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Advancement in Technology (ICONAT), International Conference for

作者： N sujatha s Pramod s Aravindh balagopala Ramesh babu s. Rukmani Devi M. Ananthi Department of Mathematics B. M. S. College of Engineering Bengaluru Karnataka India Department of Mathematics Nitte Meenakshi Institute of Technology Yelahanka Bangalore Karnataka India Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India Department of Computer Science and Engineering SRKR Engineering College Bhimavaram Andhra Pradesh India Department of Computer Science Saveetha College of Liberal Arts and Sciences SIMATS Deemed to be University Chennai Tamilnadu India Department of Computer Science and Business Systems KGiSL Institute of Technology Coimbatore Tamilnadu India

ISBN: (数字)9798350354171

ISBN: (纸本)9798350354188

It is common practice in many industries to use cash since it accounts for more than 85% of payments in almost all developing countries. A cell phone is become an everyday item. Mobile phones have practically become people’s constant companions due to the plethora of other uses they offer beyond just communicating. since they are both cheap and multipurpose, soon everyone will be utilizing them. In an ideal world, everyone would use their cell phone for everything. verification, preprocessing, and training the model are the three parts that make up the method. In order to confirm the payment, the customer’s biometric template is checked during the verification procedure. The three stages of fingerprint preparation include matching fingerprint templates, extracting fingerprint minutiae, and fingerprint preprocessing. The training of the model was carried out using a Hybrid LsTM-Ensemble Learning. The average accuracy of the suggested method is 92.76%, which is higher than LsTM and Ensemble Learning.

关键词： Training Accuracy Cellular phones biological system modeling Fingerprint recognition vectors Mobile handsets security Ensemble learning Long short term memory

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An android based smart robotic vehicle for border security surveillance system 4

An android based smart robotic vehicle for border security s...

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4th International Conference on Computational Intelligence and Communication Technologies, CCICT 2021

作者： Pawar, Krunal b. Dharwadkar, Nagaraj v. Deshpande, Pradeep A. Honawad, shivakumar K. Dharmadhikari, Pramod A. Rajarambapu Institute of Technology Department of Computer Science and Engineering Rajaramnagar Maharastra Sangli India BLDEA's V.P.Dr.P.G.Halakatti College of Engineering and Technology Department of Information Science and Engineering Karnataka Vijayapura India

ISBN: (纸本)9781665423922

Monitoring wide borders of the nation for 24/7 has become the vital role in field of national defense and security system against Terrorism. Knowingly or unknowingly Trespassers crosses borders illegally for smuggling, illegal weapons and goods transport, undocumented migration etc. In the present situation, the border monitoring process is being taking place manually by nations border security forces (bsF) these people are responsible for constantly monitoring nations borders. It requires more number of Human Resources and specific assets as the borders are spread across thousands of miles and have vast geographical area also has different climate conditions. With help of advanced technology, Practice of patrolling on the borders can be automated by using PIR sensors to detect the Trespasser, Raspberry pi camera to continuously surveillance, Android based controlling system for Robotic vehicle movement and wireless networking technology for sending information to the control room for further action. In this technical paper we are proposing An Android based smart Robotic vehicle for border security surveillance system. © 2021 IEEE.

关键词： Cameras

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An Enhanced support vector Machine based Pattern Classification Method for Text Classification in English Texts

An Enhanced Support Vector Machine Based Pattern Classificat...

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International Conference on Computation system and Information Technology for sustainable solutions (CsITss)

作者： venkata Nagaraju Thatha b. veerasekharReddy G. venuGopal K. Ashok sundarababu Maddu srilakshmi. v Department of Information Technology MLR Institute of Technology Hyderabad India Department of Computer Science and Engineering KL Education Foundation Vaddeswaram India Department of Computer Science and Engineering (cyber Security) Vignana Bharathi Institute of Technology Hyderabad India Department of Computer Science and Engineering St. Joseph's Institute of Technology Chennai India Department of Computer Science and Engineering (AI & ML) B V Raju Institute of Technology Narsapur Medak India

Text mining is a growing in a unique field that attempts to convey information from natural language text. It is too strength be uncertainty characterized as the development of analysing text as well as to take out the information that is constructive for particular purposes. Compared with other kind of data stored in databases, text is unstructured, shapeless as well as difficult to deal with algorithmically. Traditionally the patterns of the text are analyzed by using PTM and FTM algorithms but this algorithms produces less accuracy. To improve the performance of pattern classification, in this paper an Enhanced support vector Machine based Pattern classification method(EsvMPCM) is proposed. Then EsvMPCM is applied to Reuters dataset and measure the performance using different metrics as precision, recall, F-measure and accuracy.

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A Novel Advanced Algorithm in Automation of Food and Health Monitoring system using IOT 8

A Novel Advanced Algorithm in Automation of Food and Health ...

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8th IEEE International Conference for Convergence in Technology, I2CT 2023

作者： sampath Kumar, Pattem. vijayasree, J. saikumar, K. Ayad Alkhafaji, Mohammed Obaid, Ahmed J. Ali Zearah, sajad Malla Reddy Institute of Engineering & Technology Hyderabad India Department of Electronic and Communication India Koneru Lakshmaiah Education Foundation Hyderabad Dept of ECE R.V.S Nagar Moinabad-Chilkur Rd near AP Police Academy Telangana Aziznagar India National University of Science and Technology College of Engineering Technology Department of Medical Device Industry Engineering Dhi Qar Iraq University of Kufa Faculty of Computer Science and Mathematics Iraq Al-ayen University Scientific Research Center Thi-Qar Iraq

ISBN: (纸本)9798350334012

Food is one of the essential factors in human growth and development. The recent results of the internet of things and robots have already shown the beginnings of a new food monitorization. Automation in the restaurants and food sector did not originate technically, so humanoid-related IoT platforms are necessary. In this research, an advanced monitoring algorithm for the automation of food & health system performs using the (IoT). The suggested system develop using food quality sensing devices. Each detector was equipped with the above qualities and connected using breadboards and relay boards. There is tremendous fear and motivation in the thought that there may not be enough food to go around as the human population expands exponentially. To construct a monitoring system that can identify the presence of people, gases, and temperature differences, we employed website creation in combination with the (IoT). The designed application has attained a sensitivity of 97.53%, an accuracy of 98.83%, a recall of 97.98%, and a detection rate of 98.91%. The implemented technology is beneficial to researchers and society. The proposed IoT-based automation of food & health monitoring system compete with present technology and outperforms the methodology. © 2023 IEEE.

关键词： Internet of things

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Quantum-Driven Hybrid Network Architecture Leveraging 5G for High-speed and Resilient Data Transmission

Quantum-Driven Hybrid Network Architecture Leveraging 5G for...

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Mobile Computing and sustainable Informatics (ICMCsI), International Conference on

作者： Kusuma Ashok Kumar R. Mohandas sajja suneel M.R. Mahalakshmi Avinash Kumar Manmohan singh Department of Physics B V Raju Institute of Technology Telangana state India Electronics and Communication Engineering Chennai Institute of Technology Chennai Department of CSE (Data Science) Institute of Aeronautical Engineering Hyderabad Telangana India Department of ECE Sri Muthukumaran Institute of Technology Chennai Tamil Nadu Department of Computer Science and Engineering IES College of Technology Bhopal

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

The integration of quantum communication principles with 5G technology presents a groundbreaking approach to addressing the growing demand for high-speed, secure, and resilient communication systems. This paper proposes a Quantum-Driven Hybrid Network Architecture that leverages Quantum Key Distribution (QKD) for unparalleled security and combines it with 5G's ultra-fast data transmission capabilities. The architecture integrates key components such as QKD modules, 5G infrastructure, and edge computing, organized into a layered framework comprising quantum, network control, and application layers. simulation results demonstrate significant improvements in throughput (up to 23.5%), latency reduction (up to 25%), and error rate reduction in high-noise environments (from 0.25% to 0.05%). The proposed system also exhibits enhanced security, achieving a 100% success rate in mitigating eavesdropping and man-in-the-middle attacks. Using resource-efficient mechanisms, the hybrid network achieves an overall accuracy of 97.8% in secure and resilient data transmission. This work validates the potential of quantum-enhanced 5G systems to meet the challenges of future communication networks.

关键词： 5G mobile communication scalability computer architecture Network architecture Throughput Quantum key distribution Data communication Resource management Quantum networks Edge computing

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Machine Learning-driven Quality Control strategies for Industrial IoT Applications

Machine Learning-driven Quality Control Strategies for Indus...

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Innovation in Technology (AsIANCON), Asian Conference on

作者： Dankan Gowda v Muhammad Aashir Irshad P. Arockia Mary Y Durga Prasad KDv Prasad Hariprasad Tarigonda Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka Northumbria University London Department of Information Technology V.S.B. Engineering College Karur Tamilnadu India Department of Computer Science & Engineering Aditya College of Engineering and Technology Surampalem Andhra Pradesh India Symbiosis Institute of Business Management Hyderabad Symbiosis International (Deemed University) Pune India Department of Mechanical Engineering School of Engineering Mohan Babu University Tirupati Andhra Pradesh India

ISBN: (数字)9798350354218

ISBN: (纸本)9798350354225

This paper introduces a new solution for improving Quality of Control in Industrial Internet of Things (IIoT) systems by using a machine learning approach. The planned system utilizes monitoring data originating from different sensors installed in the production line to detect faults as well as estimate maintenance requirements. besides, the proposed system uses the state-of-art machine learning techniques like Convolutional Neural Networks for defect detection and Recurrent Neural Networks for Predictive maintenance with high accuracy and efficiency. computer simulations indicate a high increase in the coverage of defects, predictive capability, and overall product quality. The combination of IoT and machine learning presents a convenient and evolutionary solution that becomes progressively enhanced as more data becomes available, and give a solid framework for the sustained optimization of standards in industrial practices. Future work seeks to enhance the developed models and extend the implemented system’s functionalities to other application domains and bigger data sets.

关键词： Machine learning Quality control Production Predictive models sensor systems Data models Automobiles Industrial Internet of Things Predictive maintenance Defect detection

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Resource Allocation strategies for 6G Wireless Communications: Comparing Existing and Novel Algorithms

Resource Allocation Strategies for 6G Wireless Communication...

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Recent Innovation in smart and sustainable Technology (ICRIssT), International Conference on

作者： J. Logeshwaran vikrant sharma R. Arshath Raja Rishi Prakash shukla Divya Kumar Manika Manwal Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Coimbatore Tamil Nadu India Computer Science and Engineering Graphic Era Hill University Dehradun India Department of Electronics and Communication Engineering B.S.Abdur Rahman Crescent Institute of Science & Technology Chennai India AIT Management Chandigarh University Mohali Punjab India Chandigarh University Mohali India Computer Science and Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

ISBN: (数字)9798350309140

ISBN: (纸本)9798350309157

This paper provides a complete evaluation of useful resource allocation techniques for 6G Wi-Fi communique networks in comparison to existing and novel algorithms. special current algorithms together with maximum Clique, grasping seek, harmony seek and Particle swarm Optimization are discussed in detail and compared with the novel algorithms of Discrete Cuckoo seek, QuantumInspired Evolutionary algorithm, and synthetic Immune machine. each of those algorithms is explained in phrases of its benefits, risks, and programs with real-global examples. moreover, the paper studies the suitability of each of those algorithms for aid allocation in 6G networks. They have looked at highlighted the capacity of these novel algorithms to improve the overall performance of resource allocation techniques and enhance the pleasant of service (Qos) of 6G wi-fi networks. The paper additionally examines the demanding situations in implementing these algorithms in 6G networks and indicates capability answers. The paper gives perception into the software of those algorithms for aid allocation in 6G networks, in addition to potential destiny studies instructions for improvement.

关键词： 6G mobile communication Wireless communication Technological innovation Protocols scalability software algorithms Quality of service software Resource management Wireless fidelity

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IoT Edge and Fog Computing Architecture for Educational systems in Universities

IoT Edge and Fog Computing Architecture for Educational Syst...

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2022 IEEE International Conference on Current Development in engineering and Technology, CCET 2022

作者： siddiqui, shams Tabrez Ahmad, Md Oqail siddiqui, Alighazi Khan, Haneef Khan, Mohammad Rafeek Alsabhan, Ashjan Hamad College of Cs & It Jazan University Department of Computer Science Jazan Saudi Arabia B.S Abdur Rahman Crescent Institute of Science and Technology Department of Computer Applications Tamilnadu Chennai600048 India College of Cs & It Jazan University Department of Computer and Network Engineering Jazan Saudi Arabia Applied College University of Hafr Al Batin Cst Department Hafar al-Batin Saudi Arabia

ISBN: (纸本)9781665454155

smart lights, ovens, and industrial data-gathering equipment are all instances of internet-connected gadgets. With 41.6 billion IoT devices being used, 79.4 Zb of data will be generated by 2025, according to research firm IDC. The earliest IoT gadgets sent information to the cloud for analysis. When sending many billions of gigabytes to the cloud, the data pipeline clogs up. With computing at the edge, IoT gadgets can analyze data without transferring it to a remote server. Data is handled locally, at the 'edge' of your network, rather than being transmitted elsewhere. Technology's malleability makes it a valuable tool in the field of education. The specifications for edge computing in IoT networks vary from those of other networks. At the edge, well-suited setting to handle the massive volumes of devices and data generated by the Internet of Things. several tasks can be moved to the device's edge, which can help keep costs down. The importance of IoT edge computing architecture in education has grown as a result of its deployment in real-time applications. The research simplifies the process of analyzing the structural layout of educational systems by proposing a framework for Internet of Things (IoT) Edge computing in the field of education. There will be a focus on concerns and issues with the IoT that will be brought out by the framework. In this research, potential and pitfalls of using IoT edge computing in education institutions is explored. In addition to this, the research article analyzes the effectiveness of edge computing for Internet of Things applications in an educational environment. © 2022 IEEE.

关键词： Internet of things

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FLes: A Federated Learning-Enhanced semantic Communication Framework for Mobile AIGC-Driven Human Digital Twins

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IEEE Network 2025年

作者： Okegbile, samuel D. Gao, Haoran Talabi, Oluwasegun Cai, Jun Yi, Changyan Niyato, Dusit shen, Xuemin University of the Fraser Valley School of Computing AbbotsfordBCV2S 7M8 Canada Concordia University Department of Electrical and Computer Engineering MontrealQCH3G 1M8 Canada Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Jiangsu Nanjing211106 China Nanyang Technological University College of Computing and Data Science Singapore University of Waterloo Department of Electrical and Computer Engineering Canada

Innovative mobile artificial intelligence-generated content (AIGC) can support the evolution and updating processes of virtual twins (vTs) in human digital twin (HDT) systems. With a reliable and efficient automatic data generation process, the requirement for a timely physical-to-virtual synchronization in HDT can be satisfied. While such an AIGC-enabled HDT system can facilitate modelling high fidelity vTs, generating content that represents the true states in the physical environment and providing timely customized services, it may suffer from a poor understanding of contexts, a lack of creativity, and various security and privacy concerns. In this paper, we propose a novel framework, which integrates federated learning (FL) and semantic communication (semCom) to enhance performance in the AIGC-enabled HDT system while improving accuracy and convergence properties. First, we present a holistic architectural framework for the proposed FL-enhanced semCom (FLes) solution for mobile AIGC-enabled HDT systems and discuss its design requirements and challenges. We later present key technologies necessary to realize the FLes solution, followed by elaborating on important technical issues to suggest future directions. Experimental results demonstrate that FLes not only facilitates reliable and personalized content generation but also shows better performance when compared to existing solutions. © 1986-2012 IEEE.

关键词： Federated learning

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FlashHack: Reflections on the Usage of a Micro Hackathon as an Assessment Tool in a Machine Learning Course

arXiv

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arXiv 2024年

作者： Indra, R. Parthasarathy, P.D. Ambasana, Jatin satavlekar, spruha Department of Information Science and Engineering B.M.S. College of Engineering Bengaluru India Department of Computer Science and Information Systems BITS Pilani KK Birla Goa Campus Goa India Centre for Educational Technology Indian Institute of Technology Bombay Mumbai India

Machine learning (ML) course for undergraduates face challenges in assessing student learning and providing practical exposure. Group project-based learning, an increasingly popular form of experiential learning in Cs education, encounters certain limitation in participation and non-participation from a few students. studies also suggest that students find longer programming assignments and project-based assessments distracting and struggle to maintain focus when they coincide with other courses. To tackle these issues, we introduced FlashHack: a monitored, incremental, in-classroom micro Hackathon that combines project-based learning with Hackathon elements. Engaging 229 third year Cs undergraduate students in teams of four, FlashHack prompted them to tackle predefined challenges using machine learning techniques within a set timeframe. Assessment criteria emphasized machine learning application, problem-solving, collaboration, and creativity. Our results indicate high student engagement and satisfaction, alongside simplified assessment processes for instructors. This experience report outlines the Hackathon design and implementation, highlights successes and areas for improvement making it feasible for replication by interested computing educators. © 2024, CC bY-NC-ND.

关键词： Adversarial machine learning

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