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Fog-Enabled IoT Framework for Heart Disease Diagnosis Systems

Journal of Mobile Multimedia 2023年第2期19卷 389-418页

作者： Minh, Quang Tran Thai, Do Thanh Phung, Phu H. Huu, Phat Nguyen Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology (HCMUT) 268 Ly Thuong Kiet District 10 Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City (VNU-HCM) Linh Trung Ward Thu DucDistrict Ho Chi Minh City Viet Nam Department of Computer Science University of Dayton Dayton 45469 OH United States School of Electrical and Electronics Engineering Hanoi University of Science and Technology Hanoi Viet Nam

IoT technology has been recently adopted in healthcare systems to quickly detect abnormalities from patients, diagnose diseases and provide supports in time, even remotely. In the field of heart disease, timely diagnosis and prediction help to save people. This paper proposes a fog-based IoT approach to collect and analyze electrocardiogram (ECG) signals from patients to detect abnormalities or heart attacks with a short response time so that appropriate treatments can be provided. Commonly, ECG signals are transmitted to an eco-expert system deployed on the cloud to perform preliminary automatic diagnosis using a knowledge base built from medical experts. Although such an eco-expert system assists patients and supports physicians in performing treatment for their patients, there are several open technical challenges. First, noise in raw ECG signals makes the data imprecise and reduces the prediction accuracy. Second, involving data mining and machine learning on the cloud poses a significant latency since a huge amount of data needs to be transferred in the network. This paper proposes a novel framework that can provide the integrity of the ECG data by removing noise and then extract relevant knowledge for heart disease diagnosis at the network edge based on data mining techniques. Practical experiments demonstrate that the proposed framework not only guarantees the integrity of the data but also enhances the accuracy of the real-time detection compared with previous works. © 2022 River Publishers.

关键词： data mining fog computing heart disease diagnosis IoT

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Low Area PRESENT Cryptography in FPGA Using TRNG-PRNG Key Generation

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computers, Materials & Continua 2021年第8期68卷 1447-1465页

作者： T.Kowsalya R.Ganesh Babu B.D.Parameshachari Anand Nayyar Raja Majid Mehmood Department of Electronic and Communication Engineering Muthayammal Engineering CollegeRasipuramNamakkalTamilnaduIndia Department of Electronics and Communication Engineering SRM TRP Engineering CollegeTiruchirappalliTamilnaduIndia Department of Telecommunication Engineering GSSS Institute of Engineering and Technology for WomenMysuruIndia Faculty of Information Technology Graduate SchoolDuy Tan UniversityDa Nang550000Viet Nam Department of Information and Communication Technology School of Electrical and Computer EngineeringXiamen University MalaysiaSepang43900Malaysia

Lightweight Cryptography(LWC)is widely used to provide integrity,secrecy and authentication for the sensitive ***,the LWC is vulnerable to various constraints such as high-power consumption,time consumption,and hardware utilization and susceptible to the malicious *** order to overcome this,a lightweight block cipher namely PRESENT architecture is proposed to provide the security against malicious *** True Random Number Generator-Pseudo Random Number Generator(TRNG-PRNG)based key generation is proposed to generate the unpredictable keys,being highly difficult to predict by the ***,the hardware utilization of PRESENT architecture is optimized using the Dual port Read Only Memory(DROM).The proposed PRESENT-TRNGPRNG architecture supports the 64-bit input with 80-bit of key *** performance of the PRESENT-TRNG-PRNG architecture is evaluated by means of number of slice registers,flip flops,number of slices Look Up Table(LUT),number of logical elements,slices,bonded input/output block(IOB),frequency,power and *** input retrieval performances analyzed in this PRESENT-TRNG-PRNG architecture are Peak Signal to Noise Ratio(PSNR),Structural Similarity Index(SSIM)and Mean-Square Error(MSE).The PRESENT-TRNG-PRNG architecture is compared with three different existing PRESENT architectures such as PRESENT On-TheFly(PERSENT-OTF),PRESENT Self-Test Structure(PRESENT-STS)and PRESENT-Round Keys(PRESENT-RK).The operating frequency of the PRESENT-TRNG-PRNG is 612.208 MHz for Virtex 5,which is high as compared to the PRESENT-RK.

关键词： Dual port read only memory hardware utilization lightweight cryptography malicious attackers present block cipher pseudo random number generator true random number generator

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Building Damage Detection Using Deep Learning Models

Building Damage Detection Using Deep Learning Models

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International Conference on Telecommunications (ICT)

作者： Kibitok Abraham Moataz Abdelwahab Mohammed Abo-Zahhad Communications & Computer Engineering School of Electronics Egypt-Japan University of Science and Technology (E-JUST) New Borg EI Arab City Alexandria Egypt Electrical Engineering Department Faculty of Engineering Assiut University Assiut Egypt

ISBN: (数字)9798350356694

ISBN: (纸本)9798350356700

Human life is significantly impacted by ongoing natural disasters. The global impact of the building damage they inflict is deeply significant. Deep learning can effectively analyze the extent of damage to buildings. However, the challenge is the availability of the dataset. An innovative, challenging dataset collected from satellites has been presented, encompassing the extent of structural harm caused by the earthquake in Morocco. The dataset is from a complex, practical, arid environment where the building colour is almost like the background. The dataset has been tested using U-Net, FCN, and ResUnet models. The ResUnet demonstrates superior performance metrics with pixel accuracy, recall, precision, Fl-score, kappa score, and IoU values of 96.2%, 86.4%, 86%, 86.2%, 75.7%, and 85.5%, respectively, which promotes it for practical application.

关键词： Measurement Deep learning Accuracy Satellites Image color analysis Green buildings Disasters

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A Hybrid Blockchain Framework for Secure, Scalable, and Energy-Efficient Digital Identity Management with Token-based Selective Disclosure

A Hybrid Blockchain Framework for Secure, Scalable, and Ener...

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electronics and Renewable Systems (ICEARS), International Conference on

作者： Velmurugan M Shinzeer C K G. Maya R. Ramya R Kanimozhi Syed Ismail Abdul Lathif Department Of Computer Science & Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science And Technology Chennai Department of School of Computer Applications Lovely Professional University Phagwara Punjab Faculty of Management SRM Institute of Science and Technology Kattankulathur Department of Electronics and Communication Engineering K.Ramakrishnan College of Engineering Samayapuram Computer Science and Engineering Muthayammal Engineering College Rasipuram Department of Data Science and Business Systems SRM Institute of Science and Technology Chennai

ISBN: (数字)9798331509675

ISBN: (纸本)9798331509682

Data breaches, identity theft, and the lack of user control within traditional digital identity management systems, it begs a more secure and decentralized alternative. In this study we propose a blockchain based digital identity management framework that implements privacy, security and transparency by employing distributed ledger technology. To provide tamper proof identity storage and automated verification, the proposed model uses cryptographic hashing and smart contracts. The use of a novel token-based access mechanism enables users to safely share their identity data with third parties, while keeping sensitive information out of sight. Security metrics are enhanced by 30% for data integrity with 45% reduction in unauthorized access attempts all through simulations. The framework also achieves improved efficiency reducing identity verification time by 40 percent compared to traditional systems. It offers a promising approach to address important vulnerabilities in centralized identity management in line with the development of marketable and user-friendly digital identity solutions.

关键词： Resistance Privacy Fault tolerance Smart contracts Fault tolerant systems Throughput Energy efficiency Blockchains Identity management systems Interoperability

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Bioinspired Routing Protocols for UWSNs Using Particle Swarm Optimization

Bioinspired Routing Protocols for UWSNs Using Particle Swarm...

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2024 IEEE International Conference on Communication, Computing and Signal Processing, IICCCS 2024

作者： Adnan, Myasar Mundher Maheshkumar, N. Praveena, J. Patidar, Deepak Aarju Ambika The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq The Islamic University of Al Diwaniyah College of Technical Engineering Department of Computers Techniques Engineering Al Diwaniyah Iraq Karpagam Academy of Higher Education Faculty of Engineering Department of Science and Humanities Tamilnadu Coimbatore India Prince Shri Venkateshwara Padmavathy Engineering College Chennai127 India Ies College of Technology Department of Electronics & Communication Engineering M.P. Bhopal India Chandigarh Group of Colleges Chandigarh Engineering College Department of Computer Science Engineering Punjab Mohali India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Dapartment of Cse Chennai India

ISBN: (纸本)9798350390759

The aim of this research therefore is to propose and design bio-inspired routing protocols in UWSNs using PSO. High latency and low bandwidth, coupled with high error rates, make underwater routing a different ball game than routing in normal situations and traditional mediums. The proposed PSO-based protocols also consider factors like power utilization, coverage distance, and priority of data packets to make better routing choices thus helping to improve the efficiency and responsiveness of the UWSNs. The compare analysis of the proposed protocols with the earlier protocols, which are also developed based on AODV and DSR, proves high performance of the PSO based protocols in the energy consumption, data delivery ratio, end to end delay and the network lifetime within all the realistic underwater environments analyzed by the simulations. Such advancement would help to improve the communication system in UWSNs, presenting new approaches for efficient communication in the underwater environment. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Revolutionizing Waste Management Through Intelligent Garbage Segregation Bin 3

Revolutionizing Waste Management Through Intelligent Garbage...

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3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Veerabhadraswamy, K.M. Kumar, Karthik Indhuja, A. Barve, Amit Kannadasan, B. Bakhare, Ruhi Government Engineering College Mosalehosahalli Department of Electronics and Communication Engineering Karnataka Hassan573 212 India REVA University School of Civil Engineering Karnataka Bangalore560 064 India SNS College of Technology Department of Computer Science and Engineering Tamil Nadu Coimbatore641 035 India Parul University Parul Institute of Technology Faculty of Engineering and Technology Department of Computer Science and Engineering P.O.Limda Gujarat 391 760 India Kannadasan Balakrishnan Research Foundation Kalieswari Nagar Department of Civil Architectural Engineering and Planning Tamil Nadu Peraiyur625 703 India Dr. Ambedkar Institute of Management Studies and Research Deekshabhoomi Maharashtra Nagpur440 010 India

ISBN: (纸本)9798350343632

Efficient waste management stands as a paramount concern in the current environmental landscape. The proper handling, sorting, transportation, and disposal of waste materials are essential to mitigate environmental hazards. The separation of trash into several categories allows for a more accurate evaluation. Conventional manual waste segregation systems necessitate a significant amount of human labor, time, and money. This study proposes a waste management system integrated using advanced technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI), allowing for easy and cost-effective garbage segregation and tracking. The technique is intended to separate garbage into several categories such as glass, plastic, cardboard, paper, metal, and trash. A sample dataset acquired from Kaggle was rigorously processed to design and evaluate the system, which includes operations like as image resizing and rescaling. The DenseNet, is a Deep Learning (DL) model used for accurate garbage recognition. This unique smart segregation bin makes use of the potential of AI and IoT technology. The model is embedded in a controller, allowing it to properly recognize different waste items and trigger the associated actuator for accuracy sorting. A user-friendly Graphical User Interface (GUI) structure makes the entire process visible to the public. This interface enables users to watch the system's operation in real-time, providing a clear perspective of garbage identification and sorting. By revolutionizing waste management through intelligent garbage segregation, this system enhances the efficiency of waste sorting, contributing to environmental preservation and sustainable waste management practices. © 2023 IEEE.

关键词： Accuracy Camera Data Processing DenseNet Garbage Loss User Interface

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Investigating the Ethical Implications of Artificial Intelligence and Establishing Guidelines for Responsible AI Development

Investigating the Ethical Implications of Artificial Intelli...

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Advances in Computing Research on Science engineering and technology (ACROSET), International Conference on

作者： Sukumar R Vinima Gambhir Jyoti Seth Department of Electronics and Communication Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bangalore India Department of ISME ATLAS SkillTech University Mumbai India Department of Computer Science & Engineering Vivekananda Global University Jaipur India

ISBN: (数字)9798350388800

ISBN: (纸本)9798350388817

Now more than ever, artificial intelligence (AI) presents both unprecedented potential and difficulties. This article delves deeply into the ethical concerns raised by AI and lays forth principles that should be followed in the creation of ethical AI systems. In the opening, we recognize the revolutionary potential of AI as well as the ethical quandaries it poses. In order to guarantee that AI technologies are created and implemented in a responsible and fair way, a deep ethical examination is required in light of the proliferation of autonomous systems. To address these ethical difficulties, we suggest the adoption of an Ethical Analysis Framework (EAF). The Ethical Assessment Framework (EAF) provides a framework for systematically assessing the fairness, transparency, privacy, accountability, and bias of AI systems. It's a cornerstone for the community of AI ethics researchers, developers, and policymakers working together to keep AI honest. Our approach places special importance on the gathering and preparation of data. We emphasize how important ethically sound data is in defining the moral implications of AI. We found that when compared to other approaches to assessing the morality of AI, our suggested technique consistently outperformed the others. The suggested technique establishes itself as an innovative and effective way of navigating the growing ethical environment by providing a systematic approach to addressing AI's ethical implications and supporting responsible AI research. For instance, as compared to more conventional methods, our technique increased fairness evaluations by an average of 15%. In conclusion, there is a wide range of concerns related to the morality of AI that must be constantly monitored and addressed via joint effort. Our method places an emphasis on making sure AI is progressing in a way that is responsible, ethical, and fair to all members of society.

关键词： Ethics Privacy Systematics Navigation Transforms Organizations Turning Artificial intelligence Monitoring Guidelines

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IoT and RFID-Based Automated Electric Vehicle Battery Swapping and Charging Station

IoT and RFID-Based Automated Electric Vehicle Battery Swappi...

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International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Md Sadman Shakif Bhuiyan Md Abdus Shakur Md Salman Khan Mithil Adnan Md Abu Talha Al Shahriar Zishan M Tanseer Ali Department of Electrical and Electronics Engineering (EEE) Faculty of Engineering (FE) American International University–Bangladesh (AIUB) Dhaka Bangladesh Department of Electrical Engineering and Computer Science Electrical Engineering (MS) South Dakota School of Mines & Technology Rapid City United States

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Electric vehicles (EVs) face significant challenges, including limited range and the need for efficient battery management, which hinder their widespread adoption. Battery swapping technology, enhanced by IoT and RFID, offers a promising solution by enabling quick replacement of depleted batteries, thereby minimizing vehicle downtime. This paper presents the design and implementation of an RFID-based automated battery swapping station for EVs, leveraging IoT for enhanced efficiency and user experience in battery management. The system integrates key components such as an Arduino Uno microcontroller, servo motors, voltage sensors, and RFID technology to automate the battery-swapping process. Essential functions like battery detection, locking, and transaction processing are fully automated, with IoT-enabled real-time monitoring of battery status ensuring reliability. Practical experiments and simulations confirm the system's robust performance in managing battery-swapping operations and facilitating secure, seamless transactions. This development represents a significant advancement in EV infrastructure, supporting the broader adoption of electric vehicles.

关键词： Microcontrollers Battery management systems Voltage Electric vehicles Real-time systems Batteries Sensors State of charge Servomotors Radiofrequency identification

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The Impact of the Digital Transformation of Education on Literacy

The Impact of the Digital Transformation of Education on Lit...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power engineering (CANDO-EPE)

作者： Imre Farkas Attila Kovari Mónika Rajcsanyi-Molnar Department of Computer Systems and Control Technology Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Digital Technology Faculty of Computer Science Eszterházy Károly Catholic University Eger Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét Hungary Department of Economics and Management Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

During the COVID19 epidemic, people of all ages from all walks of life around the world have become inevitably familiar with and almost dependent on the digital tools of the age and the opportunities they offer. A change had to take place very quickly that was unprecedented. This process has also affected education. During the time of the reading lock-in, there was a proliferation of digital curricular content. The second time around, online education came to the fore, thanks to less or well-functioning online platforms, and has since become part of everyday teaching. What is the effectiveness and usefulness of sharing knowledge in this way? Is literacy still needed at all? Can online and hybrid (a controlled mix of face-to-face and online) education replace the well-established contact and face-to-face education? The study show that the respondents believe that online education has had an impact on literacy and that it is perceived to have a positive impact. The results indicate that online education has a positive impact on the literacy levels of students, as it facilitates knowledge acquisition and enhances digital literacy skills.

关键词： Power engineering Epidemics Navigation Knowledge acquisition Digital transformation Education Information age Digital intelligence Cultural differences Problem-solving

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Dual-Polarized Phase-Gradient Reflecting Metasurface for 5G mmWave Coverage Improvement

Dual-Polarized Phase-Gradient Reflecting Metasurface for 5G ...

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International Symposium on Antennas and Propagation (ISAP)

作者： Taran Anusorn Panuwat Janpugdee Suwit Kiravittaya Paramin Sangwongngam Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand National Electronics and Computer Technology Center (NECTEC) National Science and Technology Development Agency (NSTDA) Pathum Thani Thailand

This paper proposes the design of a phase-gradient reflecting metasurface (MTS) to improve 5G mmWave coverage, following the principle of perfect anomalous reflection. The reflective responses of a simple structure with cross-shaped resonators have been investigated. The results from a full wave simulation show that the proposed MTS with a surface area of 23×23 cm 2 can anomalously reflect a linear dual-polarized plane wave at 25.8 GHz from an incident angle of 30° to a reflection angle of 54° with a more than 10 dB radiation power ratio between the main reflected beam and its sidelobe at a specular reflecting direction.

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