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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Dinesh Krishna, B.V. Yogendrasai, P. Rajeev, S. Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

VoIP is a revolutionary technology for transmission of voice over internet protocol than from plain telephony systems. But current VoIP solutions have some important issues which are packet loss, latency, and jitter especially when the network is in motion. This work outlines the design, implementation and performance of a locally developed VoIP system which includes a SIP Server Node, Sender Node and a Receiver Node. The SIP Server Node was designed nearly from the ground up to handle session initiation, packet forwarding, and adaptive QoS control. Both Sender and Receiver Nodes had facilities to record, compress and playback audio. The system’s performance was evaluated in a LAN environment, achieving significant improvements in Quality of Service (QoS) metrics: achieving low latency under 150 ms, 95% packet recovery and achieving a good audio quality with the MOS of 4.2. Evaluating the obtained results, it can be concluded that the proposed system is efficient in handling the issues of the packet-switched network and providing high-quality real time voice communication. © 2025 IEEE.

关键词： Packet loss

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Resource investment for DDoS attack resistant SDN: a practical assessment

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Science China(Information Sciences) 2023年第7期66卷 112-129页

作者： Bin YUAN Fan ZHANG Jun WAN Huan ZHAO Shui YU Deqing ZOU Qiangsheng HUA Hai JIN School of Cyber Science and Engineering Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Engineering Research Center on Big Data Security Shenzhen Huazhong University of Science and Technology Research Institute School of Computer Science and Technology Huazhong University of Science and Technology Cluster and Grid Computing Lab School of Computer Science University of Technology Sydney

Software-defined networks(SDNs) present a novel network architecture that is widely used in various datacenters. However, SDNs also suffer from many types of security threats, among which a distributed denial of service(DDoS) attack, which aims to drain the resources of SDN switches and controllers,is one of the most common. Once the switch or controller is damaged, the network services can be *** defense schemes against DDoS attacks have been proposed from the perspective of attack detection;however, such defense schemes are known to suffer from a time consuming and unpromising accuracy, which could result in an unavailable network service before specific countermeasures are taken. To address this issue through a systematic investigation, we propose an elaborate resource-management mechanism against DDoS attacks in an SDN. Specifically, by considering the SDN topology, we leverage the M/M/c queuing model to measure the resistance of an SDN to DDoS attacks. Network administrators can therefore invest a reasonable number of resources into SDN switches and SDN controllers to defend against DDoS attacks while guaranteeing the quality of service(QoS). Comprehensive analyses and empirical data-based experiments demonstrate the effectiveness of the proposed approach.

关键词： SDN security DDoS attacks resource management queueing theory QoS

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Integration of Traffic Shaping with Time-Sensitive Networking for Effective Traffic Management 3

Integration of Traffic Shaping with Time-Sensitive Networkin...

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Penumada, Archana Reddy Gundapaneni, Divya Jyothi Chennupati, Akshitha Rajagopal, Shinu M. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Time-Sensitive Networking (TSN) has recently become an important standard to support time-sensitive reliable low-latency data transmission in industrial and real-time applications. This work explores the use of different traffic shaping algorithms, namely, credit-based shaping (CBS) and time-aware shaping (TAS) alongside frame preemption—a TSN instance which gives precedence to high-importance frames by means of lower-priority traffic interruption—to extend TSN’s traffic management capabilities. By controlling data flow and allowing for high priority packets to pass through unimpeded, traffic shaping algorithms serve an essential function in making the network more efficient and reducing congestion rates. The work compares these algorithms in isolation and also in combination over a network model, comprising of four switches and three end users for each switch, using the OMNeT++ simulation environment. This study aims to contribute insights into optimal shaping techniques for TSN, enhancing its suitability for critical network applications. © 2025 IEEE.

关键词： Traffic congestion

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Comprehensive Web Analysis of Automobile Websites: Performance, SEO, and Accessibility Insights

Comprehensive Web Analysis of Automobile Websites: Performan...

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2025 IEEE International Conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Busetty, Abhishek Balam, Ruchith Chillakuru, Hari Radha, R. Saranya Devi, B. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331512965

The current research work proposes a difficultydriven comparison of three most visited automobile websites namely the Automobile Site1, Automobile Site2, Automobile Site3 on parameters including performance, Search engine optimization (SEO), accessibility and traffic. The research involves tool such as Yellow Labs, Google Page Speed Insight and Semrush with regard to the website's weight, loading time, user's interactions and search engine optimization. The findings reveal distinct strengths across the sites: From the three Automobile Site1 is the most optimized and accessibly friendly site, the factors of search engine friendliness is as follows. Looking at the traffic and users of Automobile Site2, it comfortably outclasses the other sites in terms of page views as well as the audience loyalty. At the same time, Automobile Site3 has relatively low first load time which indicates fast website browsing while it is still relatively weak in terms of its SEO and the usability of the site has to be improved in terms of theoretical potential. In conclusion, the realized comparison exposes the strengths and weaknesses of each site and is informative to future developments of the sites with an aim at better user interaction levels and competitive advantage. © 2025 IEEE.

关键词： Automobiles

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Environmental Monitoring using LoRa and NodeMCU 3

Environmental Monitoring using LoRa and NodeMCU

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Mihir, D.V.S. Pavan, Baramkula Vishnu Datta Aralaguppi, Yogen Avinash Nair, Pranav Biju Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Monitoring of environmental parameters in areas with a sparsely populated and less infrastructure is quite challenging due to issues such as high power consumption, limited range for transmission, and lack of scalability. The innovation of the system proposed here deals with these problems using an IoT-based monitoring system, using LoRa technology and NodeMCU microcontrollers. It can collect and transmit real-time data on temperature, humidity, air quality, and sound levels efficiently. Key outcomes of this research work are reliable range communication up to 2 km under line-of-sight conditions, minimal power consumption, and robust data integrity through sensor calibration and error-checking mechanisms. The solution, which is scalable and low-cost, is proven feasible in real-world applications, particularly in remote and underserved areas, and promises a great future enhancement, including range extension and energy harvesting. © 2025 IEEE.

关键词： Environmental monitoring

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Smart Glasses for Blind Assistance: A Lightweight and Ergonomic Approach 3

Smart Glasses for Blind Assistance: A Lightweight and Ergono...

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Shreevatsan, S.S. Annambhotla, Yasasree Lasya Reji, Anaswara Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

Individuals who are blind or have reduced vision often struggle to navigate their environments, as traditional tools like canes offer limited information. While smart glasses have the potential to assist, existing models face challenges such as being heavy, uncomfortable, expensive, and lacking effective features for real-time navigation. These limitations hinder usability and diminish the overall user experience. This work presents a cost-effective prototype of lightweight and ergonomic smart glasses designed to enhance navigation and safety for individuals with visual impairments. By integrating obstacle detection sensors, real-time feedback mechanisms, and a user-centric design, the proposed solution aims to promote mobility, independence, and comfort while remaining accessible to a wider user base. © 2025 IEEE.

关键词： Obstacle detectors

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Enhancing Underwater Image Captioning Using Transformer Models and Augmented Terrestrial Datasets

Enhancing Underwater Image Captioning Using Transformer Mode...

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Gamidi, Rohan Hemasri, M. Muppala, Tejaswi Vinitha Chowdary, A. Aiswariya Milan, K. Palaniswamy, Suja Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331508685

Underwater environments present unique challenges for image analysis due to light attenuation, scattering, and color distortion, which significantly degrade image quality. These facts make simple operations such as image captioning, which is crucial in marine sciences, search, and conservation, challenging. Current datasets such as Flickr8K contain mostly terrestrial images and do not possess features distinctive to underwater environments therefore direct training of models is not possible in this context. To cover this gap, the current work combines a Transformer-based image captioning model with an enhanced underwater-specific image augmentation set. These augmentations mimic real-life underwater consequences such as RGB attenuation, Gaussian blur, muddy particles, noise, and gradient-based illumination distortions. The implemented model, learned and recursively tuned on the Flickr8k dataset, proves the ability to generate reasonable captions for underwater images even though the dataset belongs to Flickr8k providing a terrestrial environment. This is proven by the enhanced BLEU scores as well as from the results of the experiment which trained the translation model in less than ten percent of the dataset to show its flexibility on underwater scenarios but without necessitating the use of an underwater dataset. © 2025 IEEE.

关键词： Underwater imaging

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Radius-Based Authentication: UFrames’ Novel Approach to Prevent Account Sharing 5th

Radius-Based Authentication: UFrames’ Novel Approach to Pre...

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5th International Conference on computing and Network Communications, CoCoNet 2023

作者： Vardhan, D. Sai Tanmayi, Doddapaneni Rakesh, Kakaraparthi Sreevidya, B. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9789819745395

OTT platforms such as Netflix and Amazon Prime have been in the market for more than a decade. They have come to full-fledged usage especially during the lockdown. The main reason for their magnanimous success is ease of use and feasibility to access unlimited content anywhere and anytime with basic Internet connection. The features in OTT have made accessing the content and viewing the content easy and delightful for the users. However, the "sharing account" option enabled for a single user to access the content from multiple devices is instead being used to share one account among multiple users, negatively affecting the business of OTT creators. In this paper, the focus is to build an OTT platform that proves advantageous to both users and providers. Besides the prevailing features that are found across platforms, including sign-in and sign-up functionalities, categorized content selection, and payment options, the proposed system enables automatic sign-out when the non-primary device strays beyond range from the primary device, content uploading, and more. Furthermore, there is a proposal to implement a GPS technology-based mechanism aimed at preventing users from sharing their accounts with others. The proposed approach conceptually and experimentally proves to be beneficial to the OTT platforms from a business perspective. The scheme is able to prevent users from sharing the account beyond a geographical limit, thus improving the profit. At the same time, these stringent requirements are developed in such a way that a balance is made between user experience, ease of use experience along with improved security measures. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Global positioning system

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Dual-Plate Verification System for Vehicle Identifcation using IoT and Embedded Systems 3

Dual-Plate Verification System for Vehicle Identifcation usi...

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Sampath, A.V.S.S. Malagati, Nischal S. Kanapathi, V. Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

This research uses a dual-plate verification system for improving vehicle security by using IoT and embedded systems. The system compares front and rear license plates to detect any anomaly, which signals unauthorized modifications. Using real-time image processing and IoT-based data communication, this solution gives us an accurate plate matching system, making sure of reliable vehicle identity verification. Its possible applications include traffic monitoring, parking management, and detecting any unlawful activity. This project is unique because it integrates the dual plate verification system with an Arduino IoT setup. For hassle-free text recognition, this system uses deep learning frameworks combined with a wireless mobile setup that serves as a camera. The system’s accuracy is shown through experiments, displaying its value in improving transportation security with automation. The number plates were detected, and the respective penalties for the vehicles were imposed accordingly. © 2025 IEEE.

关键词： Anomaly detection

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Enhancing Air Quality Index Forecasting through Machine Learning Models 3

Enhancing Air Quality Index Forecasting through Machine Lear...

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3rd International Conference on Intelligent Systems, Advanced computing, and Communication, ISACC 2025

作者： Reddy, Kamalapuram Vigneswara Begum, Chimakurthy Mounika Neeraja, Adhi Jyotsna, C. Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering India

ISBN: (纸本)9798331523893

Air pollution poses serious health risks, including respiratory issues and hospitalization. This study focuses on predicting the Air Quality Index (AQI) in Delhi, leveraging data from monitoring stations and machine learning models like linear regression, support vector regression, and tree-based methods such as decision trees and random forests. Results show that the Decision Tree Regressor outperformed other models, achieving the lowest Root Mean Squared Error (RMSE) and highest R-squared (R2) values. Incorporating and advanced preprocessing enhanced accuracy, addressing seasonal variations in air quality data. The findings emphasize the value of machine learning in accurate AQI forecasting, supporting policy decisions, and improving urban air quality management. This research highlights the critical role of predictive models in mitigating air pollution's impact and protecting public health while suggesting pathways for future advancements in real-world applications. © 2025 IEEE.

关键词： Air quality

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