT extension called the Internet of Mobile Things (IoMT) suggests new scenarios in which smart objects and IoT gateways can move autonomously or be moved easily. In a comprehensive view, Quality of Context (QoC) is a term that can express quality requirements of context aware applications. These requirements can be those related to the quality of information provided by the sensors (e.g., accuracy, resolution, age, validity time) or those referring to the quality of the data distribution service (e.g, reliability, delay, delivery time). Some functionalities of context aware applications and/or decision-making processes of these applications and their users depend on the level of quality of context available, which tend to vary over time for various reasons. Reviewing the literature, it is possible to verify that the quality of context support provided by IoT-oriented middleware systems still has limitations in relation to at least four relevant aspects: (i) quality of context provisioning; (ii) quality of context monitoring; (iii) support for heterogeneous device and technology management; (iv) support for reliable data delivery in mobility scenarios. This paper presents two main contributions: (i) a state-of-the-art survey specifically aimed at analyzing the middleware with quality of context support and; (ii) a new middleware with comprehensive quality of context support for Internet of Things Applications. The proposed middleware was evaluated and the results are presented and discussed in this article, which also shows a case study involving the development of a mobile remote patient monitoring application that was developed using the proposed middleware. This case study highlights how middleware components were used to meet the quality of context requirements of the application. In addition, the proposed middleware was compared to other solutions in the literature.

A Middleware with Comprehensive Quality of Context Support for the Internet of Things Applications.

The growing demand for performance observed in many organisations can still be considered the main motivator for the evolution of high performance computing and, more recently, cloud environments. Part of this demand regards the need to deal with large and complex datasets, called big data. Performance improvement in such environments begins to be limited by energy consumption. Workload characterisation is a well-known approach to reproducing systems' behaviour. However, there are several methodologies, techniques and parameters that can be considered for a workload characterisation. As a result, we present a differentiated survey on workload characterisation focusing on performance and energy efficiency improvement on HPC, cloud and big data environments. After an extensive review and classification of research works, our study indicates that around 56.4% of the papers reviewed offer contributions to performance and energy efficiency improvement, and the growing interest in this subject has a rate of 7.86% per year.

A survey into performance and energy efficiency in HPC, cloud and big data environments

This paper provides an approach to assessing Quality of Context (QoC) parameters in a ubiquitous Ambient Assisted Living (ALL) environment. Lack of quality can lead assisted systems to respond inappropriately, resulting in errors related to assistance or support, or putting the user at risk. QoC assessments can improve these systems and set them to perform specific actions whenever lapses in quality occur. Initially, the study presents a literature review of QoC. Then it introduces the context management architecture used. The proposal is verified with the Siafu simulator in an ALL scenario where the user's health is monitored with information about blood pressure, heart rate and body temperature. Considering some parameters, the proposed QoC assessment shall allow verifying the extent to which the context information is up-to-date, valid, accurate, complete and significant. Assessing QoC parameters and the QoC value is important and helpful to detect anomalies or inconsistencies in sensors, generate alerts, activate backup sensors, discard data with insufficient QoC, choose appropriate providers, etc.

Toward assessing Quality of Context parameters in a ubiquitous assisted environment

O objetivo deste artigo e fazer um levantamento na literatura sobre Qualidade de Contexto (QoC), propondo uma taxonomia dos temas abordados pelos trabalhos pesquisados, alem de identificar alguns desafios. O aumento da utilizacao de dispositivos portateis gerou uma demanda de informacoes do ambiente e do usuario, para que aplicacoes possam oferecer servicos mais dinâmicos e personalizados. Mas para isso, a qualidade destas informacoes e um ponto critico para atender a satisfacao dos usuarios, ponto este que e pouco abordado ate o momento. A metodologia de estudo consistiu das etapas de coleta de dados, analise de dados e sintese e representacao dos dados. Os temas que se destacaram e foram agrupados na taxonomia proposta sao: definicoes e propostas de parâmetros de QoC, alternativas para suas quantificacoes, os modelos de representacao de contexto com QoC, outros temas abordados e cenarios utilizados. Este mapeamento das publicacoes pode auxiliar as pesquisas nesta area, sendo o principal desafio a falta de uniformizacao de nomenclaturas, definicoes, quantificacao e consequentemente de modelos de representacao, o que dificulta a interoperabilidade e o compartilhamento de informacoes de contexto e de QoC.

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Taxonomia das publicações sobre Qualidade de Contexto

This paper presents an approach to the evaluation of Quality of Context (QoC) parameters in a ubiquitous Ambient Assisted Living (AAL) e-Health platform, supporting the care of people with special needs (elderly or with health problems) thus improving their quality of life. The proposal is initially verified with the Siafu simulator in an AAL scenario where the users health is monitored with information about blood pressure and body temperature. The research proceeded with the use of IoT technology, the e-Health Sensor Platform, a differentiated real environment. The experiment used the sensors: pulse and oxygen in blood, body temperature, blood pressure, patients position and falls. Just as in the simulation, and with the QoC evaluation, the completed real experiment confirmed instances of insufficient QoC and its possible causes, in addition to alerts to potential health problems. Results indicates the relevance of the QoC approach for AAL applications.

Quality of Context Evaluating Approach in AAL Environment Using IoT Technology

This paper presents an enhanced approach to the evaluation of Quality of Context (QoC) parameters in a ubiquitous Ambient Assisted Living (AAL) e-Health platform, supporting the care of people with special needs (elderly or with health problems) thus improving their quality of life. At the outset, the study presents a literature review of QoC. Then it introduces the proposed context management architecture. The proposal is initially verified with the Siafu simulator in an AAL scenario where the user's health is monitored with information about blood pressure, heart rate and body temperature. The research proceeded with the use of the e-Health Sensor Platform, a differentiated real environment. The experiment used the sensors: pulse and oxygen in blood, body temperature, blood pressure, patient's position and falls. Considering some parameters, the proposed QoC evaluation allowed verifying the extent to which the context information is up-to-date, valid, accurate, complete and significant. Just as in the simulation, and with the QoC evaluation, the completed real experiment confirmed instances of insufficient QoC and its possible causes, in addition to alerts to potential health problems. This proposal means a big social impact and a technological innovation applied to AAL, at the disposal and support of a significant number of individuals such as elderly or sick people, and with a more precise technology.

An Enhanced Quality of Context Evaluating Approach in the e-Health Sensor Platform

This paper provides an approach to assessing Quality of Context (QoC) parameters in a ubiquitous Ambient Assisted Living (AAL) environment. Initially, the study presents a literature review on QoC, generating taxonomy. Then it introduces the context management architecture used. The proposal is verified with the Siafu simulator in an AAL scenario where the user’s health is monitored with information about blood pressure, heart rate and body temperature. Considering some parameters, the proposed QoC assessment allows verifying the extent to which the context information is up-to-date, valid, accurate, complete and significant. The implementation of this proposal might mean a big social impact and a technological innovation applied to AAL, at the disposal and support of a significant number of individuals such as elderly or sick people, and with a more precise technology.

/pdf/context-management-toward-assessing-quality-of-context-25i53061dg.pdf

Debora Cabral Nazario

Papers

Toward assessing Quality of Context parameters in a ubiquitous assisted environment

Taxonomia das publicações sobre Qualidade de Contexto

Quality of Context Evaluating Approach in AAL Environment Using IoT Technology

An Enhanced Quality of Context Evaluating Approach in the e-Health Sensor Platform

Context management: toward assessing quality of context parameters in a ubiquitous ambient assisted living environment