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Advancing conservation: Internet of Things-driven initiatives for marine animal rescue due to climate changes [Climate Change]

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IEEE Potentials 2024年第2期43卷 21-29页

作者： Gopi, rahul Sanmugam ramasamy, rajkumar Babu, M. david Honesty Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai600062 India

Beneath the expansive oceans lies a complex ecosystem where marine animals, from whales to delicate coral polyps, sustain the vitality of the marine environment. However, these creatures are facing significant challenges due to evolving climate changes. rising sea temperatures, ocean acidification, habitat degradation, and increasing natural disasters threaten their survival. © 1988-2012 IEEE.

关键词： Invertebrates

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design and analysis of Quad-Element MIMO Antenna for Bio-Medical Applications 3

Design and analysis of Quad-Element MIMO Antenna for Bio-Med...

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3rd International Conference on Electrical, Electronics, Information and Communication technologies, ICEEICT 2024

作者： Pappa, C. Kanmani rajesh Kumar, d. Kavitha, T. Murugan, C. Vel Tech Rangarajan Dr Sagnuthala R&d Institute of Science and Technology Department of Ece Chennai India

ISBN: (纸本)9798350369083

This article introduces an innovative four-port CPW MIMO antenna with a doughnut-shaped design tailored for dual-band usage. Covering frequencies ranging from 2.4 to 2.5 GHz and 4.4 to 5 GHz, boasting a notable 10 dB impedance bandwidth, the antenna is crafted on an Fr4 substrate measuring 55 mm x 55 mm x 1.6 mm. By strategically placing the antenna elements orthogonally to achieve isolation exceeding 20 dB, it significantly enhances various MIMO performance metrics including Envelope Correlation Coefficient (ECC), Total Active reflection Coefficient (TArC), Channel Capacity Loss (CCL), diversity Gain (dG), and Mean Effective Gain (MEG). Its versatility extends to diverse applications within Industrial, Scientific, and Medical (ISM) bands, as well as the emerging radio band 78 (n78) pertinent to biomedical and 5G applications. Furthermore, Specific Absorption rate (SAr) calculations confirm the antenna's effectiveness for biomedical purposes. © 2024 IEEE.

关键词： Medical applications

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design of Novel CPW fed High Isolation Quad-Port MIMO Antenna with dual-Band resonance 15

Design of Novel CPW fed High Isolation Quad-Port MIMO Antenn...

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

作者： Gowthami, ratikrinda Vivek, Ippili Sai Abhinay, ravula dileepan, d. Dept of ECE Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9798350370249

In this article, a Multiple Input Multiple Output (MIMO) can provide a stronger, more focused signal, improved signal quality, and increased data rates. However, designing MIMO antennas poses challenges such as narrower beam width, alignment issues, and high isolation. This proposed system is a dual-band microstrip patch antenna that has conductive material mounted on a dielectric substrate, such as Fr-4. The single element has a dimension of 32 × 22 mm2, and the MIMO structure is created by duplicating the single element with a compact size of 54 × 54 mm2. It is useful for various applications like wireless sensor networks, WLAN, Wi-Fi, and cellular networks. It can overcome these challenges as it provides two independent and dedicated networks, allowing more flexibility, bandwidth, and support for various wireless applications. The ports are aligned orthogonally, which increases isolation. ©2024 IEEE.

关键词： Microstrip antennas

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An Efficient Antenna Parameters Estimation Using Machine Learning Algorithms

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Progress In Electromagnetics research C 2023年 130卷 169-181页

作者： ramasamy, rajendran Bennet, Maria Anto Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai600062 India

A smart antenna synthesis approach is described as automatically choosing the optimum antenna type and providing the best geometric characteristics under the demands of antenna performance. different antenna performance characteristics are examined, and using decision tree classifier, the optimal antenna is suggested using an intelligent antenna selection model. Finally, the geometric characteristics of the antenna are given before the fuzzy inference system is developed by merging five primary learners to fully exploit the benefits of each type of learner. rectangular patch antenna, pyramidal horn antenna, and helical antenna are the three types of antennas that are classified by a decision tree classifier, and the optimal antenna size parameters are determined using a fuzzy inference method. The performance of decision tree classifier measured using accuracy and FIS is measured using Mean Square Error (MSE) and MAPE. The system demonstrates excellent capability in parameter prediction with antenna categorization with a MAPE of less than 5.8% and accuracy over 99% achieved in our proposed method. The recommended methodology might be widely applied in actual smart antenna design. © 2023, Electromagnetics Academy. All rights reserved.

关键词： Microstrip antennas

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Power efficient module in single chip for the energy optimized dynamic IoT communication

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Multimedia Tools and Applications 2025年第10期84卷 8107-8126页

作者： Gaikwad, Nitesh Shiyamala, S. Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R &D Institute of Science and Technology Tamil Nadu600062 India

The design of a power-efficient Internet of Things (IoT) dynamic communication system is the most required task for digital applications. However, allocating the optimal power based on the user requests is not an easy task. So, the current research article has planned to design a novel Firefly-based Power Estimation and Allocation (FbPEA) strategy for the communication microarchitecture. Here, the presented model is processed on the power chip of the microarchitecture module. Consequently, the data has been transmitted, and parameters were estimated in the LabView environment. Moreover, designing the microarchitecture of the LabView platform is new in the IoT communication fields. Compared to other tools, LabView has better power optimization and execution time results. Hence, using the LabView tool for the microarchitecture design has reduced the computation cost and complexity score of the designed FbPEA dynamic communication microarchitecture. The designed microarchitecture's efficiency has been verified with some critical parameters like power usage, execution time, and energy consumption. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Internet of things

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Efficient Architectures of FIr Filters using distributed Arithmetic 3

Efficient Architectures of FIR Filters using Distributed Ari...

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3rd International Conference on Automation, Computing and renewable Systems, ICACrS 2024

作者： Kumar, G. Charan Shiyamala, S. Department of ECE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology India

ISBN: (纸本)9798331532420

This research presents an overview of the Finite impulse response (FIr) filter architectures that utilize distributed arithmetic design (dAd). This paper reviews non-reconfigurable as well as reconfigurable FIr filter architectures using dA. General Multiply Accumulator (MAC) based FIr filter architectures require large chip area, consume more power and enforce a limitation on the order of filters. dAd technique is a bit serial operation which has high throughput processing capability, cost effective, area and power efficient. This paper presents different realizations of FIr filters using different dAd techniques namely LUT based dAd, LUT-Less dAd, shared LUT based dAd. This paper presents a comparative analysis of different dA based FIr filters and can form a basis for further work on dA based reconfigurable FIr filters. © 2024 IEEE.

关键词： FIr filters

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Webcam painting canvas window application using OpenCV and Numpy

Webcam painting canvas window application using OpenCV and N...

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Usha, V. Arivubrakan, P. Sai Balaji, K. CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9781032669663

designers all understood quite well that the most popular and efficient means of expression for our emotions are via art and writing. In the olden days, people used to write or print on the rocks, walls, stones, but as time passed the process changed. People had discovered new plants and extracted the minerals and they turned it into papers. Then they created different kinds of artificial papers. In this modern area, this has gone too far. People are using electronic devices like screens, where we can write, draw and represent various structures, symbols, arts, painting, etc. either by hand, by typing and also just with a single tap. But now, we are taking this process more far, making it easier to use and easier to express your feeling just by moving your little fingers. We know canvas is a special type of surface where it is also used for painting. And now imagine a surface where there is no physical object and try to paint or write anything. Is it possible? Yes, this is possible using air canvas. Air canvas is a digital drawing which uses free-hand. All you have to do is to think about what you want to express or show, and then just move your finger according to what you wanted to express. © 2024, CrC Press/Balkema. All rights reserved.

关键词： Thermoelectric equipment

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Systematic Analysis of Historical Analogies and Challenges: Lung Cancer detection 5

Systematic Analysis of Historical Analogies and Challenges: ...

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Sathyamoorthy, K. ravikumar, S. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Chennai Avadi India

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379945

Cancer is a fatal condition that usually comes on by the aggregation of several diseases and inherited illnesses. Wherever in the human body, cancerous cells can develop and cause deadly growths. Cancer, referred to as a tumor, needs to be immediately and precisely identified in its earliest phases in order to decide what can be effective for its treatment. Even while each method has its own distinct problems, some of the main reasons for death include challenging histories, poor diagnosis, and subpar treatments. The goal of the study is to evaluate, classify, examine, and discuss recent developments in the detection of cancer in lung using different learning techniques. The main objective of this work is to study and compare the different modalities like machine learning using unsupervised, supervised, as well as deep learning algorithms that can help in lung cancer detection and therapy. The findings are compared using standard datasets for metrics including precision, specificity, sensitivity, and accuracy. Several novel strategies are clustered under one cluster. Last but not least, challenges are also emphasized for prospective future work. © 2024 IEEE.

关键词： Lung cancer

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AI Based Skin Cancer diagnosis 2

AI Based Skin Cancer Diagnosis

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2nd IEEE International Conference on Emerging research in Computational science, ICErCS 2024

作者： rajalakshmi, N.r. Sankar, Pasala Mani raju, Kosireddy Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai63 India

ISBN: (纸本)9798331534950

This study presents an innovative approach to skin cancer detection using Artificial Intelligence and deep learning methodologies. The AI model, trained using Convolutional Neural Networks (CNNs), outperformed human diagnostic abilities in distinguishing between cancerous and healthy skin, achieving an accuracy rate of over 90% in detecting skin cancer. The model also demonstrated proficiency in classifying various types of skin cancers, offering expedited and precise diagnoses. This breakthrough in skin cancer diagnosis has the potential to revolutionize early detection and alleviate strain on healthcare systems, enabling individuals to screen for skin cancer without a doctor's visit. The designed AI-powered deep convolutional neural network system capable of automatically analyzing and classifying skin lesions based on dermoscopic images. By harnessing the power of deep learning and CNNs, it endeavors to achieve heightened accuracy and efficiency in skin cancer detection. © 2024 IEEE.

关键词： Lung cancer

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Improving Sign Language recognition for deaf and Hard of Hearing Individuals using the VGG16 Model 3

Improving Sign Language Recognition for Deaf and Hard of Hea...

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3rd International Conference on Automation, Computing and renewable Systems, ICACrS 2024

作者： Benjamin, Minu Inba Shanthini Watson Patan, Yaseen Kumar, Ansilin S.M. reddy, Pocharam Nithyanandh Ahamad, Syed Faheez Puneeth, Muvvala Sai Department of Computer Science & Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Artificial Intelligence and Data Science Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9798331532420

Persons who are deaf and who cannot speak face a variety of challenges, which emphasises the need for greater research to offer appropriate assistance. Interaction and communication with others are a big challenge. Since sign language is the major means of communication for these people, there is a significant knowledge gap among hearing individuals when it comes to understand and interpret sign language. As a result, there has been a notable expansion in the field of sign language study to close this gap. This work highlights the importance of sign language detection and offers a thorough analysis of relevant studies carried out in this domain using deep learning technique. It approaches the issue from multiple perspective, including translation, sign language recognition, and access to relevant datasets. Understanding these facets is intended to create a meaningful impact on sign language literature and its practical implementation. VGG16 deep learning model for sign language recognition offers the best solution for solving communication challenges faced by deaf and muted individuals. The results show that the VGG16 based technique achieves accuracy of around 95.8%. The VGG16 model uses a Convolutional Neural Network (CNN) architecture, which applies many layers of convolutional filters to identify patterns and attributes in the input images. recognizing sign language using VGG16. © 2024 IEEE.

关键词： Convolutional neural networks

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