1,751 research outputs found

    Active and assisted living ecosystem for the elderly

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    A novel ecosystem to promote the physical, emotional and psychic health and well-being of the elderly is presented. Our proposal was designed to add several services developed to meet the needs of the senior population, namely services to improve social inclusion and increase contribution to society. Moreover, the solution monitors the vital signs of elderly individuals, as well as environmental parameters and behavior patterns, in order to seek eminent danger situations and predict potential hazardous issues, acting in accordance with the various alert levels specified for each individual. The platform was tested by seniors in a real scenario. The experimental results demonstrated that the proposed ecosystem was well accepted and is easy to use by seniors

    Modern computing: Vision and challenges

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    Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Mobile Computing: Trend, Challenges, Trend Topics, Success Factors and Implementation Fields

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    This paper aims to explore the development of mobile computing in knowing trends, challenges, trending topics, success factors, and what fields apply to mobile computing. This study uses a systematic literature review (SLR) methodology consisting of several stages: search strategy, literature criteria, data extraction and monitoring, and data synthesis. The analysis results describing the research findings show that from the reviewed articles, it can be concluded that Mobile Computing is implemented to support and play an important role in community and organizational activities in all disciplines. Mobile computing has a very important role in the ease of use of device applications. The research results can also describe the evolution of mobile computing so that it can be studied in more depth

    Interactive visualisation of electricity usage in smart environments

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    Saving electricity is a trending topic due to the electricity challenges that are being faced globally. Smart environments are environments that are equipped with physical objects, which include computers, sensors, actuators, smartphones, and wearable devices interconnected together through the Internet of Things. The Internet of Things provides a network to achieve communication, and computation abilities to provide individuals with smart services anytime, and anywhere. Rapid developments in information technology have increased the number of smart appliances being used, leading to increased electricity usage. Devices and appliances in Smart Environments continue to consume electricity even when not in use, because of the standby function. The problems arise as the electricity consumption of the standby function accumulates to large amounts. Effective communication through visualisation of the electricity consumption in a Smart Environment provides a viable solution to reducing the consumption of electricity. This research aimed to design and developed a visualisation system that successfully communicates electricity consumption to the user using a variety of visualisation techniques. The Design Science Research Methodology was used to address the research questions and was used to iteratively design and develop an energy usage visualisation system. The visualisation system was created for the Smart Lab at the Nelson Mandela University's Department of Computing Sciences. A usability study was conducted to assess the usability and efficacy of the system. The system was found to be usable and effective in communicating power usage to potential customers, since the participants were able to complete the tasks in a short amount of time. The positive results show that visualisation can aid in communicating electricity usage to customers, resulting in a possible reduction in electricity consumption and improved decision-making.Thesis (MSc) -- Faculty of Science, School of Computer Science, Mathematics, Physics and Statistics, 202

    Design of an E-learning system using semantic information and cloud computing technologies

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    Humanity is currently suffering from many difficult problems that threaten the life and survival of the human race. It is very easy for all mankind to be affected, directly or indirectly, by these problems. Education is a key solution for most of them. In our thesis we tried to make use of current technologies to enhance and ease the learning process. We have designed an e-learning system based on semantic information and cloud computing, in addition to many other technologies that contribute to improving the educational process and raising the level of students. The design was built after much research on useful technology, its types, and examples of actual systems that were previously discussed by other researchers. In addition to the proposed design, an algorithm was implemented to identify topics found in large textual educational resources. It was tested and proved to be efficient against other methods. The algorithm has the ability of extracting the main topics from textual learning resources, linking related resources and generating interactive dynamic knowledge graphs. This algorithm accurately and efficiently accomplishes those tasks even for bigger books. We used Wikipedia Miner, TextRank, and Gensim within our algorithm. Our algorithm‘s accuracy was evaluated against Gensim, largely improving its accuracy. Augmenting the system design with the implemented algorithm will produce many useful services for improving the learning process such as: identifying main topics of big textual learning resources automatically and connecting them to other well defined concepts from Wikipedia, enriching current learning resources with semantic information from external sources, providing student with browsable dynamic interactive knowledge graphs, and making use of learning groups to encourage students to share their learning experiences and feedback with other learners.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Luis Sánchez Fernández.- Secretario: Luis de la Fuente Valentín.- Vocal: Norberto Fernández Garcí

    Digital Twins and Blockchain for IoT Management

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    We live in a data-driven world powered by sensors getting data from anywhere at any time. This advancement is possible thanks to the Internet of Things (IoT). IoT embeds common physical objects with heterogeneous sensing, actuating, and communication capabilities to collect data from the environment and people. These objects are generally known as things and exchange data with other things, entities, computational processes, and systems over the internet. Consequently, a web of devices and computational processes emerges involving billions of entities collecting, processing, and sharing data. As a result, we now have an internet of entities/things that process and produce data, an ever-growing volume that can easily exceed petabytes. Therefore, there is a need for novel management approaches to handle the previously unheard number of IoT devices, processes, and data streams. This dissertation focuses on solutions for IoT management using decentralized technologies. A massive number of IoT devices interact with software and hardware components and are owned by different people. Therefore, there is a need for decentralized management. Blockchain is a capable and promising distributed ledger technology with features to support decentralized systems with large numbers of devices. People should not have to interact with these devices or data streams directly. Therefore, there is a need to abstract access to these components. Digital twins are software artifacts that can abstract an object, a process, or a system to enable communication between the physical and digital worlds. Fog/edge computing is the alternative to the cloud to provide services with less latency. This research uses blockchain technology, digital twins, and fog/edge computing for IoT management. The systems developed in this dissertation enable configuration, self-management, zero-trust management, and data streaming view provisioning from a fog/edge layer. In this way, this massive number of things and the data they produce are managed through services distributed across nodes close to them, providing access and configuration security and privacy protection

    Recommender Systems for Online and Mobile Social Networks: A survey

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    Recommender Systems (RS) currently represent a fundamental tool in online services, especially with the advent of Online Social Networks (OSN). In this case, users generate huge amounts of contents and they can be quickly overloaded by useless information. At the same time, social media represent an important source of information to characterize contents and users' interests. RS can exploit this information to further personalize suggestions and improve the recommendation process. In this paper we present a survey of Recommender Systems designed and implemented for Online and Mobile Social Networks, highlighting how the use of social context information improves the recommendation task, and how standard algorithms must be enhanced and optimized to run in a fully distributed environment, as opportunistic networks. We describe advantages and drawbacks of these systems in terms of algorithms, target domains, evaluation metrics and performance evaluations. Eventually, we present some open research challenges in this area
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