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Wireless Alert technology for Elderly Care at Home 1

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16th international conference on Ubiquitous computing and Ambient Intelligence

作者： Poulin, Sebastien Obradovic, Natasa Lacerte, Julie Provencher, Veronique Pigot, Helene Giroux, Sylvain Ngankam, Hubert Univ Sherbrooke Lab DOMUS Departement dinformat Sherbrooke PQ Canada Univ Sherbrooke Ecole Readaptat Fac Med Sherbrooke PQ Canada

ISBN: (数字)9783031775710

ISBN: (纸本)9783031775703;9783031775710

Ambient Assistance uses the internet of things (IoT) technologies to monitor elderly people at home, improving their quality of life through wearable sensors, audio-video technology, and ubiquitous computing. Social isolation, a critical issue for seniors, poses a greater risk to mortality than obesity or physical inactivity, threatening the health and independence of adults over 65. While commercial solutions exist, they are costly and often disregard user context and caregiver needs. this article presents a system that prioritizes user autonomy by notifying the elderly adult before caregivers. It supports various devices and provides a platform for exploring wearable sensors for the elderly, with the aim of reducing social isolation by reassuring loved ones when the user is in a safe area. the system offers caregivers contextual alerts, real-time visualization, and two-way communication when the elderly person leaves a designated safe zone. Our study consisted of two phases: laboratory tests to validate system components and interfaces, followed by a 2-year longitudinal study with an elderly participant and their caregiver, analyzing long-term usage patterns and real-world effectiveness. Our technological findings demonstrate the system's robustness and efficiency. We achieved an 80% uptime over the 2-year period, with an average notification delay of less than 2 s. the system successfully integrated with various IoT devices, including smartwatches, door sensors, and motion detectors. Key challenges included minimizing false alarms, which were reduced to less than 1% using MapReduce-based data processing algorithms, and ensuring seamless operation in diverse network conditions. Although promising, the limitations of the study require further research with a larger sample size. this project contributes to the field of ambient assistance by offering a distributed lambda architecture and a technologically advanced approach to combating social isolation among the elde

关键词： Ambient Assisted Living internet of things Social Isolation distributed Lambda Architecture

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Employing Convolutional Neural Network for IoT Healthcare Attack Detection in Intensive Care Unit 6

Employing Convolutional Neural Network for IoT Healthcare At...

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6th international conference on Contemporary computing and Informatics, IC3I 2023

作者： Sharma, Ishu Kaushik, Keshav Pahuja, Vanshika Chhabra, Gunjan Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of Computer Science University of Petroleum and Energy Studies Dehradun India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350304480

the internet of things helps the healthcare sector to embrace the methodologies with emerging technologies and facilitate technological change from traditional to highly equipped technology. Some of the frequent uses of the internet of things in healthcare include monitoring patient healthcare, enhancing proper healthcare and searching medical resources. this digitalization and increase in the use of internet-connected sensors in healthcare have taken to a new height through advancement in technology. But security and efficient use of IoT in healthcare is still a critical challenge. Cyber-attacks are very common at present with the main motive of hacking private patient data and stealing other health information from the devices equipped for fetching patient's well-being. this research paper shows the employment of a convolutional neural network for detecting attacks on Intensive care units in hospitals. the results achieved by the convolutional neural network technique prove that deep learning methodologies are a promising solution to provide reliable and trustworthy communication in healthcare sectors with the internet of things devices. © 2023 IEEE.

关键词： Convolutional Neural Networks Health care Intensive Care Unit internet of things Security

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A Comprehensive Survey on Role of Fog computing and Need for Semantic technology in Modern computing Platform 7

A Comprehensive Survey on Role of Fog Computing and Need for...

引用

7th international conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Amshavalli, R.S. Kalaivani, J. SRM Institute of Science and Technology Dept of Computing Technology India

ISBN: (纸本)9798350397253

Fog computing can be considered as one of the trending paradigms, as it has the potential of bringing the end devices closer to the cloud. Fog plays a vital role in bridging the gap between the end user and cloud with low latency, which in turn helps in the better realization of Intelligent IoT. the emergence of IoT applications has paved the way for Semantic Interoperability (SI). Instead of storing raw data, SI attempts to annotate these data with semantic information that ensures smart management of huge volumes of data generated by IoT. Nevertheless, such semantic reasoning in the cloud can be computationally expensive as it deals with enormous amount of incoming data. So, distributing the procedure of semantic reasoning among a hierarchy of distributed fog nodes than in a centralized cloud will gives the better result. this research study investigates how semantics work in fog computing © 2023 IEEE.

关键词： internet of things

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Data Security in Cloud using Advanced Encryption Standard 6

Data Security in Cloud using Advanced Encryption Standard

引用

6th international conference on Inventive Computation Technologies, ICICT 2023

作者： Basha, Shaik Mahaboob Rishik, Vissa Krishna, V. Jaya Naga Kavitha, S. Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Greenfields Vaddeswaram Guntur522302 India

ISBN: (纸本)9798350398496

this research study gives an overview on cloud security to understand the security concerns and solutions. the internet has revolutionised how people live and work, and cloud computing is considered as the next logical progression. Cloud security is a series of security precautions employed to safeguard cloud-based architecture, services, and information. these precautions cover client and hardware authentication, information and resource access management, and data confidentiality. People who utilize the internet should also be concerned about cloud computing security. Despite the hype, cloud computing has also created new vulnerabilities, such as unwanted access to individual's personal data and the ability to control sensitive information, which includes an underlying weak point. the encryption algorithm guarantees that the data will be kept confidential while in transit, ensuring that it can only be decoded by the authorised user. Advanced Encryption Standard (AES) is the symmetric encryption algorithm that is more frequently utilisedandmore generally known nowadays. Here, the data may be accessed and exploited in a variety of ways, and it is also critical to understand the dangers. this study discusses about the different ways to guarantee that user data is secure and confidential. Finally, the future potential strategies for cloud security are examined. Moreover, the cloud computing will not only save the world, it will alter the way users engage with digital/mobile applications. © 2023 IEEE.

关键词： Cloud computing architecture

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Joint Optimization of Service Migration and Resource Management for Vehicular Edge computing 19

Joint Optimization of Service Migration and Resource Managem...

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19th Annual international conference on distributed computing in Smart Systems and the internet of things, DCOSS-IoT 2023

作者： Lan, Dapeng Taherkordi, Amir Eliassen, Frank Liu, Lei Yuan, Xiaoming University of Oslo Norway Guangzhou Institute of Technology Xidian University Guangzhou510555 China Northeastern University Qinhuangdao066004 China

ISBN: (纸本)9798350346497

the integration of edge computing and vehicle networks with future communications (e.g., 5G/6G networks) enables computation-intensive and delay-sensitive applications, such as autonomous driving. However, the mobility of end devices and vehicles with context switching brings a considerable Quality of Service (QoS) degradation and interruptions in edge services provisioning. Predicting the end-user mobility and context switching enable edge nodes to migrate services proactively to guarantee the QoS. But the cost maybe significant if the prediction is wrong. Service migration seems to be an effective way to minimize service disruptions and maintain service continuity. Service migration can be performed in two ways: proactive and reactive. Most of existing works focus on either reactive or proactive service migration models without considering resource usage efficiency. In this paper, we consider the combination of reactive and proactive service migration and propose a novel framework for joint optimization of service migration and resource management for vehicular edge computing by leveraging reinforcement learning (RL) as an emerging technique. We construct an optimization problem to reduce migration costs in terms of latency and energy usage. Finally, we present Multi-Armed Bandit (MAB) methods for solving the optimization issue. Rigorous theoretical analysis and extensive evaluations, combining both testbed and numerical simulation, demonstrate the superior performance of the proposed intelligent service migration framework in vehicular edge computing environments. © 2023 IEEE.

关键词： Reinforcement learning

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Personalized Self Adaptive internet-of-things Enabled Sustainable Healthcare Architecture for Digital Transformation 6

Personalized Self Adaptive Internet-of-Things Enabled Sustai...

引用

6th international conference on Advanced computing and Communication Technologies for High Performance Applications (ACCthPA)

作者： Bhadula, Shuchi Sharma, Sachin Graph Era Deemed Be Univ Dept Comp Sci & Engn Dehra Dun Uttarakhand India

ISBN: (纸本)9798350398441

As the world undergoes digital transformation, the internet of things (IoT) has shown increasing trends in numerous sectors for cost-effective, efficient, and qualitydriven services. the usage of the internet of things to enable a sustainable healthcare architecture is proposed as a costeffective way to provide better and more real-time healthcare services. Healthcare digital transformation is the process of using digital technology to create new or alter existing business processes, culture, and customer experiences in order to satisfy changing business and market demands. Sustainable healthcare design provides high-quality care while reducing environmental impact, is cost-effective in the present and future, and has a positive social impact. Healthcare architectures can use the internet of things to be more watchful and proactive in their interactions with patients. Wheelchairs, defibrillators, nebulizers, oxygen pumps, and other monitoring devices are all tracked in real time utilizing IoT devices with sensors. Several advantages and obstacles are studied in order to foresee the IoT enabled healthcare architecture integration in future medical research for digital transformation.

关键词： Personalized Self Adaptive internet-of-things Sustainable Healthcare Architecture Digital Transformation

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Cloud computing Adoption in Pre-tertiary Malaysian Education Institution 4

Cloud Computing Adoption in Pre-tertiary Malaysian Education...

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4th international conference on Emerging Smart Technologies and Applications (eSmarTA)

作者： Manimaran, Jotheehwary Alsamman, Mohammed Mohammed, Fathey Fazea, Yousef Ghazali, Osman Inchcape Shipping Serv Dept Informat Technol Shah Alam 40150 Selangor Malaysia Univ Utara Malaysia Sch Comp Sintok 06010 Kedah Malaysia Sunway Univ Dept Business Analyt Subang Jaya 47500 Selangor Malaysia Marshall Univ Dept Comp Sci & Elect Engn 1 John Marshall Dr Huntington WV 25755 USA

ISBN: (纸本)9798350354140;9798350354133

Cloud computing has created a new concept to deal with software services and hardware infrastructure. Some benefits are immediate;for instance, it allows students to share their information easily and to discover new experiences in the education system. However, despite the comprehensive literature, there are still limited studies related to the applied factors that influence the adoption of cloud technology at pre-tertiary education institutions. this paper attempts to enhance the understanding of related factors affecting the adoption of cloud computing in the educational context of developing nations. Also, an interpretive paradigm with a quantitative research method to investigate the main enablers of and barriers to cloud computing adoption at Malaysian Institutions. Six factors are studied in this study namely, Awareness, Network Connectivity, Scalability, Data Security, Staff Training and Budget. A questionnaire survey was conducted with a select group of educators from pretertiary educational private and public institutions in Malaysia. the educators gauge their opinions on the level of significance of each factor affecting cloud computing in their institution using a 5-point scale. Out of 100 questionnaire sets distributed using Google Forms, 70 valid responses were extracted as the collected data. this data was analyzed descriptively. the results of the analysis found that most of the public schools do not have reliable and stable internet connections and private school internet connections are somewhat reliable which affects most schools that do not adopt cloud computing as well. Limited finance resources and concerns about data privacy and infrastructure stability are other considerable factors that have made the institution not adopt cloud computing till now. the impact of this research will be felt simultaneously to guide institutions in developing strategies and policies that promote successful cloud computing adoption.

关键词： Cloud computing pre-tertiary education Malaysia Adoption

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Towards a Framework for Analyzing the Suitability of DLTs for Integration in the IoT 5

Towards a Framework for Analyzing the Suitability of DLTs fo...

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5th international conference on Blockchain computing and Applications, BCCA 2023

作者： Perscheid, Guido Moormann, Jurgen Center for Deep Tech Innovation JadenX GmbH Berlin Germany Frankfurt School of Finance & Management Management Department Frankfurt a.M. Germany

ISBN: (纸本)9798350339239

the internet of things (IoT) is marked by the presence of a versatile network of devices employing various forms of communication and data types. Due to their distributed nature and the generation of extensive data, IoT nodes often encounter obstacles such as hardware and storage limitations, security vulnerabilities, and lack of interoperability. To mitigate these challenges, researchers have proposed the integration of distributed Ledger Technologies (DLTs), such as blockchain or Directed Acyclic Graph (DAG). To this end, researchers have begun analyzing the applicability of DLTs for IoT applications on a case-specific basis. However, DLTs differ with respect to the consensus protocols implied. Hence, there is a need for developing a framework defining categories for evaluating the integration of different DLT consensus protocols for IoT applications. this research-in-progress paper should be seen as a first approach to a framework that can evaluate the suitability of different DLTs for IoT applications. © 2023 IEEE.

关键词： internet of things

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2024 international conference on Emerging Smart computing and Informatics, ESCI 2024

2024 International Conference on Emerging Smart Computing an...

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6th IEEE international conference on Emerging Smart computing and Informatics, ESCI 2024

ISBN: (纸本)9798350306613

the proceedings contain 192 papers. the topics discussed include: reducing gender and ethnicity bias in personality trait prediction;MDLGO: integrated multimodal deep learning framework for enhanced precision in glaucoma diagnosis using OCT A-scans;advancing manufacturing energy efficiency: the role of AI and web-based tools;integrated healthcare system for saline monitoring, patient communication, and heart disease prediction using IoT and machine learning algorithms;IoT based real time drainage monitoring system;software defect prediction by logistic regression with gradient descent cost computation;ONU: A reinforcement load balancing approach for resource-aware task allocation in distributed systems;a novel approach using feature fusion for android malware detection and classification;and graph based analysis technique for identification of key functionalities in malicious IoT binaries.

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Scaling Machine Learning at the Edge-Cloud: A distributed computing Perspective 19

Scaling Machine Learning at the Edge-Cloud: A Distributed Co...

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19th Annual international conference on distributed computing in Smart Systems and the internet of things, DCOSS-IoT 2023

作者： Marozzo, Fabrizio Orsino, Alessio Talia, Domenico Trunfio, Paolo Dimes University of Calabria Rende Italy

ISBN: (纸本)9798350346497

the widespread diffusion of internet of things (IoT) devices has led to an exponential growth in the volume of data generated at the edge of the network. With the rapid spread of machine learning (ML)-based applications, performing compute and resource-intensive learning tasks at the edge has become a critical issue, resulting in the need for scalable and efficient solutions that can overcome the resource constraints of edge devices. this paper analyzes the problem of scaling ML applications and algorithms at the edge-cloud continuum from a distributed computing perspective. In particular, we first highlight the limitations of traditional distributed architectures (e.g., clusters, clouds, and HPC systems) when running ML applications that use data generated at the edge. Next, we discuss how to enable traditional ML algorithms combining the benefits of edge computing, such as low-latency processing and privacy preservation of personal user data, with those of cloud computing, such as virtually unlimited computational and storage capabilities. Our analysis provides insights into how properly separated parts of a ML application can be deployed across edge-cloud architectures in order to optimize its execution. More-over, examples of ML applications and algorithms appropriately adapted for the edge-cloud continuum are shown. © 2023 IEEE.

关键词： internet of things

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