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Optimizing Smart Home Systems: Utilizing Blockchain and Edge computing 5

Optimizing Smart Home Systems: Utilizing Blockchain and Edge...

引用

5th international conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Xu, Rong School of Information and Architectural Engineering Anhui Open University Anhui Hefei230022 China

ISBN: (纸本)9798350379945

the evolution of smart home systems into the internet of things (IoT) era has revolutionized the traditional home, offering greater convenience and automation. However, with these benefits come significant security concerns, particularly around data privacy and centralized vulnerabilities. Current smart home models rely heavily on centralized servers, exposing them to single points of failure and potential breaches that undermine user trust and system reliability. In addition, interoperability challenges between devices and opaque data management further complicate these issues. To address these challenges, this study proposes a novel smart home architecture that integrates blockchain and edge computing technologies. Blockchain provides a decentralized approach to data management, ensuring transparency, security, and user control over personal data. By distributing data across nodes and employing advanced cryptographic techniques, blockchain enhances resilience against cyber-attacks and unauthorized access. the proposed methodology includes the design of a robust smart home gateway using advanced micro-controller units and enhanced Wi-Fi modules. this gateway orchestrates device communication and user interaction, enhancing system flexibility and scalability. Experimental evaluations confirm the effectiveness of the proposed system, demonstrating reduced storage overhead for blockchain nodes and optimized communication protocols. the results highlight the feasibility and benefits of decentralized, edge-enabled smart home solutions in improving user experience and system reliability. © 2024 IEEE.

关键词： Smart homes

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Service Discovery and Provisioning in Social Digital Twin Networks: a Name-based Approach 20

Service Discovery and Provisioning in Social Digital Twin Ne...

引用

2024 international conference on Wireless and Mobile computing Networking and Communications

作者： Amadeo, Marica Ruggeri, Giuseppe Marche, Claudio Nitti, Michele Univ Mediterranea Reggio Calabria Reggio Di Calabria Italy Univ Cagliari Cagliari Italy

ISBN: (纸本)9798350387452;9798350387445

Digital Twin (DT) technology is expected to cover a crucial role in a variety of 6G application scenarios, including smart automotive, smart home and smart city. By leveraging advanced Artificial Intelligence (AI) modules alongside cutting-edge communication and networking architectures, DTs will be able to develop cognitive and social skills and build relationships with each other, thus facilitating the sharing of services and experience. However, in current implementations, DTs typically engage with their physical counterpart only, for predictive maintenance and optimization, while protocols for inter-twin communications and service discovery are still unexplored. In this paper, we focus on service discovery and provisioning in DT networks hosted at the network edge. In our design, the Social internet of things (SIoT) notion is applied to build social networks among DTs and, in parallel, name-based primitives, according to the Information Centric Networking (ICN) paradigm, are considered to support inter-twin interactions. Two distributed name-based service discovery mechanisms are envisioned: a social-driven scheme, leveraging friendship and similarities among DTs' names, and a network-driven scheme, leveraging the ICN forwarding fabric only. A performance evaluation shows the benefits of the conceived solution in terms of reduced discovery latency compared to legacy centralized approaches.

关键词： Digital Twin Social internet of things Information Centric Networking Inter-twin Communications

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Design and Application of Image Recognition Framework Based on Cloud Edge Collaboration in Distribution Stations 5

Design and Application of Image Recognition Framework Based ...

引用

5th IEEE international conference on Power, Intelligent computing and Systems, ICPICS 2023

作者： Wu, Wenwei Zhang, Lishou Kang, Kai Liu, Juntao State Grid Shanghai Municipal Electric Power Company Construction and Operation Center Shanghai China Shanghai Yitong Information Technology Co. Ltd R and D Department Shanghai China

ISBN: (纸本)9798350333442

Targeted on the intelligent identification and cloud load reduction requirements of power system in video monitoring, a vision analysis system platform and implementation scheme for distribution station based on cloud edge system are proposed. through multi-source data fusion analysis, optimization of defect fault location, image recognition algorithm, cloud edge threshold classification collaboration, image processing and feature extraction technologies such as YOLOv3, Mask-CRNN, etc., the high-definition real-time image is analyzed, and the main equipment status recognition and security abnormal behavior recognition functions of the distribution station are realized. the real-time and accuracy of each analysis function is verified by the on-site distribution station, and the relevant experimental results of some functions in the power grid are compared to show the effectiveness of the system scheme. © 2023 IEEE.

关键词： internet of things

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Detection and Prognosis of Pulmonary Tuberculosis Using ML Classifiers with Soft computing 5

Detection and Prognosis of Pulmonary Tuberculosis Using ML C...

引用

5th IEEE international conference on computing, Power, and Communication technologies, IC2PCT 2024

作者： Bisht, Girish Singh Ganesh, D. Kumar, Santosh Tula's Institute Department of Computer Science and Engineering Dehradun India Department of Computer Science and Information Technology Bangalore India Noida Institute of Engineering and Technology Department of Internet of Things Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350383522

Several intriguing research works on soft computing techniques have recently been presented and for the creation of a pulmonary TB diagnosis system, researchers continue to build an accurate and trustworthy intelligent decision-making approach. the current diagnostic testing system processes are cumbersome and time-consuming to analyse. Since increased sensitivity and specificity can be attained, the diagnosis of TB still has to be improved upon using new speedy and accurate diagnostic models and procedures, which will help with disease prevention and control. therefore, this review paper's significance lies in its ability to discriminate between the many soft computing methodologies used to help the diagnosis, identification, prediction, and intelligent categorization of pulmonary TB illness. Researchers and medical professionals anticipate employing soft computing methods in the field. 'Artificial neural networks, genetic algorithms, support vector machines, fuzzy logic', and others are a few of these. the most recent diagnostic techniques involve artificial neural networks. Predictive inference accuracy and easy-to-optimize, adoptable non-linear modelling of large data sets are some additional advantages of artificial neural networks, showing that they could be an important decision support tool in a variety of industries, including medicine. © 2024 IEEE.

关键词： Artificial Neural Network Fuzzy and Fuzzy Logic Genetic Algorithm Pulmonary Tuberculosis Support Vector Machine

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Fededrated Learning: Research, Challenges, and Future Directions 5

Fededrated Learning: Research, Challenges, and Future Direct...

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5th IEEE international conference on computing, Power, and Communication technologies, IC2PCT 2024

作者： Kaswan, Kuldeep Singh Dhatterwal, Jagjit Singh Yadav, Rishika Malik, Kiran Tripathi, Aanjey Mani Galgotias University School of Computing Science and Engineering UP Greater Noida India Artificial Intelligence and Data Science Koneru Lakshmaiah Education Foundation AP Guntur India Graphic Era Hills University Department of Computer Science and Engineering Uttarakhand Dehradun India Mriem Department of Computer Science and Engineering Rohtak India Galgotias University School of Computing Science and Engineering Greater Noida India

ISBN: (纸本)9798350383522

Federated Learning, a disruptive and novel aspect of machine learning, is at the forefront of decentralized, privacy-conscious data processing. this in-depth review study navigates the complex environment of Federated Learning Ecosystems, attempting to extract the core of the topic while shining light on its research horizons, pressing difficulties, and promising approaches. Our trip begins with a look at the fundamental concepts of Federated Learning, emphasizing its importance in the landscape of distributed machine learning paradigms. We track its development via historical milestones and key contributions, offering context for the field's increasing research. this study focuses on the many features of Federated Learning research, including privacy-preserving techniques, communication protocols, aggregation approaches, and real-world applications. We aggregate major results and advances within these domains, highlighting notable authors and their contributions. However, the route to Federated Learning's full fulfillment is plagued with difficulties, including questions about privacy, communication efficiency, and scalability. In the future, we will enlighten the growing paths of Federated Learning research, forecasting trends, providing insights into overcoming present problems, and visualizing its integration into diverse fields. To summarize, this review article serves as a guidepost for scholars, practitioners, and enthusiasts wanting to understand the vast domain of Federated Learning. It captures the core of this dynamic discipline, offers strategic counsel for resolving its obstacles, and encourages optimism about its bright future within the domain of distributed machine learning paradigms. © 2024 IEEE.

关键词： Data Analysis distributed Environments Edge computing Federated Learning Machine Learning

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Development of Online Clearance System Using Web-Based System 5

Development of Online Clearance System Using Web-Based Syste...

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5th IEEE international conference on Electrical, Computer and Communication technologies, ICECCT 2023

作者： Alsideiri, Abir Tawafak, Ragad M Alfarsi, Ghaliya Khudayer, Baidaa Hamza Cob, Zaihisma Che Buraimi University Collage College of Computing and Informatics Department of Information Technology Buraimi Oman Selangor Kajang Malaysia Buraimi University Collage Department of Information Technology Buraimi Oman Selangor Kajang Malaysia

ISBN: (纸本)9781665493604

Computer Software, an Online-based clearance system, is an internet-based system that effectively manages information for colleges and universities. the aim of this study is to develop software for graduated services and follow up to replace the manual method of clearance for graduating students. the system serves as a more reliable and effective means of removing all forms of delay and enabling an understanding of the procedures involved and how to do online clearance. the data was collected from the BUC collage. the method used to develop software for easy service after graduation. the online clearance system was implemented using Basic Visual 2015 for all static and dynamic programming and MYSQL to manage the database. the finding reveals a significant use of the software. the application reveals the effectiveness and efficiency of these services' software. © 2023 IEEE.

关键词： Dynamic programming

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Blockchain-driven System for Authentication and Authorization 5

Blockchain-driven System for Authentication and Authorizatio...

引用

5th IEEE international conference on computing, Power, and Communication technologies, IC2PCT 2024

作者： Kumar, Aman Raheja, Devansh Rawal, Jatin Yadav, Anup Lal Chandigarh University Cse Department Punjab India

ISBN: (纸本)9798350383522

Security is really important when it comes to cloud computing services, and authentication and authorization are key to making sure no one can get in. We already have some traditional ways to access cloud services, but we also need to make sure no one else can get in cloud services. We have some traditional centralized access control models for the authentication and authorization which is third party based model which faces a critical challenge due to a high trust cost and a single point of failure. So for handling such type of challenges, Blockchain achieve the distributed trust for access control designs. Blockchain provides a dynamic update of access permissions by syncing the smart contract. To improve the storage efficiency and system scalability and to record a user's access privileges only one transition is required. the system is up and running, the content of the smart contracts can be executed when trigger conditions are fulfilled, data is uploaded and network access is achieved, and processing is completed. the protocol combines the authentication and integrity properties of blockchain architectures suitable for power systems with the new blockchain technique to allow identity verification and source authorization in smart grid systems. © 2024 IEEE.

关键词： access access control authentication authorization Block-chain mobile cloud computing security

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Enhanced Web based Multi-Platform E-voting Solution 5

Enhanced Web based Multi-Platform E-voting Solution

引用

5th international conference on Smart Electronics and Communication, ICOSEC 2024

作者： Nallapareddy, Anusha Swapna, T. Shanmugam, Sundaramurthy Shabu, Jany Refonaa, J. Hyderabad India G Narayanamma Institute of Technology and Science Department of Computer Science and Engineering Hyderabad India Srm Institute of Science and Technology Department of Computing Technologies Chennai India Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331504403

In democratic nations such as India, the act of voting is a basic right that grants individuals the power to choose their leaders. Traditionally, voting has typically taken place at specific locations called polling booths, either in centralized or distributed. Every Indian citizen above 18 years of age has the right to vote and participate in choosing their representatives. Voters go to the polling booths where they can cast their votes under the observation of authorized individuals. However, this traditional voting system has various challenges such as low voter turnout and instances of fraudulent voting. To address these issues, a secure multi-platform E-Voting system is proposed in this research, developed using the Flutter framework and Firebase backend services. the system aims to verify each voter before they can cast their vote, employing multiple levels of verification. the proposed application consists of an administrator (admin) interface and a voter interface. the admin interface allows for the addition of elections, candidates, and constituencies, while the voter interface requires voters to register, log in, and cast their vote. the verification process includes One Time Password (OTP) authentication, face recognition, fingerprint verification, and validation through government-issued identification cards. Two commonly used identification cards in India are the Aadhaar card and the Permanent Account Number (PAN) card, which are unique to each citizen. By utilizing this proposed online voting application, eligible voters can conveniently cast their votes from anywhere in the world, using internet-connected devices like mobile phones or tablets. the primary objectives of the proposed system are to increase voter turnout and reduce instances of fraudulent voting. Furthermore, conducting elections through this application also helps reduce the required workforce. © 2024 IEEE.

关键词： Authentication

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A lightweight, fully-distributed AI framework for energy-efficient resource allocation in LoRa networks 16

A lightweight, fully-distributed AI framework for energy-eff...

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16th IEEE/ACM international conference on Utility and Cloud computing (UCC) / 10th IEEE/ACM international conference on Big Data computing, Applications and technologies (BDCAT)

作者： Scarvaglieri, Antonio Palazzo, Sergio Busacca, Fabio Univ Catania Catania Italy

ISBN: (纸本)9798400702341

As the internet of things (IoT) continues to grow rapidly, efficient resource utilization is crucial for the sustainability and performance of IoT networks. In this context, LoRa technology, known for its low-power, long-range communication, has become popular for IoT applications. However, the limited energy and spectrum resources in Long Range (LoRa) networks present challenges in achieving optimal network performance in dense deployments. In particular, existing centralized approaches, such as LoRa Adaptive Data Rate, may fail to scale up to the large networks typical of IoT scenarios. To address all of these issues, we propose a smart, fully-distributed resource allocation scheme based on multi-agent cooperative Q-learning approach. Simulations results prove that our approach improves the Packet Delivery Ratio (PDR) and reduces the energy consumption of up to 43% as compared to fixed SF and random non-smart strategies, respectively, while also keeping the decision process at a device-level, with no centralized entities involved.

关键词： LoRa IoT Reinforcement Learning LPWANs Q-Learning distributed Decisioning

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Exploring Methods of Mitigation against DDoS Attack in an IoT Network 7

Exploring Methods of Mitigation against DDoS Attack in an Io...

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7th international conference on Inventive Computation technologies, ICICT 2024

作者： Prajapati, Piyush M. Gandhi, Priyesh P. Degadwala, Sheshang Gujarat Tech. University Gujarat Ahmedabad India Sigma University Gujarat Vadodara India Sigma University Dept. of Comp. Eng Gujarat Vadodara India

ISBN: (纸本)9798350359299

Smart homes and industrial systems alike have benefited greatly from the increased connection and ease made possible by the explosion of internet of things (IoT) devices. Nevertheless, distributed Denial of Service (DDoS) assaults have become more common due to the widespread use of these linked devices, which has put IoT networks at risk. In order to protect IoT networks against distributed Denial of Service (DDoS) assaults, this study looks into the topic and suggests new ways to do so. the research delves into advanced tactics, such as adaptive traffic filtering, anomaly detection, machine learning algorithms, and hardware-based solutions, by examining the specific vulnerabilities of IoT ecosystems. Also covered is the possibility of using edge computing for mitigation and detection in real-time. through simulations and experiments, the research evaluates the performance and efficacy of these methods under diverse attack scenarios, considering resource constraints and scalability. the findings not only contribute to academic discussions on IoT security but also provide practical insights for industry practitioners and policymakers. the research aims to enhance the resilience of IoT networks, ensuring the integrity, availability, and confidentiality of data in the face of evolving DDoS threats. © 2024 IEEE.

关键词： internet of things

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