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检索条件"机构=M.Tech Computer Science and Engineering"

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Tracking and monitoring the safety of the child in the stroller

Tracking and monitoring the safety of the child in the strol...

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International Conference on Power, Energy, Control and Transmission Systems (ICPECTS)

作者： Pandiaraja P Rajesh Kanna P Sumathi K Karthik K muthumanickam K S. Radha 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 Bannari Amman Institute of Technology Erode Tamilnadu India Department of Computer Science and Engineering Builders Engineering College Kangeyam Tamilnadu India Department of Computer Science and Engineering M.Kumarasamy College of Engineering Karur Tamilnadu India Department of Information Technology Kongunadu College of Engineering and Technology Tiruchirappalli Tamilnadu India Department of Information Technology Vivekanandha College of Engineering for Women (Autonomous) TamilNadu India

ISBN: (数字)9798331508845

ISBN: (纸本)9798331508852

The safety of the child in the stroller is at risk when there is a deviation in the parent’s focus. The automatic movement in the baby strollers have led to many accidents and have been fatal to the baby. To overcome this, a stroller integrated with the touch sensor in the handle and movement sensor in wheels using IoT is planned in the project. The touchsensor is implemented using Capacitive or resistive sensing technology and works when an individual gets in physical contact with it. If a wheel movement is detected without touch in the handle, the customized voice alarm present in the stroller will go off to alert the parent. In addition to this, to locate the stroller through a device like mobile or tablet, a Global Positioning System (GPS) tracker will be placed in the stroller. When the stroller is left for about certain meters from the connected device, the parent will be notified through the connected device and can monitor the location of stroller in the device all the time using Blynk application.

关键词： Pediatrics Tracking Surveillance Roads Wheels Tactile sensors Safety Sensors Global Positioning System Accidents

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Design of Intelligent Home Security Handling System based on Face Recognition and IoT Assisted technology

Design of Intelligent Home Security Handling System based on...

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2023 IEEE International Conference on Research methodologies in Knowledge management, Artificial Intelligence and Telecommunication engineering, RmKmATE 2023

作者： Nirmala, P. Lakshmi, S. megala, J. Devi, P. Kalpana Venkatramanan, C.B. Bronson, F. Antony Xavier Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATS Chennai India Department of CSE St Joseph's College of Engineering Chennai India Department of EEE S.A. Engineering College Chennai India Vel Tech Rangarajan Dr.Sagunthala R & D Institute of Science and Technology Chennai India Department of EEE Sona College of Technology Salem India Department of Computer Science and Engineering Dr.M.G.R.Educational and Research Institute Chennai India

ISBN: (纸本)9798350305708

Security concerns pose significant challenges for residential homes, offices, and institutions, necessitating the deployment of trained personnel to ensure safety. However, human error remains a possibility, potentially compromising security measures. In response, the advancement of facial recognition systems has emerged, proving valuable for home door locking systems. These systems are user-friendly, accurate in identifying residents, and offer a convenient security solution. Facial recognition technology has evolved notably, with Convolutional Neural Networks (CNNs) playing a pivotal role. This method has proven effective in various applications, including object recognition. The study focuses on utilizing the AlexNet facial recognition system within a door locking system. The proposed model stands out with a remarkable sensitivity score of 96.745%, highlighting its exceptional precision in identifying positive cases. Notably, the system delivers accurate results for both authorized and unauthorized access attempts. This functionality addresses security concerns effectively. © 2023 IEEE.

关键词： AlexNet Convolutional Neural Network Face Recognition Internet of Things (IoT)

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3DSC2-UNet: Advancing Breast Cancer Segmentation techniques Using the 3D Skipped Convolution Capsule-UNet

3DSC2-UNet: Advancing Breast Cancer Segmentation Techniques ...

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Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT), International Conference on

作者： Parthasarathy Ramadass C. Sharmila Rakesh Kumar mahendran Hema V E. Kavitha R Sanmugasundaram Department of Computer Science & Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Information and Technology Dr. M.G.R. Educational and Research Institute Chennai India Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India Department of Computer Science and Engineering School of Computing Sathyabama Institute of Science and Technology Chennai Department of Physics Dr.M.G.R Educational and Research Institute Chennai Electronics and Communication Engineering Rajalakshmi Institute of Technology Chennai India

ISBN: (数字)9798331540685

ISBN: (纸本)9798331540692

Breast cancer (BC) persists as a substantial global health hurdle, demanding ongoing progress in the realms of detection, diagnosis, and therapeutic approaches. This thorough examination delves into cutting-edge technologies and methodologies that have surfaced in the quest for enhanced results in BC management. Yet, investigations employing solitary imaging modalities have showcased restricted clinical effectiveness owing to their relatively diminished diagnostic precision and dependability when compared to multimodal systems. As a result, our aim is to create a 3D Skipped Convolution Capsule UNet designed for the segmentation of breast tumors, employing both mammogram and ultrasound imaging modalities. For the integration of these modalities, we utilize the Dynamic Fusion Net (DF-Net), incorporating two modules named the molecular-Level Aligner module and Biphasic Sequential Integration module (BSInU). The process of segmentation takes place within our innovative framework, 3DSC2-UNet, encompassing four primary elements: (a) Graphical feature extraction, (b) Convolutional Capsule (ConvCaps) encoder module, (c) Synaptic skip connection, and (d) Convolutional decoder (Conv Decoder). The overall accuracy attained is 99.97%, accompanied by a Dice Similarity Coefficient (DSC) of 0.89 and an Average Surface Distance (ASD) of 2.5mm across the mammogram dataset. moreover, the precision stands at 99.65%, accompanied by a Dice Similarity Coefficient (DSC) of 0.88 and an Average Surface Distance (ASD) of 2.4mm across the ultrasound dataset. The suggested 3DSC2-UNet, harnessing both mammogram and ultrasound, showcases exceptional performance in accuracy, ASD, and DSC metrics. This model holds the capability to diminish unwarranted biopsy procedures, thereby advancing its prospects for clinical implementation.

关键词： Image segmentation Solid modeling Ultrasonic imaging Three-dimensional displays Accuracy Convolution Imaging

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Harnessing Tidal Energy: Design and Performance Evaluation of marine Energy Conversion Systems

Harnessing Tidal Energy: Design and Performance Evaluation o...

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2023 International Conference for technological engineering and its Applications in Sustainable Development, ICTEASD 2023

作者： Dhabliya, Dharmesh Varshney, Neeraj Sasikumar, m. Vijayaraghavan, P. Vimala, m. Sapaev, J.B. Almusawi, muntather Ushasree, Dupakuntla Vishwakarma Institute of Information Technology Information Technology Maharashtra Pune India GLA University Computer Engineering and Applications Mathura India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Computer Science and Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Mechanical Engineering Chennai India R.M.K. Engineering College Electrical and Electronics Engineering Tamil Nadu Kavaraipettai India National Research University Tashkent Uzbekistan Western Caspian University Baku Azerbaijan The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq GRIET Telangana Hyderabad India

ISBN: (纸本)9798350336474

Ocean wave energy, a sustainable energy source with significant growth prospects, has substantial storage capacity. Tidal energy technologies' application possibilities and practical significance for harnessing tidal energy resources are extensive. Researchers have developed several Wave Energy Converters (WECs) with diverse architectures and designs based on various principles. This study comprehensively analyzes tidal energy power production technology's basic framework and Power Take-Off (PTO) mechanism. This article introduces several types of WEC and multi-Degree Wave Energy Converters (mDWEC) and provides implementation examples. The analytical method creates an extensive multi-index model and assesses the current WEC based on five perspectives: energy capture, technological cost, economics, dependability, environmental friendliness, and adaptability. The results indicate that the mDWEC exhibits outstanding overall efficiency and has various applications in tidal energy consumption and development. Applying subjective and quantitative approaches determines the ideal technical strategy for WEC. This is achieved by reviewing and analyzing the technological principles of tidal energy power production and the implementation of devices. These findings are utilized for the advancement of WEC. © 2023 IEEE.

关键词： Energy utilization

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Exploring the Synergy between Blockchain technology and Cryptocurrencies: Implications for Financial Innovation and Security

Exploring the Synergy between Blockchain Technology and Cryp...

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Global Conference for Advancement in technology (GCAT)

作者： S. Banumathi K Saravanan R. Nadanasabai Radhamani Vijayakumar Sumalatha A B. Shamreen Ahamed Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Information Technology R.M.K Engineering College Kavaraipettai Tamil Nadu India Department of MBA St. Josephs College of Engineering Chennai Department of ECE Rajalakshmi Engineering College Thandalam Chennai Department of Computer Science Kristu Jayanti College Autonomous Bengaluru Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Jeppiaar Nagar Chennai

ISBN: (数字)9798350376685

ISBN: (纸本)9798350376692

A new age has begun in the financial sector with the arrival of blockchain technology, and cryptocurrencies have emerged as a paradigm-shifting invention. This study investigates the potential for financial innovation and safety by exploring the interplay between blockchain and cryptocurrency. The study demonstrates how decentralization, transparency, and immutability—the three pillars of blockchain—allow for the development of safe and effective cryptocurrency systems. Cryptocurrencies have the ability to revolutionize the financial industry by providing better privacy, lower transaction costs, and cross-border transactions, among other benefits. Additional topics covered include legislative barriers, market volatility, and security issues that are linked to cryptocurrency. Smart contracts, decentralized finance (DeFi), and asset tokenization are just a few examples of how this study uses a literature review, case studies, and empirical analysis to pinpoint important areas where blockchain and cryptocurrencies may work together to propel financial innovation. The study highlights the significance of a well-rounded regulatory system that encourages innovation while reducing potential dangers. New investment opportunities, payment systems, and financial inclusion opportunities may arise as a result of the combination of blockchain technology and cryptocurrencies, according to the results. To overcome obstacles and capitalize on this revolutionary synergy, however, business stakeholders, regulators, and lawmakers must work together to realize this promise.

关键词： technological innovation Privacy Smart contracts Finance Decentralized applications Tokenization Cryptocurrency Blockchains Security Internet of Things

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Revolutioning IIot: A Smart Appliance of an Internet of Things over Industrial manufacturing Unit to make Error-Free Circumstances

Revolutioning IIot: A Smart Appliance of an Internet of Thin...

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2024 International Conference on Cybernation and Computation, CYBERCOm 2024

作者： Ravi, Kiran Chand Vaishnavi, T. Princy, Anni Kandaswamy, Vijay Anand Dinesh, m. Lakshmisridevi, S. MLR Institute of Technology Department of ECE Hyderabad India Vel Tech Rangarajan Dr. Sagunthala RandD Institute of Science and Technology Department of ECE Tamil Nadu Chennai India Panimalar Engineering College Department of Artificial Intelligence and Machine Learning Tamil Nadu Chennai India R.M.K. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha University Department of VLSI Microelectronics Tamil Nadu Chennai India Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331542344

A future where cyberspace and the real world are inseparable is the goal of the Internet of Things (IoT). The potential for the development of robust industrial services and applications, colloquially known as the Industrial Internet of Things (IIoT), is enormous. From the acquisition of raw materials to the provision of customer service and support, the Internet of Things (IoT) was utilized across numerous sectors by industries. The Internet of Things (IoT) offers a great opportunity to develop significant manufacturing-related services and applications, and it is widely regarded as a crucial technology of the industrial revolution. In addition, it facilitates communication between intelligent devices, allowing them to exchange information and data-crucial for complex systems to make decisions in the here-And-now. In this paper, a new method called Error-Free Smart Industrial Control System (EFSICS) is introduced to improve the efficiency of industrial operations through the use of IIoT. To test how well this method works, it is cross-validated with the traditional model called Classical Industrial Control System (CICS). Regarding the manufacturing aspects in particular, the suggested method is well-suited to the effects of the Internet of Things on sustainable development. Researchers are now at the forefront of cyber integrated manufacturing research, which will further illuminate the present state of the internet of things (IoT) in manufacturing. © 2024 IEEE.

关键词： Smart manufacturing

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Cloud-based fault prediction using IoT in office automation for improvisation of the health of employees

Cloud-based fault prediction using IoT in office automation ...

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Advance Computing and Innovative technologies in engineering (ICACITE), International Conference on

作者： Nakul Shahdadpuri Somanchi Hari Krishna SathiJyothirmaye Reddy C. Ganesh Kirti Agarwal Sourabh Bhattacharya IPG Programme {(B.Tech + M.Tech (It)} IIITM Gwalior Department of Business Management Vignana Bharathi Institute of Technology Malkajigiri Telangana Department of Management Marwadi University Rajkot Gujarat Computer and Communication Engineering Sri Eshwar College of Engineering Anna University Chennai ITERC College Delhi (NCR) India Department of Management and Social Science Haldia Institute of Technology West Bengal

modern technology is the best thing to be used in every commercial sector. The devices are well equipped to understand the problems of the users. The offices are now been maintained by technology the devices for daily monitoring even the electrical appliances are been monitored and maintained by technology. In previous times the best method of this work is to make it via cloud computing, but now as technology has evolved and evolved new adding devices are making system malfunction. The fault of cloud computing needs to be identified, So the best method is to automate the office with the introduction of IoT. it is a platform equipped with all the facilities for monitoring and maintaining the devices inside the office, even the working capacity of employees is also measured via this method. The study is showing the effectiveness of the IoT to identify the faults of cloud computing related to maintaining the working method of the office. The data collected for this study is secondary data like articles, books, journals and many more. Then gathered data is analyzed by qualitative data analysis. The results are quite positive about the use of it to automate the office and its working procedure.

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ANALYSIS OF CONCRETE CRACKS AND FATIGUE IN SmART CITIES USING YOLOV3

ANALYSIS OF CONCRETE CRACKS AND FATIGUE IN SMART CITIES USIN...

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2023 IEEE International Conference on Research methodologies in Knowledge management, Artificial Intelligence and Telecommunication engineering, RmKmATE 2023

作者： Archana, U. Sharma, Sarvdaman Singh, Sitesh Kumar Sureshkumar, R. Senthilkumar, P. Harish Babu, T. Department of Computer Science and Design R.M.K. Engineering College Chennai India Department of Civil Engineering University Institute of Engineering and Technology University of Jammu Jammu & Kashmir India Department of Civil Engineering Wollega University Oromia Nekemte Ethiopia Department of Electronics and Communication Engineering Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai India KL School of Architecture Koneru Lakshmaiah Education Foundation Greenfield Vaddeswaram Andhra Pradesh Guntur India Department of Electrical and Electronics Engineering Sethu Institute of Technology Tamilnadu India

ISBN: (纸本)9798350305708

This study focuses on the application of the YOLOv3 (You Only Look Once version 3) object detection algorithm for the analysis of concrete cracks and fatigue within Smart Cities. Concrete infrastructure plays a crucial role in urban environments, and its structural integrity is paramount for ensuring public safety and sustainable development. The proposed approach utilizes YOLOv3 to identify and localize instances of concrete cracks and signs of fatigue in images and videos captured from various urban settings. By leveraging deep learning techniques, this research aims to enhance the efficiency and accuracy of monitoring and maintaining concrete structures, contributing to the overall resilience and longevity of Smart Cities. The findings of this study present valuable insights into the potential of utilizing advanced computer vision methods for proactive infrastructure management in the urban landscape. © 2023 IEEE.

关键词： Concrete cracks Fatigue analysis Infrastructure monitoring Smart Cities YOLOv3

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mCHeRA: An Efficient multi Cloud Heuristic Resource Allocation using Grey Wolf Optimization

MCHeRA: An Efficient Multi Cloud Heuristic Resource Allocati...

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Data Intelligence and Cognitive Informatics (ICDICI), International Conference on

作者： P. Gandhimathi S. Kiruthiga BIndu K V Shanthi H J V. Velmurugan Sangeethaa SN Physics SRM Madurai College for Engineering and Technology Department of Computer Science &Engineering School of Computing Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India S&H(General Engineering) R.M.K College Of Engineering and Technology Puduvoyal Computer Applications Hindustan Institute of Technology and Science Deemed to be University Padur Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr Sagunlatha R&D Institute of Science and Technology Avadi Chennai India Computer Science & Engineering Bannari Amman Institute of Technology

ISBN: (数字)9798350389609

ISBN: (纸本)9798350389616

Cloud computing is a cutting-edge technology that has gained immense popularity in the present era. The burgeoning demand for services has necessitated the development of a framework for efficiently allocating resources to incoming requests. This approach not only enhances the network's efficiency but also reduces costs significantly. The convergence of cloud and edge computing has emerged as a burgeoning field of study in the computing industry over the past few years. The exponential rise in the number of customers and requests for cloud data centers (CDCs) has highlighted the critical need for robust servers and energy-efficient mechanisms. As CDCs expand to meet growing demands, they face significant challenges related to energy consumption, environmental impact, and operational costs. Employing suitable algorithms for resource allocation in CDCs is crucial in order to minimize energy consumption. The objective of this research endeavor was to devise an ingenious approach for dynamically allocating resources in cloud networks by leveraging the power of the Gray Wolf Optimization algorithm. The proposed work performs multi-Cloud Heuristic Resource Allocation (mCHeRA) using Grey Wolf Optimization (GWO) algorithm and produces 61% of computational resource utilization, 79% of CPU utilization, 64% memory utilization, 74% bandwidth utilization. The algorithm that has been put forth is meticulously assessed and contrasted with its counterparts. The outcome of the simulation manifests the remarkable efficacy of the novel mCHeRA in comparison to alternative algorithms.

关键词： Industries Cloud computing Energy consumption Costs Heuristic algorithms Bandwidth Organizations Resource management Servers Optimization

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Secure and Responsive Human-Robot Interaction for Dementia Patients Using LSTm and IoT 3

Secure and Responsive Human-Robot Interaction for Dementia P...

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3rd International Conference for Advancement in technology, ICONAT 2024

作者： Ramya, S. Radhika, m. Roychoudri, Subramani Senthil, S. Arunachalam, G. muthulekshmi, m. Paavai Engineering College Department of Cyber Security Tamil Nadu Namakkal India R.M.D. Engineering College Department of Information Technology Tamil Nadu Chennai India Usha Rama College of Engineering and Technology Department of Computer Science and Engineering Andhra Pradesh Vijayawada India Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Avadi Department of Mathematics Tamil Nadu Chennai India Department of Electronics and Communication Engineering Tamil Nadu Namakkal India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350354171

An innovative architecture that combines Long Short-Term memory (LSTm) networks with Internet of Things (IoT) technology is presented in this paper to assist dementia patients. It solves Human-Robot Interaction (HRI) difficulties in dementia care. It also ensures security and responsiveness in HRI to establish a secure and trustworthy environment for dementia patients. LSTm networks help the robot to recognize and to adapt based on the dementia patients' behaviors. Through real-time data gathering and exchange, IoT devices offer seamless and context-aware interactions. The system protects user privacy and sensitive data with strong encryption and authentication processes. The framework uses adaptive learning methods to improve the robot's comprehension of the user's preferences and needs, offering a personalized and responsive assistance system. Simulations and real-world situations show that the proposed technology provides safe, responsive, and personalized human-robot interactions for dementia care. By presenting a potential solution to dementia care difficulties it advances assistive technology and improves quality of life for dementia patients. © 2024 IEEE.

关键词： Human robot interaction

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