Delivering elder-care environments utilizing TV-channel based mechanisms

In this paper, we present a smart environment for elderly. What makes the development of such system challenging is that the concept of smartness for elderly brings to the extreme the idea of invisibility of the technology. In our experience, elders are well-disposed to new technologies, provided that those will not require significant changes - namely, they are invisible - to their habits. Starting from this consideration, 200 caregivers responses were collected by questionnaire, so as to better understand elders' needs and habits. A system was subsequently developed allowing elders to access a number of "modern web services" as standard TV channels: at channel 43 there is the health status, at channel 45 the photos of the family, at 46 the agenda of the week, just to mention few of the available services. The content of such services is automatically generated by the smart devices in the environment and is managed by the caregivers (e.g., family members) by simple web apps. Fourteen families were asked to install the system in their house. The results of these experiments confirm that the proposed system is considered effective and user-friendly by elders

Development of an ambient assisted living ecosystem

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de ComputadoresThe society that we live in faces today big demographic changes. Nowadays, peo-ple live longer, and it is expected that this trend will proceed. In 2000, there were already 420 million people with more than 65 years old, which correspond to about 7% of the world population. In 2050, it is expected that this number reaches 1500 million which corresponds to about 16% of the world population. Naturally, in these circumstances, the number of disabled people will increase as well. This context brings new challenges to the traditional health care systems in Portugal and in the rest of the world. There is an urgent need to search for new solutions that will allow people to live in the best possible way, in the latest stages of life. In order to fulfill this need, it is necessary to develop systems that allow to extend their life in their favorite environment, improving their safety, autonomy, mobility and welfare. Nowadays, information and communication technologies (ICT) offer new opportunities to provide care and assistance. Ambient Assisted Living (AAL), is such a paradigm, in which technology is used as a way to improve the independ-ence and welfare of aged or disabled people at their homes. This dissertation has the purpose of contributing to providing an answer to this necessity, associated to a development of an ecosystem for Ambient Assisted Living, associated to a business model and the search for the possibility of collabo-rative networks creation, in order to look for efficient and accessible solutions for AAL services provision

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

Ambient intelligence: applications and privacy policies

Proceedings of: 12th International Conference on Practical Applications of Agents and Multi-Agent Systems, University of Salamanca (Spain), 4th-6th June, 2014. Workshop on Intelligent Systems for Context-based Information Fusion (ISCIF 2014)In this paper, we present a complete overview of Ambient Intelligence (AmI) focused in its applications, considering the involved domain and technologies. The applications include AmI at home, care of elderly and people with disabilities, healthcare, education, business, public services, leisure and entertainment. The aim of this survey of AmI’s applications is to show its socials and ethical implications and specially privacy issues. Intelligent Environments (IE) collect and process a massive amount of person-related and sensitive data. These data must ensure privacy of the users. An important concern in AmI's applications is privacy. Addressing design by privacy, an important challenge to consider is the development of an architecture that includes the different privacy policies and how can we fusion them in a specific application domain. Ensuring privacy in Intelligent Environments is a difficult problem to solve, as there are different perceptions of privacy and its role in computing for each user. In the so called ‘design by privacy’ we have to identify the relevant design issues that should be addressed for its developing. Here we present an approach to the dimensions to consider, in order to provide privacy in the design of Ambient Intelligence’s applications.This work has been supported in part by the projects: CAM “Contexts” (S2009/TIC-1485), MINECO “Falcon” (TEC2011-28626-C02-02), MINECO “Tease” (TEC2012-37832-C02-01)

Inside a Digital Experiment: Co-producing Telecare Services for Older People

The problem of the user remains central to information systems research and practice, more so given the importance now given to user-led innovation. Telecare is a much-vaunted example of e-enabled health and social care which, over the past decade or more has received considerable policy attention and investment in Europe and beyond. However, it appears that the technological opportunities offered have not been taken-up in everyday practice and that the engagement of users—service providers and end users—has been identified as a major barrier. This article presents the experience of a European level project that sought to use a form of co-production to engage users in the development of a telecare system for older people. The outcome was a platform with infrastructural properties and a service-orientated architecture better able to support subsequent innovation in use

Design for energy-efficient and reliable fog-assisted healthcare IoT systems

Cardiovascular disease and diabetes are two of the most dangerous diseases as they are the leading causes of death in all ages. Unfortunately, they cannot be completely cured with the current knowledge and existing technologies. However, they can be effectively managed by applying methods of continuous health monitoring. Nonetheless, it is difficult to achieve a high quality of healthcare with the current health monitoring systems which often have several limitations such as non-mobility support, energy inefficiency, and an insufficiency of advanced services. Therefore, this thesis presents a Fog computing approach focusing on four main tracks, and proposes it as a solution to the existing limitations. In the first track, the main goal is to introduce Fog computing and Fog services into remote health monitoring systems in order to enhance the quality of healthcare. In the second track, a Fog approach providing mobility support in a real-time health monitoring IoT system is proposed. The handover mechanism run by Fog-assisted smart gateways helps to maintain the connection between sensor nodes and the gateways with a minimized latency. Results show that the handover latency of the proposed Fog approach is 10%-50% less than other state-of-the-art mobility support approaches. In the third track, the designs of four energy-efficient health monitoring IoT systems are discussed and developed. Each energy-efficient system and its sensor nodes are designed to serve a specific purpose such as glucose monitoring, ECG monitoring, or fall detection; with the exception of the fourth system which is an advanced and combined system for simultaneously monitoring many diseases such as diabetes and cardiovascular disease. Results show that these sensor nodes can continuously work, depending on the application, up to 70-155 hours when using a 1000 mAh lithium battery. The fourth track mentioned above, provides a Fog-assisted remote health monitoring IoT system for diabetic patients with cardiovascular disease. Via several proposed algorithms such as QT interval extraction, activity status categorization, and fall detection algorithms, the system can process data and detect abnormalities in real-time. Results show that the proposed system using Fog services is a promising approach for improving the treatment of diabetic patients with cardiovascular disease