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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Kirti, Atul Das, Ankita Priyanka, R. SRM Institute of Science and Technology Faculty of Engineering and Technology Department of Networking and Communications School of Computing Tamil Nadu Kattankulathur603203 India

ISBN: (纸本)9798350365269

Farming and agriculture is the backbone of every country's economy thus plays a crucial role in the overall growth and development of its economic status. The respective governments of every country do their best when it comes to supporting the farmers in terms of various aids such as subsidized fertilizers, pesticides, medicines etc. at discounted rates by allocating a huge chunk of tax payers money into various schemes. But do these schemes are effective enough? Are the targeted people getting these benefits? Is the revenue invested in these subsidies being utilized to its potential? The short answer is 'NO' because most of the subsidies are being exploited by middle men. A major chunk of the resources are either sold at profits or are simply designated to farmers in an uneven manner where needy farmers get very little resources and greedy middle men make profits of these resources because of unorganized distribution of subsidies. In this paper we will discover ways by which accurate distribution of subsidized resources can be made so that targeted farmer's needs can be fulfilled without the resources being wasted and black marketed. By enabling the methods discussed in this paper, governments can save huge chunk of taxpayer's money on unorganized distribution of resources thus improving their budget on several other required domains. © 2024 IEEE.

关键词： Profitability

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Voice Controlled Wheelchair 4

Voice Controlled Wheelchair

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4th International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Venkatakrishnan, G.R. Rengaraj, R. Jeya, R. Pozhilan, G. Venkat, C. Shiva Adithyaa, T. Thejas Sri Sivasubramaniya Nadar College of Engineering Kalavakkam Chennai India Srm Institute of Science and Technology Computing Technologies Kattankalathur Chennai India

ISBN: (纸本)9798331508845

The require for programmed Wheelchair is particularly show in care of undaunted individuals (individuals with tireless vegetative state, paraplegia, stroke and spinal line wounds), where the care requires a part of time and labor. This report is the result of a plan and advancement of an computerized multifunctional Wheelchair that would perform all capacities display in today's Wheelchair (Wheelchair with flexible parcel of back rest and leg rest additionally farther control with which we are able give all fundamental development) as well as modern capacities of fitting Wheelchair segments ( leg positions altering). It is anticipated that this modern programmed Wheelchair would empower people's superior therapeutic care, and would significantly decrease time and labor to the old-age domestic staff. Hence, The purpose of this model is to plan, design and build a wheelc hair audio control system. The frame of the wheelchair include a motor frame and a voice recognition module controlled by a microcontroller. Hence, the created voice controlled wheelchair can give simple get to for individuals with physical inability additionally offer programmed security from impediment collision in case the botch of any voice commands happens. © 2024 IEEE.

关键词： Wheelchairs

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Achieving Seamless Semantic Interoperability and Enhancing Text Embedding in Healthcare IoT: A Deep Learning Approach with Survey

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SN Computer science 2024年第1期5卷 99页

作者： Purushothaman, Sony Shanmugam, G. Siva Nagarajan, Sureshkumar School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Computer Science Govt. Model Engineering College Kerala Kochi India Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Tamil Nadu Krishnakovil India

Achieving semantic interoperability in healthcare is one of the significant challenges in the rapidly expanding healthcare sector. On the other hand, IoT in healthcare can provide patient-centric treatment mechanisms to help resolve these issues. When several healthcare organizations are generating heterogeneous medical information, semantic interoperability becomes essential to develop better treatment plans and better medical research. In this article, we discuss the applications of healthcare IoT, a comparative study of existing solution paradigms for achieving semantic interoperability and its enabling technologies. The comprehensive analysis of semantic interoperability has versatile dimensions to meet this, and it establishes deep learning-based directions. In continuing the background work, we proposed a new deep learning model called MedRelBERT with six embeddings to remove linguistic ambiguities in medical documents. The survey also examines the bibliographic evaluation of Web of science articles discussing semantic interoperability solutions. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Deep learning Internet of medical things Privacy Semantic interoperability

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Navigating IoT Security:Insights into Architecture,Key Security Features,Attacks,Current Challenges and AI-Driven Solutions Shaping the Future of Connectivity

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Computers, Materials & Continua 2024年第12期81卷 3499-3559页

作者： Ali Hassan N.Nizam-Uddin Asim Quddus Syed Rizwan Hassan Ateeq Ur Rehman Salil Bharany Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan Department of Biomedical Engineering HITEC UniversityTaxila47080Pakistan Department of Electronics Engineering University of ChakwalChakwal48800Pakistan Department of Computer Science NFC Institute of Engineering and Fertilizer ResearchFaisalabad38000Pakistan School of Computing Gachon UniversitySeongnam-si13120Republic of Korea Chitkara University Institute of Engineering and Technology Chitkara UniversityRajpura140401PunjabIndia

Enhancing the interconnection of devices and systems,the Internet of Things(IoT)is a paradigm-shifting *** security concerns are still a substantial concern despite its extraordinary *** paper offers an extensive review of IoT security,emphasizing the technology’s architecture,important security elements,and common *** highlights how important artificial intelligence(AI)is to bolstering IoT security,especially when it comes to addressing risks at different IoT architecture *** systematically examined current mitigation strategies and their effectiveness,highlighting contemporary challenges with practical solutions and case studies from a range of industries,such as healthcare,smart homes,and industrial *** results highlight the importance of AI methods that are lightweight and improve security without compromising the limited resources of devices and computational *** networks can ensure operational efficiency and resilience by proactively identifying and countering security risks by utilizing machine learning *** study provides a comprehensive guide for practitioners and researchers aiming to understand the intricate connection between IoT,security challenges,and AI-driven solutions.

关键词： Internet of Things(IoT) artificial intelligence(AI) IoT architecture security attacks in IoT

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Enhancing TCP Congestion Control: A Comparative Analysis, and Algorithmic Modifications using NS2

Enhancing TCP Congestion Control: A Comparative Analysis, an...

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2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024

作者： Thangam, S. Trisha, K. Hima Sree, N. Reddy P, Srinithya Balakrishnan, Sivaneasan Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bengaluru India Singapore Institute of Technology Singapore

ISBN: (纸本)9798350309140

The transmission control protocol is essentially a computer network protocol and ensures the reliability of the transmitted data. TCP's congestion control algorithms support network performance and stability. Network congestion has become a major issue in network analysis. TCP (Transmission Control Protocol) Congestion control algorithms ensure smooth transmission of data across networks. This work examines TCP congestion algorithms. The main objective is to increase its efficiency and modify the algorithm. A detailed performance analysis of the enhanced TCP congestion control algorithms namely Tahoe, New Reno, and Vegas is performed and simulations are used to evaluate its performance under different network conditions such as high latency, constant bit rate (CBR) bandwidth load, and varying traffic loads. Metrics such as latency, throughput, and round-trip time are analyzed under the scenarios using ns-2 simulator. © 2024 IEEE.

关键词： Transmission control protocol

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Cyber-Attacks and Anomaly detection on CICIDS-2017 dataset using ER-VEC 2

Cyber-Attacks and Anomaly detection on CICIDS-2017 dataset u...

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Jha, Ravi Shankar Ojha, Kushagra Mishra, Aryan Mishra, Riya Kaushik, Abha School of Computing Dit University Dehradun India Computer Science and Engineering Gl Bajaj Institute of Technology and Management Greater Noida India

ISBN: (纸本)9798350371055

Securing a network the preliminary defense mechanisms of applied Security Compliance along with IDS (Intrusion Detection System) and IPS (Intrusion Prevention System) that are applied all over the networks to block the passage of malicious content into it. With the advent of modern technologies and innovations in every field, there has been a significant load on the security architecture to provide for faultless, secure, and robust infrastructure. In today's modern day, firewalls are capable of blocking a major portion of malicious activity from creeping into the network. Still, attackers have been successful in penetrating in the form of internal attacks and can perform their targeted exploitation, like denial of service, link failures, ransomware, and so on, which has disastrous consequences. Thus, such anomalies do occur that pose a threat to data security and the underlying structure. This study aims to propose a novel technique, including the use of ER-VEC (Extra-Tree Random Voting Ensemble Classifier), to classify various attack network packets into benign and suspicious categories. We also did comparisons with SVM(support vector machine), DT (decision tree), RF(random Foreset), and EXTC(extra tree extension) proposed by other researchers, to testify our models we have also tested and compared on the same datasets, and compared the results proved to be more effective and efficient than the previous methodologies. This article started with a section introduction then section two related work which included with problem statement, section three with the proposed predicted model, then we covered result analysis and comparative study with proposed strategies by other researchers and conclusion and future scope. © 2024 IEEE.

关键词： anomaly cyber-attack IDS cybersecurity detection DT ER-VEC EXTC firewall IPS RF

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Joint Communication and Computation Resource Allocation for Emerging mmWave Multi-User 3D Video Streaming Systems

Joint Communication and Computation Resource Allocation for ...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Badnava, Babak Chakareski, Jacob Hashemi, Morteza University of Kansas Department of Electrical Engineering and Computer Science United States New Jersey Institute of Technology College of Computing United States

ISBN: (纸本)9798350351255

We consider a multi-user joint rate adaptation and computation distribution problem in a millimeter wave (mmWave) virtual reality (VR) system. The VR system that we consider comprises an edge computing unit (ECU) that serves 360° videos to VR users. We formulate a multi-user quality of experience (QoE) maximization problem, in which VR users are assisted with the ECU to decode/render 360° videos. The ECU provides additional computational resources that can be used for processing video frames, at the expense of increased data volume and required bandwidth. To balance this trade-off, we leverage deep reinforcement learning (DRL) for joint rate adaptation and computational resource allocation optimization. Our proposed method, dubbed Deep VR, does not rely on any predefined assumption about the environment and relies on video playback statistics (i.e., past throughput, decoding time, transmission time, etc.), video information, and the resulting performance to adjust the video bitrate and computation distribution. We train Deep VR with real-world mmWave network traces and 360° video datasets to obtain evaluation results in terms of the average QoE, peak signal-to-noise ratio (PSNR), rebuffering time, and quality variation. Our results indicate that the Deep VR improves the users' QoE compared to state-of-the-art rate adaptation algorithm. Specifically, we show a 3.08 dB to 4.49 dB improvement in video quality in terms of PSNR, a 12.5x to 14x reduction in rebuffering time, and a 3.07 dB to 3.96 dB improvement in quality variation. © 2024 IEEE.

关键词： Video streaming

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Improving energy efficiency in scalable WSNs through IoT-driven approach

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International Journal of Information Technology (Singapore) 2025年 1-11页

作者： Singh, Omkar Kushwaha, Ajay Shriram Sharma, Col. Rahul Kumar, Lalit National Institute of Fashion Technology Bihar Patna India Department of Computer Science & Application Sharda School of Computing Sciences & Engineering Sharda University UP Greater Noida India School of Computer Science & Engineering ILM University Greater Noida India

A novel QoS-Driven Optimization for Energy-Efficient Clustering Routing (QDOEECR) protocol tailored for IoT-based Wireless Sensor Networks (WSNs), addressing the critical challenge of energy efficiency in sensor nodes with limited battery life. The protocol’s innovative approach lies in its advanced techniques for optimizing the selection of sub-sink nodes and identifying the optimal path to the sink node, ensuring improved adherence to Quality of Service (QoS) standards. Performance evaluations, conducted through MATLAB simulations, demonstrate the QDOEECR protocol's superior performance, achieving significant advancements over existing routing protocols. These include 30–35% reduction in end-to-end delay, 25–30% improvement in throughput, 35–40% decrease in energy consumption, 28–32% reduction in packet loss, and 32–38% extension in network lifetime. These results establish QDOEECR as a groundbreaking solution that not only enhances energy efficiency but also elevates network performance metrics beyond the capabilities of current state-of-the-art protocols like CBCCP, HCSM, and ZEAL. © Bharati Vidyapeeth's institute of Computer Applications and Management 2025.

关键词： CBCCP HCSM IoT QDOEECR WSN ZEAL

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Performance Evaluation of Different Optimization Techniques for TMIV Immersive Video Streaming 2nd

Performance Evaluation of Different Optimization Techniques ...

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2nd Congress on Control, Robotics, and Mechatronics, CRM 2024

作者： Bhuyan, Aklanta Niraz Dwaraknath, Thrishalini Saranya, G. Department of Networking and Communication School of Computing College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur 603203 India

ISBN: (纸本)9789819768097

Cloud-based immersive video streaming is a growing technology that has the potential to revolutionize how we consume entertainment and media. However, some challenges need to be addressed, such as delivering high-quality video to users with internet speed and processing capabilities. One way to tackle these obstacles is by optimizing the configuration of Three-Dimensional Image View (TMIV) for encoding and streaming videos in cloud environments. This study thoroughly compares optimization techniques including learning, reinforcement learning, and heuristic methods. The authors also investigate the impact of factors like usage decoding time and video quality. To effectively evaluate their proposed approach, diverse video datasets and different streaming conditions are utilized. The findings demonstrate improved decoding time and video quality utilization compared to traditional TMIV optimization methods. As a result, this technique holds the potential for enhancing the experience of immersive video streaming in applications such as virtual reality, augmented reality, and 360° videos, which are examples of immersive digital experiences. Furthermore, it offers the added benefit of reducing both requirements and computational resources needed for streaming videos—thus enabling better accessibility for users with limited resources. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Video streaming

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CDGNet: A Cross-Time Dynamic Graph-Based Deep Learning Model for Vehicle-Based Traffic Speed Forecasting

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-14页

作者： Fang, Yuchen Luo, Haiyong Zhao, Fang Sun, Poly Z.H. Qin, Yanjun Zeng, Liang Hui, Bo Wang, Chenxing School of Computer Science National Pilot Software Engineering School Beijing University of Posts and Telecommunications Beijing China Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Chinese Academy of Sciences Beijing China Department of Industrial Engineering School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China Tsinghua University Beijing China University of Tulsa Tulsa USA

Vehicle-based traffic speed forecasting aims to predict the average speed of vehicles on the road in the future, which is an essential side information in intelligent vehicles and beneficial to safe autonomous driving, yet is very challenging due to the complex and dynamic spatio-temporal dependencies in real-world vehicle-based traffic. To extract intricate correlations among multiple vehicle-based speed time series, previous methods have used graph convolution networks. However, the conventional static and dynamic graphs fail to reflect the traffic evolution and the hysteresis spatial influence caused by vehicle movement. To address this issue, we propose a novel cross-time dynamic graph-based deep learning model, named CDGNet, for vehicle-based traffic speed forecasting. The model is able to effectively capture hysteresis spatial dependencies between each time slice and its historical time slices through the cross-time dynamic graph-based GCN. Meanwhile, a gating mechanism is integrated into our cross-time dynamic graph, which conforms to the sparse correlation in the real world. Besides, GCNs are incorporated into a novel encoder-decoder architecture to forecast multi-step speed. Experimental results on three real-world vehicle-based traffic speed datasets demonstrate the superiority of our CDGNet over various state-of-the-art spatio-temporal forecasting methods and the effectiveness of each component. We additionally provide a visualization of our cross-time dynamic graph to show the capability of assisting intelligent vehicles to avoid congestion. IEEE

关键词： Forecasting

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