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Healthcare management in Bigdata with Blockchain and IOT integrated System 1

Healthcare management in Bigdata with Blockchain and IOT int...

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1st IEEE international conference on Advances in computing, Communication and Networking, ICAC2N 2024

作者： Kaliyahan, Shalini Bhatnagar, Prachi Gupta, Shilpi Jain, Archana Malik, Suraj Gochhait, Saikat Sharma, Aditi Pandey, Mahima Shankar IIMT University Department of Computer Science and Application Uttar Pradesh Meerut India Meerut Institute of Technology Department of Computer Science and Engineering Uttar Pradesh Meerut India IIMT University Department of Computer Science and Engineering Uttar Pradesh Meerut India Constituent of Symbiosis International Deemed University Symbiosis Institute of Digital and Telecom Management Pune India Galgotia College of Engineering and Technology Department of Computer Science and Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350356816

In 21st decade, healthcare is one of the biggest challenges, and the current scenario very flexible to adapt the effective execution technology solutions like internet of things (IoT). Through this a patient may access the treatment remotely and rapidly. Most suitable and effective applications need complex data of personal care, and reliability among the entire participated component or parties. Blockchain technology has been captured the industry domain with its computation and trusted model among participated parties. This paper presents a data storage decision framework for managing blockchain storage using on-chain and off-chain methods. There is a need for making balanced decisions between the very expensive on-chain storage methods and the less secure off-chain storage, towards optimizing blockchain storage costs. © 2024 IEEE.

关键词： Cloud computing architecture

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Design and Experimentation of a distributed Information Retrieval-Hybrid Architecture in Cloud IoT Data Centers 1st

Design and Experimentation of a Distributed Information R...

引用

1st international Workshop on the Design, Verification, and Validation of IoT Systems, GRAAL4IoT 2024 and 1st international Workshop on IoT standards, stAND4IoT 2024, held in conjunction with 7th IFIP WG 5.5 international Cross-Domain conference on internet of Things, IFIPIoT 2024

作者： Tosi, Davide Pazzi, Roberto Università dell’Insubria Via Ravasi 2 Varese Italy

ISBN: (纸本)9783031820649

The proliferation of data from IoT devices has introduced challenges for efficient and accurate information retrieval in distributed Cloud Data Centers. This paper presents a Hybrid distributed Information Retrieval (H-DIR) model optimized for IoT environments using advanced semantics and a hybrid query approach. The model aims to improve retrieval precision and efficiency by leveraging semantic concepts and contextual metadata, while also enhancing security and data privacy. Applied in a real industrial setting for gardening services, the H-DIR model demonstrates potential to increase revenue through economic quantification of services and value creation via faster preventive measures. © IFIP international Federation for Information Processing 2025.

关键词： Data centers

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Comparative Analysis of Deep Learning Techniques for Chatbots Implementation 1

Comparative Analysis of Deep Learning Techniques for Chatbot...

引用

1st international conference on Emerging Technologies for Dependable internet of Things, ICETI 2024

作者： Al-Qahtani, Anwar Hussein Al-Baltah, Ibrahim Ahmed Ghaleb, Mukhtar Department of Information Technology Faculty of Computer and Information Technology Sana’a University Sana’a Yemen College of Computing and Information Technology University of Bisha Bisha Saudi Arabia

ISBN: (纸本)9798331533557

Nowadays, advancements in technology have facilitated the development of machines that emulate humanlike behavior. One notable application of this is conversational software agents which utilize natural language process (NLP) and artificial intelligence (AI), commonly referred to as Chatbots. These Chatbots serve various purposes and find application across diverse sectors such as business, healthcare, agriculture, and more. The evolution of Chatbots has been remarkable, prompting significant interest and research endeavours. This paper aims to provide a comprehensive survey of the techniques employed in enhancing Chatbot functionalities, offering a comparative analysis among them. Additionally, it delves into the nuances of these techniques, elucidating both their commonalities and distinctions. Through this exploration, the most commonly used algorithms in chatbots are reinforcement learning, BERT, NLP, and hybrid algorithms of artificial neural networks. The paper endeavours to identify research gaps that can guide future improvements in Chatbot technology, ultimately enhancing customer satisfaction levels. © 2024 IEEE.

关键词： Chatbots

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Data Analysis in Wireless Sensor Networks with distributed Self Organizing Map 1

Data Analysis in Wireless Sensor Networks with Distributed S...

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1st IEEE international conference on Advances in Signal Processing, Power, Communication, and computing, ASPCC 2024

作者： Panwar, Anita Nanda, Satyasai Jagannath Malaviya National Institute of Technology Jaipur Dept. of Electronics and Communication Engineering Rajasthan 302017 India

ISBN: (纸本)9798350355093

distributed clustering algorithms are employed in wireless sensor network (WSN) to improve the local data analysis. This process is carried out collaboratively with the help of nearby neighbours without a central controller. In this paper, distributed clustering is performed with Self Organizing Map (SOM). The SOM is a popular unsupervised neural network model that maps input data to a lower-dimensional grid. On this grid map similar input patterns are placed closer to each other. This process helps in discovering patterns and relationships in the data without prior labeling, thus making proposed distributed Self Organizing Map (DSOM) useful for unknown local data analysis at the WSNs. The proposed algorithm is applied to analyze two real life WSN datasets: Water quality monitoring of Thames river, Weather monitoring dataset of various stations at Canada. Comparative analysis is carried out with distributed Particle Swarm optimization algorithm and distributed K-means algorithm. The proposed DSOM has superior performance, as indicated by Silhouette Index and Quantization Error measurements. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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High-Resolution Hadamard-Based CDM-MIMO Automotive Radar 1

High-Resolution Hadamard-Based CDM-MIMO Automotive Radar

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1st international conference on computing, internet of Things and Microwave Systems, ICCIMS 2024

作者： Benyahia, Zakaria Hefnawi, Mostafa Aboulfatah, Mohamed Abdelmounim, Hassan Zbitou, Jamal Hassan 1st University FST Settat Settat Morocco Royal Military University of Canada KingstonON Canada Abdelmalek Essadi University Tétouan Tétouan Morocco

ISBN: (纸本)9798350351736

This paper proposes a deep learning (DL) approach for high-resolution Hadamard-based Code Division Multiplexing Access (CDM) Multiple Input Multiple Output (MIMO) automotive radar to enhance the discrimination capabilities of the radar in a cluttered environment. The approach is based on the SqueezeNet deep convolutional neural network (DCNN), which treats the angle, range, and Doppler estimations of the extracted targets as a multilabel classification problem. Compared to traditional techniques such as Minimum Variance Distortionless Response (MVDR) and Multiple Signal Classifier (MUSIC), our approach demonstrates superior performance in resolving targets in clutter and interference. Our approach also outperforms existing DL-based TMD-MIMO radar systems. Simulation results show that an angular resolution of 0.25 degrees was achieved with a 12×12 MIMO radar system. © 2024 IEEE.

关键词： Automotive radar

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Prevent the Counterfeit of Pharmaceutical Products by Using Data Matrix Code and distributed Blockchain 1

Prevent the Counterfeit of Pharmaceutical Products by Using ...

引用

1st international conference on Technological Innovations and Advance computing, TIACOMP 2024

作者： Hasan, M. M. Rakibul Fatema, Sadia Jahan Hossain, Gazi Md. Shakil Alam, Mohammad Mahabub International University of Business Agriculture and Technology Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350392111

False medications are a serious risk, threatening lives and undermining confidence. This research paper offers an innovative approach to fight counterfeiting and transform the transparency of the pharmaceutical supply chain combining blockchain technology with data matrix code. Consumers with cell phones can easily verify the validity of products by using unique data matrix codes linked to an immutable blockchain database. Authorized participants trace the movement of products within the network, from pharmacies to producers, producing an informative audit trail. Attempts at counterfeiting are exposed and are replaced with efficiency and trust. Envision an open supply chain promoting early identification and mitigation of counterfeiting. The goal of this research is to be the driving force behind this change by utilizing blockchain technology and data matrix to dramatically increase patient and consumer safety and create a more reliable pharmaceutical industry. © 2024 IEEE.

关键词： Blockchain Data Matrix Code IPFS Pharmaceutical Product Prevent Counterfeit Proof of stack Public Key Cryptography SHA 256 Supply Chain Transparency

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Optimizing Computation Offloading in UAV-Enhanced Mobile Edge computing through a Deep Deterministic Policy Gradient Method 1

Optimizing Computation Offloading in UAV-Enhanced Mobile Edg...

引用

1st international conference on Emerging Technologies for Dependable internet of Things, ICETI 2024

作者： Alwah, Nada Noman Al-Baltah, Ibrahim Ahmed Department of Information Technology Faculty of Computer and Information Technology Sana’a University Sana’a Yemen

ISBN: (纸本)9798331533557

In this study, we explore the concept of drone-assisted drones. In a mobile edge computing (MEC) setting, unmanned aerial vehicles (UAVs) play a critical role in providing offloading services to mobile devices in regions lacking adequate infrastructure, UAVs are utilized for delivering offloading services to nearby mobile devices (UEs), with the primary objective being the minimization of processing delays under constraints involving discrete variables. by collectively enhancing user scheduling, balancing task offloading, adjusting UAV flight angles, and optimizing flight speeds, we aim to enhance the efficiency and performance of the system. Given the non-convex nature of the issue, the extensive range of states, and the continuous actions involved, this paper proposes. A computational strategy for offloading that employs the Deep Deterministic Policy Gradient (DDPG) technique. within the domain of Reinforcement Learning (RL). The results from the experiments clearly show the effectiveness of the suggested algorithm. converges toward the optimal solution, markedly enhancing processing speeds and system performance. This study sheds light on the remarkable advancements achieved through our proposed solution, showing tangible improvements in processing efficiency and system efficacy. © 2024 IEEE.

关键词： Drones

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A Lightweight Biometric-based User Authentication Protocol for Self-driving Vehicles 1

A Lightweight Biometric-based User Authentication Protocol f...

引用

1st international conference on Cyber Security and computing, CyberComp 2024

作者： Coulibaly, Lasseni Hanyurwimfura, Damien Twahirwa, Evariste Diwani, Abubakar University of Rwanda African Center of Excellence in Internet of Things Kigali Rwanda The State University of Zanzibar Department of Computer Science and IT Zanzibar Tanzania United Republic of

ISBN: (纸本)9798350387728

With the adoption of intelligent transportation systems, there is a rapid migration from traditional driver-based vehicles to self-driving vehicles, which have become open to the cyber world, and therefore, vulnerable to several attacks. Among existing security measures like mutual vehicular authentication, secure communication channels, and intrusion detection systems, there is a severe lack of attention to the user-to-vehicle authentication aspect, which represents a primary security barrier against vehicular attacks. In this paper, a secure and lightweight biometric-based user-to-vehicle authentication protocol is proposed to prevent unauthorized access to vehicles' systems and vehicular communications by extension. Through formal and informal security analysis, the proposed protocol has demonstrated a good performance in terms of resistance to well-known attacks while achieving lower computational and communication overheads compared to the related methods. © 2024 IEEE.

关键词： Authentication Protocol

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Health Monitoring and Diagnostic Platform Based on AI and IoMT Sensors: An Overview of Methodologies and Challenges 1

Health Monitoring and Diagnostic Platform Based on AI and Io...

引用

1st international conference on Trends in Engineering Systems and Technologies, ICTEst 2024

作者： Goel, Akanksha Neduncheliyan, S. Dr D. Y. Patil School of Science and Technology Dr D. Y. Patil Vidyapeeth Pune India Bharath Institute of Higher Education and Research Chennai600073 India

ISBN: (纸本)9798350307795

Healthcare research including artificial intelligence (AI) is progressing rapidly with possible applications being demonstrated across various healthcare fields. Intelligent wearables and other internet of medical things (IoMT) devices are progressively being utilized to measure crucial signals in order to forecast diagnosis. As the need for ways to lower healthcare expenses increases in the next years, artificial intelligence for healthcare (MedAI) and cloud computing lead to significant improvements in diagnostic speed, accuracy, and transformation, especially for people's health and safety. The subject of this study is contemporary research in the field of artificial intelligence enabled by the internet of Medical Things (IoMT), as well as improvement on their conventional equivalents. The paper also outlines some of the research prospects in the healthcare platform based on AI and so provides an overview of future work and achievement in this area. © 2024 IEEE.

关键词： Cloud computing

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Research on Digital Equipment Application Based on Digital Twin technology

Research on Digital Equipment Application Based on Digital T...

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2023 international conference on internet of Things, Robotics and distributed computing, ICIRDC 2023

作者： Zhang, Yangyang Fang, Liqing Qi, Ziyuan Deng, Huiyong Liang, Hui 1st Dept. of Shijiazhuang Campus Army Engineering University Shijiazhuang China

ISBN: (纸本)9798350375275

Modern large-scale mechanical equipment usually has diverse tasks and complex structures. The traditional development and design, task management and operation and maintenance modes are increasingly difficult to meet the practical needs. With the development of computer and information technology, digital twin technology has been proposed and widely concerned. It can realize the interaction and fusion between an object's physical entity and virtual model by establishing a model with multi-physics, multi-scale, multi-level and multi-disciplinary attributes. It has the characteristics of virtual-real synchronization, faithful mapping, and high fidelity, which provides a new way to solve the above problems. Therefore, based on the basic theory and technology of digital twin, taking typical complex equipment as the research object, this paper proposes the overall architecture of digital equipment, summarizes the key technologies of developing digital equipment, and explores several potential application services based on digital twin, such as product design, auxiliary decision-making, intelligent maintenance and health management, to provide theoretical and methodological references for further research and equipment application in the future. © 2023 IEEE.

关键词： Decision making

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