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3rd International Conference for Advancement in Technology, ICONAT 2024

作者： More, Pravin Baban Jadhav, Amolkumar N. Khatik, Irfan Singh, Sonam Borate, Vishal Kisan Mali, Yogesh Kisan Annasaheb Dange Colleg of Engineering & Technology Department of CSE Ashta India Fergusson College Pune India Dr D y Patil Institute of Technology Department of AIML Pune India Dr D y Patil College of Engineering & Innovation Talegaon Department of Computer Engineering Pune India G.H Raisoni College of Engineering and Management Wagholi Department of AIML Pune India

ISBN: (纸本)9798350354171

Communication is an essential part of life, but it can be a significant challenge for those who cannot speak. That's why we are working on a research project to develop a real-time American Sign language (ASl) detector using computer vision and machine learning. Our goal is to create a solution that has the potential to transform the lives of people who rely on sign language. Imagine the frustration of wanting to express yourself or use voice-activated technology without the ability to speak. While sign language interpreters are a valuable resource, their cost can be a significant barrier to consistent access. © 2024 IEEE.

关键词： Gesture recognition

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Trust based Relay Node Selection and Efficient Multihop Clustering for VANETs 1

Trust based Relay Node Selection and Efficient Multihop Clus...

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1st Asian Conference on Communication and Networks, ASIANComNet 2024

作者： Hariz, Hussein Muhi Hashim, Mohammed I. Thiyagu, T.M. Hameed, Riyadh Rashid Hadi, Maysam Reyad Abbas, F.H. Mazaya University College Department of Computer Techniques Engineering DhiQar Iraq The Islamic University College of Technical Engineering Department of Computer Technical Engineering Najaf Iraq Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Department of Computer Science and Engineering Chennai India National University of Science and Technology Dhi Qar Iraq Altoosi University College Department of Computer Science Najaf Iraq Al-Mustaqbal University Medical Laboratories Techniques Department Hillah Iraq

ISBN: (纸本)9798350367003

In this article, trust-based relay node selection and efficient multi hop clustering model (TRSEMC) is developed. The core modules of this model are efficient network construction, multi hop clustering and vertical trust management. Even through this process the efficiency is greatly increased and that leads to expanding the life span of the devices. The proposed concept is constructed in the simulator called NS3 and he matrix which are taken to analyses the performance of the network are throughput, network delay, routing overhead, transmission accuracy and energy efficiency. This TRSEMC greatly fulfills the identified research gap and through an effective clustering mechanism the efficiency of the vehicles is increased than the SVCHT-UAV, FMMTC-UAV and GRTMI-UAV models. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Fashion Recommendation System for E-Commerce using deep learning Algorithms 15

Fashion Recommendation System for E-Commerce using Deep Lear...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Arunkumar, M.S. Gopinath, R. Chandru, M. Suguna, R. deepa, S. Omprasath, V. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Tamilnadu Chennai62 India K. S. Rangasamy College of Technology Department of Computer Science and Engineering Tiruchgode India College Department of Computer Science Erode India Bannari Amman Institute of Technology Department of Computer science and Engineering Sathyamangalam India Kongu Engineering College Department of Computer Technology - Pg Erode Tamilnadu Perundurai638060 India Kongu Engineering College Erode Tamilnadu Perundurai638060 India

ISBN: (纸本)9798350370249

In the increasingly competitive outlook of ecommerce, personalized recommendation systems have emerged as pivotal tools to enhance user experience and drive sales. This paper proposes a novel Fashion Recommendation System (FRS) leveraging deep learning techniques to offer personalized fashion suggestions to users. The system utilizes a combination of convolutional neural networks (CNNs) for image feature extraction. Through a comprehensive analysis of user interactions and preferences, the FRS generates tailored recommendations that align with individual style preferences and current trends. The work proposes a novel approach that utilizes the ResNet50 algorithm to analyze images of fashion items, extracting meaningful features that capture the essence of style, color, and texture. By training the ResNet50 model on vast datasets of fashion images, thereby enhancing its ability to make accurate recommendations. Through the integration of user preferences and historical data, this system can generate personalized fashion recommendations tailored to each user's unique style and preferences, thus enhancing user satisfaction and engagement. By harnessing the power of deep learning and the ResNet50 algorithm, fashion retailers can offer personalized shopping experiences, increase customer retention, and drive sales. © 2024 IEEE.

关键词： Convolutional Neural Networks deep learning E-commerce Fashion Recommendation System Fashion Retailers Personalization ResNet50 Algorithm User Experience

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Unlocking the Experimental Possibilities of a logical Wireless Power Transfer System design for Charging Electric Vehicles Through High Intensity Concentration

Unlocking the Experimental Possibilities of a Logical Wirele...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Rani, A. Jaya Mabel Selvi, d.M. Kalai Saranya, d. Rathika, S. Sharma, V. Rama Krishna Shobana, d. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India R.M.D Engineering College Department of Cse Tamil Nadu Chennai India St Joseph's College of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Master of Business Administration Tamil Nadu Chennai India Mlr Institute of Technology Department of Ece Hyderabad India Rajalakshmi Engineering College Department of Mechatronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350375237

An exciting new direction in electric vehicle (EV) energy supply system development is the wireless power transfer (WPT) method. The WPT outshines plug-in hybrid electrical charging systems in many respects, including its compact battery size, low weight, rapid charging capabilities (charging-in-motion services), and extensive range while on the go. After establishing the framework and categorization of the WPT system, this article goes on to examine the fundamentals of the most well-known WPT method, electromechanical reactive resonance transmission. Through the use of wireless technology, known as wireless power transfer (WPT), electric energy may be sent wirelessly from an energy source to a load. With their numerous benefits over their wired counterparts - including the elimination of exposed cables, simplified charging, and unfaltering transfer of power even in harsh environments - wireless power transceivers (WPTs) are finding widespread usage in industrial settings. Several businesses are considering using WPTs to power the electric vehicle (EV)'s internal batteries, and they're working to enhance and advance the many related topologies. The low-cost inductive connection of two coils, the transmitter and receiver coils, allows for WPT to function. The transmitter coils for electric car charging applications are buried under the road, while the receiver coils are installed inside the vehicle. In this study, a novel approach to power transfer is presented, HIWPT. To assess its efficacy, it is cross-validated with an existing technique, CPTS, which stands for Conventional Power Transfer System. Regarding moderately high transfer of power usage, such as charging electric vehicles, capacitive WPT of the resonance type is typically preferred because to its higher efficiency. While designing the WPT system's power supply stages, we took into account the following factors(i) the values and ratings of the capacitors that render the coil-coupling resonance;(ii) the ele

关键词： Energy transfer

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An Investigation of Explicit Indicators for Identifying Cyberstalking Incidents Towards Sexism using Keyword-Assisted Topic Model

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Journal of The Institution of Engineers (India): Series B 2024年 1-12页

作者： Muthusami, Rathinasamy Saritha, Kandhasamy Sarwe, deepak Umrao Megala, Arumugam dora Pravina, C.T. Department of Computer Applications Dr. Mahalingam College of Engineering and Technology Tamil Nadu Pollachi India Department of Mathematics P. A. College of Engineering and Technology Tamil Nadu Pollachi India Department of Mathematics University of Mumbai Maharashtra Mumbai India Department of Mathematics Nandha Engineering College Tamil Nadu Erode India Department of Mathematics Vel Tech Rangarajan Dr Sagunthala R & ampD Institute of Science and Technology Tamil Nadu Chennai India

This research explores the use of explicit indicators to identify cyberstalking incidents, a growing concern in the digital age. As the web and computer technology have grown, cyberstalking is now a major problem that affects an estimated 1.3 million people a year in the US alone. This research evaluates the comparative legitimacy of several predictors, such as those pertaining to an individual’s background, sociodemographic characteristics, risk, protective domains, and sexism, that are linked to allegations of cyberstalking and victimisation. The results draw attention to the distinctive elements that contribute to adult individuals from different nations engaging in cyberstalking regarding sexism. The outcomes of the investigation can help guide the improvement of initiatives to prevent and cope with cyberstalking, giving organisations and governments’ significant data to develop preventative plans and effectively deploy resources. In this research, keyword-assisted topic model (KATM), a machine learning-based system, has been developed to detect cyberstalking incidents. By combining keywords and attributes, KATM is able to identify potential instances of cyberstalking in online communication. The established automated topic coherence metrics, such as normalised pointwise mutual information (NPMI), UCI-coherence, and UMass-coherence across the SemEval-2023 Task 10 dataset, are used to evaluate the topics obtained from the established topic model KATM and a few other topic models as benchmark, including latent dirichlet allocation (ldA) and embedded topic model (ETM). The evaluation outcomes reveal that KATM consistently surpasses its counterparts in terms of topic coherence, excelling in all three metrics. © The Institution of Engineers (India) 2024.

关键词： Adversarial machine learning

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A lightweight Blockchain Scheme for Secure data Communication in Internet of Things-enabled Wireless Sensor Network

A Lightweight Blockchain Scheme for Secure Data Communicatio...

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2024 International Conference on Smart Systems for Applications in Electrical Sciences, ICSSES 2024

作者： Balraj, lavina Prasanth, A. devi Sowndarya, K.K. Kuntavai, T. Sri Venkateswara College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Sriperumbudur India Institute of Science and Technology Tamil Nadu Vel Tech Rangarajan Dr. Sagunthala R&D Department of Computer Science and Engineering India DMI College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Chennai India Adhipara Sakthi Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chengalpattu India

ISBN: (纸本)9798350364040

In today's world, there will probably be an enormous rise in the volume of data sensed by sensors on the Internet of Things-enabled Wireless Sensor Network (IWSN). The sensed data from sensor nodes is gathered and transmitted to the sink. These sensor nodes suffer from several consequences including security, transparency, trust, and immutability. Furthermore, other technical impairments like computation, storage of sensed data, privacy, and energy conservation enhance the issues of the IWSN. To overcome this, a novel Blockchain Interplanetary File Access Control System (BIFACS) has been proposed to manage intelligent autonomous access control for IWSN. Efficient data security and data transmission can be achieved in the proposed scheme by using the BIFACS algorithms. Further, the proposed scenario is implemented in the Solidity programming language and deployed on the local Ethereum. The efficacy of the proposed system has been analyzed based on computing, storage, and network performance. © 2024 IEEE.

关键词： Smart contract

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IoT and Cloud Solutions Waste-to-Energy in Hospitals for Energy Recovery from Medical Waste 10

IoT and Cloud Solutions Waste-to-Energy in Hospitals for Ene...

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10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Thanigaivelu, P.S. lakshmi, d. Ramasamy, Jayabharathi Kumaresh, P.S. Sumathi, G. Mathivanan, K. Srm Institute of Science and Technology Computing Technologies Chenagalpattu Chennai Tamil Nadu Kattankulathur India St. Joseph's College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Chennai India Rmk College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India K.L.N.College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Sivagangai India Kongunadu College of Engineering and Technology Department of Information Technology Tamil Nadu Trichy India Adhiparasakthi Engineering College Department of Electronics and Communication Engineering Tamil Nadu Melmaruvathur India

ISBN: (纸本)9798350353068

Innovative approach to hospital waste management and energy recovery due to the Internet of Things (IoT)-powered waste-to-energy system. This system addresses the complex problems of medical waste management and renewable energy production with a single framework. The system integrates several advanced sensors and components made possible by IoT technology's power to optimize waste management and energy generation. Sensors connected to the IoT, intelligent waste containers, and radio frequency identification labels all contribute to an improved garbage collection, sorting, and processing system. While fill-level sensors and RFId technology improve garbage collection routes and save operating costs and environmental effects, real-time data collection and analysis provide exact waste monitoring. Temperature and gas sensors enable safe and effective waste processing, eliminating risks and maximizing energy recovery. Medical waste is converted into useful energy sources like syngas in the system's energy recovery phase using pyrolysis or gasification reactors. These renewable energy sources lessen the environmental impact of medical waste disposal in landfills while relieving pressure on conventional fossil fuel supplies. The environmental advantages are highlighted, with less landfill trash and reduced greenhouse gas emissions specifically highlighted. © 2024 IEEE.

关键词： Renewable energy

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Intelligent Chat Bots: An AI Based Chat Bot for Better Banking Applications

Intelligent Chat Bots: An AI Based Chat Bot for Better Banki...

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Kiran, Ajmeera Kumar, I. Jeya Vijayakarthik, P. Naik, S.K lokesh Vinod, T. MLR Institute of Technology Department of Computer Science and Engineering Hyderabad India Good Shepherd College of Engineering Department of CSE India R.L.Jalappa Institute of Technology Dept of Computer Science and Engineering Dodabalapur Bengaluru India

ISBN: (纸本)9798350348217

A text-based and audio-based chat and voice assistant for a banking application that is powered by artificial intelligence and does conversions that are designed to resemble human conversations. Chat and voice assistants have come a long way from their humble beginnings, with advances in machine learning and natural language processing enabling them to learn from their interactions and hold conversations in a human-like manner. Becoming more human can help with calculating loan interests and checking transaction details and savings, among other things. Chat and voice assistants have come a long way from their humble beginnings. Conversational banking is an improved method for retaining loyal customers because it enables the bank to respond more quickly to the customers' inquiries. The Stone Age was followed by the Bronze Age, and now we are in the digital Age thanks to the advancement of technology. When it comes to customer behaviour, the transition from being a service seeker to a game-changer is happening at a very rapid rate. Those days are long gone when a company could still get away with putting the requirements of their customers lower on their priority list. Since the customer is now the person who ultimately decides whether a company will succeed or fail, it has become the top goal of any company to make certain that the needs and desires of the customer are met to the greatest possible extent. © 2023 IEEE.

关键词： Semantics

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Exploring the Experimental Possibilities of AI based Real- Time Virtual Reality Assisted Touchless Home Appliance Control 1

Exploring the Experimental Possibilities of AI based Real- T...

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1st International Conference on Innovative Sustainable Technologies for Energy, Mechatronics and Smart Systems, ISTEMS 2024

作者： Kumar, C. Ashok Gnanasekar, A. Ramya, R. Narmatha, S.U. Arunadevi, R. Ravi, C.N. Engineering Mlr Institute of Technology Department of Electronics and Communication Hyderabad India R.M.D. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Nano Electronics Materials and Sensors Tamil Nadu Chennai India R.M.K. College of Engineering and Technology Department of Physics Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Information Technology Tamil Nadu Chennai India Cmr Engineering College Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350384246

The design and execution of home automation systems have been greatly enhanced by recent technological breakthroughs, which have increased the capabilities and usefulness of embedded systems. There is a significant demand for smart home automation systems that include Virtual Reality (VR). One possible use of the proposed technology is to let the owner operate their home appliances through virtual reality. Using this is a breeze. In this work, we offer a modular, practical, and secure automation control structure for smart homes that is tied to virtual reality and has a cheap price tag. In this study, we take a simple look at how virtual reality may be used to regulate voltage for common home equipment including lights, fans, air conditioners, motor controls, and more. An AI-based Virtual Appliance Control System (AIVACS) is the name given to the proposed system because of its foundation in AI logic. In order to determine how effective the proposed model is, it is cross-validated using a standard Home Appliance Control System (HACS). The hardware has been assembled and tested in a scaled-down prototype with three options for controlling it: illumination, motors, and a fan in a domestic setting. The primary rationale for this research is the significant practical benefit that this VR-based hands-free operation would provide to physically impaired and elderly individuals, who wouldn't be required to physically go to the location of the switch. © 2024 IEEE.

关键词： domestic appliances

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A Comprehensive Evaluation of Fake Face Recognition Scheme using Artificial Intelligence Oriented learning Scheme 1

A Comprehensive Evaluation of Fake Face Recognition Scheme u...

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1st International Conference on Pioneering developments in computer Science and digital Technologies, IC2SdT 2024

作者： Subashree, S. Rose S, Remya Valarmathy, A.S. Joseph, Princy dennis, P. Jasmin Ravi, S. E.G.S. Pillay Engineering College Department of Computer Science and Engineering Tamil Nadu Nagapattinam India R.M.D. Engineering College Department of Artificial Intelligence and Machine Learning Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India CMR College of Engineering and Technology Department of Computer Science and Engineering Hyderabad India Vi Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chengalpattu India Saveetha University Department of VLSI Microelectronics Tamil Nadu Chennai India

ISBN: (纸本)9798350365016

Fake face recognition has emerged as a critical area of research due to the proliferation of synthetic media and its potential misuse in various domains. This study presents a thorough evaluation of a novel Fake Face Recognition Scheme utilizing Artificial Intelligence Oriented learning Scheme (AIOlS) coupled with Generative Adversarial Network (GAN)-GoogleNet integration. The aim is to discern authentic facial images from synthetic or tampered ones with high accuracy. In this research, we employed a dataset comprising a diverse range of authentic and synthetic facial images. The proposed scheme incorporates the power of GANs for generating synthetic facial images and leverages GoogleNet, a state-of-the-art deep convolutional neural network, for discriminative feature extraction. The integration within the AIOlS framework facilitates efficient learning and adaptation to complex patterns present in fake facial images. The evaluation of our scheme was conducted through rigorous experimentation on the dataset, employing various performance metrics. Notably, the accuracy obtained was measured at an impressive 96.7%, signifying the effectiveness of our approach in distinguishing between real and fake facial images. Additionally, other metrics such as precision, recall, and F1-score were also computed to provide a comprehensive assessment of the scheme's performance. © 2024 IEEE.

关键词： Generative adversarial networks

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