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Employing Information and Communications Technologies in Homes and Cities for the Health and Well-Being of Older People
YesHe X and Sheriff RE (Eds.) Employing ICT in Homes and Cities for the Health and Well-Being of Older People. Workshop Proceedings of ICT4HOP’16. 15-17 Aug 2016. Sichuan University, Chengdu, China.British Council, Researcher Links, Newton Fund, NSF
A Comprehensive Analysis of Blockchain Applications for Securing Computer Vision Systems
Blockchain (BC) and Computer Vision (CV) are the two emerging fields with the
potential to transform various sectors.The ability of BC can help in offering
decentralized and secure data storage, while CV allows machines to learn and
understand visual data. This integration of the two technologies holds massive
promise for developing innovative applications that can provide solutions to
the challenges in various sectors such as supply chain management, healthcare,
smart cities, and defense. This review explores a comprehensive analysis of the
integration of BC and CV by examining their combination and potential
applications. It also provides a detailed analysis of the fundamental concepts
of both technologies, highlighting their strengths and limitations. This paper
also explores current research efforts that make use of the benefits offered by
this combination. The effort includes how BC can be used as an added layer of
security in CV systems and also ensure data integrity, enabling decentralized
image and video analytics using BC. The challenges and open issues associated
with this integration are also identified, and appropriate potential future
directions are also proposed
Emergent situations for smart cities: A survey
A smart city is a community that uses communication and information technology to improve sustainability, livability, and feasibility. As any community, there are always unexpected emergencies, which must be treated to preserve the regular order. However, a smart system is needed to be able to respond effectively to these emergent situations. The contribution made in this survey is twofold. Firstly, it provides a comprehensive exhaustive and categorized overview of the existing surveys for smart cities. The categorization is based on several criteria such as structures, benefits, advantages, applications, challenges, issues, and future directions. Secondly, it aims to analyze several studies with respect to emergent situations and management to smart cities. The analysis is based on several factors such as the challenges and issues discussed, the solutions proposed, and opportunities for future research. The challenges include security, privacy, reliability, performance, scalability, heterogeneity, scheduling, resource management, and latency. Few studies have investigated the emergent situations of smart cities and despite the importance of latency factor for smart city applications, it is rarely discussed
SHELDON Smart habitat for the elderly.
An insightful document concerning active and assisted living under different perspectives: Furniture and habitat, ICT solutions and Healthcare
Human Digital Twin: A Survey
Digital twin has recently attracted growing attention, leading to intensive
research and applications. Along with this, a new research area, dubbed as
"human digital twin" (HDT), has emerged. Similar to the conception of digital
twin, HDT is referred to as the replica of a physical-world human in the
digital world. Nevertheless, HDT is much more complicated and delicate compared
to digital twins of any physical systems and processes, due to humans' dynamic
and evolutionary nature, including physical, behavioral, social, physiological,
psychological, cognitive, and biological dimensions. Studies on HDT are
limited, and the research is still in its infancy. In this paper, we first
examine the inception, development, and application of the digital twin
concept, providing a context within which we formally define and characterize
HDT based on the similarities and differences between digital twin and HDT.
Then we conduct an extensive literature review on HDT research, analyzing
underpinning technologies and establishing typical frameworks in which the core
HDT functions or components are organized. Built upon the findings from the
above work, we propose a generic architecture for the HDT system and describe
the core function blocks and corresponding technologies. Following this, we
present the state of the art of HDT technologies and applications in the
healthcare, industry, and daily life domain. Finally, we discuss various issues
related to the development of HDT and point out the trends and challenges of
future HDT research and development
Estimation of the QoE for video streaming services based on facial expressions and gaze direction
As the multimedia technologies evolve, the need to control their quality becomes even more important making the Quality of Experience (QoE) measurements a key priority. Machine Learning (ML) can support this task providing models to analyse the information extracted by the multimedia. It is possible to divide the ML models applications in the following categories:
1) QoE modelling: ML is used to define QoE models which provide an output (e.g., perceived QoE score) for any given input (e.g., QoE influence factor).
2) QoE monitoring in case of encrypted traffic: ML is used to analyze passive traffic monitored data to obtain insight into degradations perceived by end-users.
3) Big data analytics: ML is used for the extraction of meaningful and useful information from the collected data, which can further be converted to actionable knowledge and utilized in managing QoE.
The QoE estimation quality task can be carried out by using two approaches: the objective approach and subjective one. As the two names highlight, they are referred to the pieces of information that the model analyses. The objective approach analyses the objective features extracted by the network connection and by the used media. As objective parameters, the state-of-the-art shows different approaches that use also the features extracted by human behaviour. The subjective approach instead, comes as a result of the rating approach, where the participants were asked to rate the perceived quality using different scales. This approach had the problem of being a time-consuming approach and for this reason not all the users agree to compile the questionnaire. Thus the direct evolution of this approach is the ML model adoption. A model can substitute the questionnaire and evaluate the QoE, depending on the data that analyses. By modelling the human response to the perceived quality on multimedia, QoE researchers found that the parameters extracted from the users could be different, like Electroencephalogram (EEG), Electrocardiogram (ECG), waves of the brain. The main problem with these techniques is the hardware. In fact, the user must wear electrodes in case of ECG and EEG, and also if the obtained results from these methods are relevant, their usage in a real context could be not feasible. For this reason, my studies have been focused on the developing of a Machine Learning framework completely unobtrusively based on the Facial reactions
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