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BITS: A Blockchain-driven intelligent Scheme for Telesurgery System

BITS: A Blockchain-driven Intelligent Scheme for Telesurgery...

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international conference on Computer, Information and Telecommunication Systems (CITS)

作者： Rajesh Gupta Urvish Thakker Sudeep Tanwar Mohammad S. Obaidat Kuei-Fang Hsiao Department of Computer Science and Engineering Nirma University Ahmedabad Gujarat India College of Computing and Information University of Sharjah UAE King Abdullah II School of IT University of Jordan Jordan University of Science and Technology Beijing China Department of Information Systems University of Sharjah UAE Department of Information Management Ming Chuan University Taiwan

ISBN: (数字)9781728165448

ISBN: (纸本)9781728165455

intelligent Telesurgery (TS) system with 6G-enabled Tactile Internet (TI) based on the blockchain has tremendous potential to deliver real-time and intelligent ultra-responsive healthcare services remotely with high quality and reliability. It would be significantly beneficial for the society in the prospect that high-quality medical service could be delivered to deprived areas and a highly promising surgical diagnosis could be achieved. However, the state-of-the-art TS systems have security, privacy, reliability, latency, and high-cost blockchain-based storage concerns, which limit the applicability of TS in surgical operations across the globe in the near future. To mitigate the aforementioned issues, we in this paper propose a novel approach named BITS an intelligent and blockchain-based TS framework. The issues pertaining to security, privacy, and lack of trust could be resolved through employing a smart contract. The issues related to the cost of data storage could be resolved by employing the InterPlanetary File System (IPFS) protocol. Moreover, we incorporate Artificial intelligent (AI) algorithms for training of surgical robots. The proposed scheme also prevents the execution of malicious commands transmitted by an intruder to a great extent. The 6G communication channel significantly mitigates the latency issues in exchanging surgical commands. Finally, we highlight some issues of the state-of-art TS systems and how the proposed BITS will be beneficial to combat those issues.

关键词： Medical services Surgery Security Reliability Robots Blockchain 6G mobile communication

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intelligent Fall Detection and Alert System for the Elderly Using Yolov8 and Cloud-Based analytics

Intelligent Fall Detection and Alert System for the Elderly ...

引用

Electronics and Sustainable Communication Systems (ICESC), 2020 international conference on

作者： Vishal Papan Maheswari S. Dept. of Computer Engineering Vellore Institute of Technology Chennai India

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

As people age, the frequency and impact of falls among the elderly continue to escalate, presenting significant health and mobility risks. Efficient detection and immediate response are crucial in reducing the severity of injuries and potentially life-threatening complications associated with such falls. This research study introduces a real-time alert system for the elderly by utlilizing the cutting-edge capabilities of YOLO v8, the latest iteration in the You Only Look Once series of models known for its high speed and accuracy in object detection tasks. The system is designed to operate with inputs from a variety of sources, including direct video feeds, RTSP streams from existing CCTV infrastructure, static images, and data from wearable sensors. This multi-source approach ensures that the system is adaptable for use in a wide range of environments, from personal residences to care facilities, providing continuous monitoring with enhanced accuracy. Upon the detection of a fall, the system immediately activates an alert protocol via Amazon Web Services (AWS) Simple Notification Service (SNS), ensuring that caregivers or family members are promptly notified to respond swiftly to the incident. This data-driven approach not only enhances the accuracy and responsiveness of the system over time but also aids caregivers and healthcare providers in understanding fall patterns and potential risk factors associated with specific environments or individuals, effectively addressing the critical challenges in elderly fall prevention and care.

关键词： YOLO Adaptation models Accuracy data analysis smart homes Real-time systems Older adults Fall detection Wearable sensors Monitoring

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Parking Lot Profiling Analysis: the City of Split Use Case

Parking Lot Profiling Analysis: the City of Split Use Case

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international Multidisciplinary conference on Computer and Energy Science (SpliTech)

作者： Goran Jelen Vedran Podobnik Jurica Babić Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

ISBN: (数字)9789532901054

ISBN: (纸本)9781728173634

Urban areas are going through a digital transformation where they are embracing Information and Communication Technology (ICT) to improve the Quality of Living (QoL) for its citizens. In this process, new data sources emerge, such as ground parking sensors which have the role in monitoring parking space occupancy. It is highly beneficial to analyse ground parking sensors data and to conduct parking profiling analysis to discover new knowledge about drivers' parking behaviour. This new knowledge can be used not only for understanding current parking patterns but as well as for creating prediction models that will have the ability to tell us how many parking spaces should be empty in the specific parking area and in the specific time slot. In this paper, the framework for parking profiling analysis will be presented, as well evaluated on the use case of parking spaces in the area of the City of Split, Croatia. The analysis shows that parking demand in Split is higher during the daily hours than the night hours, and that parking demand is the highest on Mondays and the lowest on Saturdays. For example, the profiling analysis for the most frequently used parking lot in Split shows that there is 18.67% of chance that parking lot will be fully occupied at midnight on Monday, and 20.66% chance that it will be fully occupied at noon on Monday.

关键词： Analytical models Digital transformation Urban areas Predictive models Information and communication technology Monitoring intelligent sensors

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IoT enabled smart Lighting System using STM32 microcontroller with high performance ARM® Cortex®-M3 core

IoT enabled Smart Lighting System using STM32 microcontrolle...

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UK/ China Emerging Technologies (UCET)

作者： Siyu Wu Amir M. Abdulghani Shuja Ansari Muhammad Ali Imran Qammer H. Abbasi Glasgow College UESTC University of Glasgow Glasgow UK James Watt School of Engineering University of Glasgow Glasgow UK Smart City Research Group Sultan Qaboos University Oman

ISBN: (数字)9781728194882

ISBN: (纸本)9781728194899

Green technology for economically viable engineering designs and sustainable environment is highly desirable for future smart city applications. An intelligent system for operating and controlling lighting in order to save energy is developed and presented in this article. The system is implemented on Alibaba Cloud IoT platform on STM32 development board using STM32 medium-density performing microcontroller with high performance ARM ® Cortex ® -M3 RISC core. It includes communication between wireless sensors and actuators, and control of light sources. The HC-SR501 human infrared sensor is also used for detecting people and BH170 photosensitive sensor for synthetic brightness detection. The system includes indicators to represent three orders of magnitude of temperature sensor reading. The system developed in this work also features (i) an OLED display unit enabling users to view sensed data easily and (ii) Web platform-based User Interface (dashboard) for allowing users to easily interact with the system. The overall system provides a practical and interactive solution for data visualization and to remotely control light sources.

关键词： Sensors Protocols Internet of Things Wireless fidelity smart homes Cloud computing Lighting

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A smart Ambulatory Cognitive State Taxonomy System Through EEG Signal Analysis

A Smart Ambulatory Cognitive State Taxonomy System Through E...

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international conference on computing and Networking Technology (ICCNT)

作者： Sumanto Dutta Sumit Hazra Anup Nandy Computer Science & Engineering National Institute of Technology Rourkela India

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Human mental state classification using Electroen-cephalogram(EEG) signal is one of the dynamic investigating areas in developing intelligent machine frameworks. In this paper, we propose an ambulatory cognitive state classification system using statistical feature analysis. The aim is to develop a realtime system which captures human cognitive states through computer-mediated help based on physiological signals. The walking cognitive state estimator is developed using a realtime Augmented Cognition (AugCog) framework. Six different normality testing methods, i.e. Kolmogorov-Smirnov, Anderson Darling, Cramer-Von Mises, Shapiro Wilk, Jarque-Bera, D'Ago-stino and Pearson's test are applied to achieve better accuracy. Box-Cox-transformation is also applied to ensure whether the data follows a normal distribution. We apply Fisher Discriminant Ratio (FDR) for selecting the most discriminative feature amongst all the statistical features (i.e. Mean, Median, Mode, Standard Deviation, Variance, Skewness and Kurtosis) obtained from the signal. Various machine learning methods are applied on the extracted features for training, testing and validation. Probabilistic neural network (P-NN) with Kurtosis feature is found to produces a maximum accuracy of 92.61 % as compared to other classifiers.

关键词： Electroencephalography Feature extraction Legged locomotion Headphones Support vector machines Testing Protocols

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Learning-analytics based intelligent Simulator for Personalised Learning

Learning-Analytics based Intelligent Simulator for Personali...

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Advancement in data Science, E-learning and Information Systems (ICADEIS), international conference on

作者： Nurfadhlina Mohd Sharef Masrah Azrifah Azmi Murad Evi Indriasari Mansor Nurul Amelina Nasharuddin Muhd Khaizer Omar Normalia Samian Noreen Izza Arshad Waidah Ismail Faaizah Shahbodin Faculty of Computer Science and Information Technology Universiti Putra Malaysia Serdang Selangor Malaysia Faculty of Educational Studies Universiti Putra Malaysia Serdang Selangor Malaysia Positive Computing Research Center Institute of Autonomous Systems Universiti Teknologi PETRONAS Bandar Seri Iskandar Perak Malaysia Faculty of Science and Technology Universiti Sains Islam Malaysia Bandar Baru Nilai Negeri Sembilan Malaysia Centre for Academic Excellence and Scholarship Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Melaka Malaysia

ISBN: (数字)9781728182728

ISBN: (纸本)9781728182735

Personalised learning enables instructions to be tailored specific to students learning needs, while making sure learning outcomes are attained. Instructors require information that could facilitate them in adapting their pedagogy design so the learning delivery could be optimized. However, existing solutions are limited to descriptive analytic and intervention facilitation is confined to students at risk prediction based on their course engagement frequency. Tools to predict final grade is available but very scarce. Besides, realtime monitoring of reaction to learning events are not available. Therefore, this paper proposes a solution that integrates Internet of Things, learning analytic and chatbot to fill the said gaps. The paper also presents the experience of pilot developments towards the current version of solution.

关键词： Education Chatbot Internet of Things Information technology Computer science Monitoring Ecosystems

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A Content-based intelligent Label Classification System for Warehouse Management

A Content-based Intelligent Label Classification System for ...

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Zaipeng Xie Yuxuan Lin Cheng Ji Weiyi Zhao Yao Liu Hohai University Nanjing China

ISBN: (数字)9781728170862

ISBN: (纸本)9781728170879

With the rapid development of the e-commerce business, smart warehouse management has become a critical part of the supply chain for maintaining an optimized cost in stock logistics. The managing of inventory may require substantial labors and expenses on the order fulfillment and the label classification. This paper proposes a warehouse management system that can provide the real-time categorizing service for labels based on a fastText based word text classification algorithm. In this system, a label classifier is presented to facilitate the process of classifying massive labels based on its content. In this classifier, a Huffman tree data structure have been developed and a layered softmax structure is utilized to reduce the computational complexity. Experimental results show that the proposed method is capable of processing efficient label classification tasks where the management efficiency can be improved for the economic benefits of warehouse management.

关键词： Tree data structures Supply chains Text categorization Neural networks Real-time systems Task analysis Informatics

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Using Blockchain in the agri-food sector following SARS-CoV-2 pandemic

Using Blockchain in the agri-food sector following SARS-CoV-...

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international conference on Electronics, Computers and Artificial Intelligence (ECAI)

作者： Florentina Magda Enescu Valeriu Manuel Ionescu Department of Electronics Communications and Computers University of Pitesti Romania

ISBN: (数字)9781728168432

ISBN: (纸本)9781728168449

This article proposes the use of Blockchain by small farmers in the agri-food sector. The registers of accounts and transactions stored by each participating partner, made through Blockchain, allow keeping secure information about the status of farms, contracts and product stocks. This ensures the creation of credible supply chains for both the producer and the consumer. intelligent contracts are made that can guarantee timely payments between the parties while modifying the data in the distributed databases. The research conducted in our study found that, usually, the marketing of small farmers' products is done in the arranged spaces (agri-food markets) or are taken over by intermediaries to be marketed. All these processes have the effect of increasing the prices borne by the consumer, but not only. During critical emergency periods, such as 2020 SARS-CoV-2, many farmers were left with unseen products. In support of producers and consumers; it is proposed to use the new blockchain system. This system achieves transparency, security and trust in the trading process. Although the blockchain system is at the beginning of the road, it can successfully achieve all these problems, so that small farmers can sell the products in periods with restrictions or not, to consumers, safely and at lower prices (directly from the manufacturer).The process can be applied in a region, state and even globally.

关键词： Blockchain Registers smart contracts Relational databases Production Reliability Peer-to-peer computing

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smart cities: Progress and Problems in India

Smart cities: Progress and Problems in India

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international conference on Advances in computing, Communication Control and Networking

作者： Priyanka Gupta Rajan Gupta GGSIPU New Delhi India

The urge of urbanization is increasing at a rapid rate worldwide. It ensues the emergence and use of various digital technologies like Internet of Things, Cloud computing, Big data analytics, intelligent computing etc. The one important and most hyped application of such technologies is smart Cities. This concept revitalizesthe whole city by strengthening its core competencies. It automates every sector like transportation, homes, traffic, agriculture, water and electricity supply, waste management, health, education etc. This notion is implementing in various parts of the world leading to the new level of urbanization. The perception of this powerful approach in India is presented in this paper. The current stage of this project and the possible roadblocks in implementing it in Indian scenario is also discussed in this manuscript.

关键词： smart city Urbanization Technologies

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DeepKAF: A Heterogeneous CBR & Deep Learning Approach for NLP Prototyping

DeepKAF: A Heterogeneous CBR & Deep Learning Approach for NL...

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IEEE international Symposium on Innovations in intelligent Systems and Applications (INISTA)

作者： Kareem Amin Stelios Kapetanakis Nikolaos Polatidis Klaus-Dieter Althoff Andreas Dengel Smart Data and Knowledge Services German Research Center for Artificial Intelligence Technische Universität Kaiserslautern Kaiserslautern Germany School of Computing Engineering and Mathematics University of Brighton Brighton United Kingdom Intelligent Information Systems Lab Institute of Computer Science University of Hildesheim Hildesheim Germany

ISBN: (数字)9781728167992

ISBN: (纸本)9781728168005

With widespread modernization, digitization and transformations of most of industries, Artificial Intelligence (AI) has become the key enabler in that modernization journey. AI offers substantial capabilities to solve new problems and optimise existing solutions specialising on specific problems and learning from different domains. AI solutions can be either explainable or black box ones with the latter being urged to improve since they cannot trust. Case-based Reasoning (CBR) is an explainable AI approach where solutions are provided along with relevant explanations in terms of why a solution was selected. However, CBR, like most other explainable approaches, has several limitations in terms of scalability, large data volumes, domain complexity, that reduce its ability to scale any CBR system in industrial applications. In this paper, we provide a heterogeneous CBR framework - DeepKAF where we combine CBR paradigm with Deep Learning architectures to solve complicated Natural Language Processing (NLP) problems (eg. mixed language and grammatically incorrect text).DeepKAF is built based on continuous research in the area of Deep Learning and CBR. DeepKAF has been implemented and used across different domains, test use cases and research models as an ensemble deep learning and CBR Architecture.

关键词： Machine learning Training Neural networks Natural language processing Cognition Buildings Task analysis

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