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

作者： Maitreya, Jaldu Krishna Nath, Gunda Uday Kanagachidambaresan, G.r. Arun, C.A. Arvind, A.r. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Dept of Ece Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Dept of Cse Chennai India Ashok Leyland Ennore India

ISBN: (纸本)9798350370249

In today's industries, optimizing energy consumption is critical, but outdated monitoring devices cause inefficiencies. Our paper proposes an IoT-based solution utilizing the AdE9000 chip for real-time monitoring of energy parameters like current, voltage, frequency, power, power factor and power quality. By leveraging the AdE9000's high accuracy and unique power quality measurement capabilities, industries can identify areas of overconsumption and implement targeted efficiency measures. For example, real-time power quality analysis aids in detecting and mitigating issues such as voltage fluctuations, thereby reducing downtime. data analytics enables industries to make informed decisions, optimize operations, and cut costs, demonstrating IoT's transformative potential in improving industrial energy efficiency and sustainability. Our approach for this idea aligns perfectly with the capabilities of the AdE9000 chip. Overall the AdE9000 can provide real-time alerts in addition to sending data to the cloud for every 100 milli seconds, which is pivotal in bolstering the performance, efficiency, and sustainability of industrial operations. Our solution, powered by the AdE9000 chip, ensures industry-leading accuracy, with a precision rate of 99.89%, enabling precise monitoring of energy parameters. This high level of accuracy enhances decision-making and empowers industries to achieve unparalleled efficiency gains and sustainability objectives. © 2024 IEEE.

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5G ready: A Compact Two-Port Antenna for Sub-6GHz Applications

5G Ready: A Compact Two-Port Antenna for Sub-6GHz Applicatio...

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2025 International Conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Murugan, C. Kavitha, T. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Chennai India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509828

The new design is proposed based on Two-port antenna and Simulation outcome with an operating frequency range of 3.3-5.,5GHz, which covers N77, N78, N79 and Wireless Local Area Network (WLAN) bands. The newly coined antenna design achieves gain of 3dB and ensure trustworthy and effective communication in 5th Generation networks. Multiple Input and Multiple output (MIMO) parameters like Envelope Correlation Coefficient (ECC), Total Active reflection Coefficient (TArC)., diversity gain, Channel Capacity Loss (CCL) and radiation Efficiency which are measured in a multi-antenna system. The proposed antenna design illustrates excellent MIMO performance which achieves 5G Privileges likeenhanced mobile broadband (eMBB), ultra-reliable low-latency communications (UrLLC), and massive machine-type communications (mMTC). The Compact Size and Antenna radiation which makes it fit into 5G devices, like smartphones, tablets, and laptops. © 2025 IEEE.

关键词： Wireless local area networks (WLAN)

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A Feature Selection technique–Based Approach for Author Profiling Using Word Embedding techniques 8th

A Feature Selection Technique–Based Approach for Author Pro...

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8th International Conference on Computers, Management and Mathematical sciences, ICCM 2022

作者： Kavuri, Karunakar Kavitha, M. CSE Department Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9783031511660

Textual data are tremendously increasing on the World Wide Web through different social networking platforms, such as blogs, review sites, Facebook, Instagram, Twitter, etc. Crimes or frauds are also growing with the development of text in these platforms. Most of the users on these platforms create accounts with false information and send harassing and threatening messages. Knowing the details or basic information of text posted on these platforms is a very important task to control fraud. Author profiling (AP) is one technique used by the research community and social network administrators to know the author’s information related to messages posted on social networking platforms. Author profiling is a method of detecting demographic profiles such as age, gender, education, etc., of authors based on their written texts. Author profiling techniques are used in various applications of text processing, such as marketing, forensic analysis, and security-related fields. Most author profiling techniques use the content information of text to differentiate the writing styles of authors. The dataset contains a huge number of content words and, the identification of relevant words for differentiating the writing style of different authors is one challenging task to the research community. Feature selection algorithms are proposed by the researchers to find relevant features in the dataset. In this article, we developed a feature selection technique–based approach by using word embedding techniques for predicting the gender and age from the selected dataset. The PAN competition author profiling datasets are considered in this article for experimentation. In the proposed approach, word embedding techniques are used for converting words into word vectors. The similarity measure is used for finding the similarity among the word vectors. Similar words are grouped into clusters. Select the most important words from these clusters and consider them for experimentation. Selected w

关键词： Embeddings

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design and development of Efficient Feeding Network Structure for Patch Antenna Array Modules in UAV Communication Applications

Design and Development of Efficient Feeding Network Structur...

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International Conference on VLSI, Signal Processing, Power Electronics, IoT, Communication and Embedded Systems, VSPICE-2022

作者： Bharati, Chandravijay Prasanna, r. Balasubramanian, E. Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai India Department of Mechanical Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai India

ISBN: (纸本)9789819944439

This article focused on the development of microstrip patch antenna with linear and planar array distribution structures. Ansoft HFSS electromagnetic simulation software was used to analyze the radiation and reflection parameter of the designed element. Initially, single element antenna was realized and further 1 × 2, 2 × 2, and 1 × 4 array structures were analyzed with a due consideration of two different substrate materials such as duroid-5880 and Fr-4. 1 × 4 array antenna with duroid-5880 offers highest gain of 14.12 dB. To validate the design concept, 1 × 2 array antenna was fabricated. S11 parameter was measured using a vector network analyzer and it has downward frequency shift by 54.5 MHz as compared to simulated results. The radiation characteristic of the antenna was measured on anechoic chamber, and the E/H plot reveals that antenna is unidirectional. Measured gain is enhanced by 7.82 dB as compared to simulated results. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Improving Energy Efficiency in Wireless Sensor Network with Intelligent Energy Prediction Using Machine Learning Approach

Improving Energy Efficiency in Wireless Sensor Network with ...

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2024 International Conference on Computational Intelligence for Green and Sustainable technologies, ICCIGST 2024

作者： Panneerselvam, Bhuvaneswari devarasu, Neelamegam Pasupulati, Baburao Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350381887

In our day-to-day life, one of the emerging roles of green energy in wireless sensor network shoves the investigations of recent technological and economical solutions for solar energy. Saving external energy is one of the fundamental factors in any wireless sensor network with limited storage capacity. due to different environmental conditions, the energy conversation is too fast in the solar system and unconstrained atmospheric resource energy leads to operate the rechargeable batteries in the outdoor systems. However, some fluctuations occur in the environmental side. It is very crucial to predict the unnecessary errors in the sensing devices. Also, to examine the future energy and to maintain the system reliability in the solar powered wireless sensor network, the accurate prediction models are required. In this work, the Energy Efficient Nonlinear Autoregressive (EENA) algorithm using Machine Learning approach is proposed. With this approach, the algorithm effectively predicts the future energy status with respect to different time slots. The proposed algorithm gives a promising solution to prolong a battery life and the accurate predictions in the outdoor energy harvesting network. © 2024 IEEE.

关键词： Energy Harvesting Error Prediction Machine Learning Sensor network Solar

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Evaluation of tribological properties of thermally sprayed tungsten carbide coating on AISI1045

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Materials Today: Proceedings 2023年 72卷 2193-2198页

作者： Muthukumar, S. Ganesh, B. dilip raja, N. Selvam, M. Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Avadi Chennai 600072 India Vel Tech Rangarajan Dr.Sakunthala R&D Institute of Science and Technology Avadi Chennai 600072 India

The plasma based thermal coatings have been used for over five decades. The provision of plasma spray coatings on the low strength materials such as low carbon steels find prominent position in cost savings and replacement cycles of sliding components. Particularly the AISI 1045 based components find important role in automotives and marine structures. A clear understanding of the impact of thermal conditions on enhancement of surface characteristics for low carbon alloys during plasma spray coating is needed for deciding the lifecycle of products involving high temperature sliding conditions. Plasma Spray Coating was employed on AISI1045 plates and the improvement of strength, hardness and wear resistance along with the material composition was studied. Plasma Spray Coating is improved the wear resistance of AISI1045 sheets by 30 percent. The problems faced by the practicing professional such as frequent replacement of siding components and shorter life expectancy are reduced much by employing the thermal spray coating. © 2022

关键词： Tribology

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detecting Ship Wake from Complex Backgrounds in Synthetic Aperture radar (SAr) Imagery

Detecting Ship Wake from Complex Backgrounds in Synthetic Ap...

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2024 International Conference on Intelligent Computing and Sustainable Innovations in technology, IC-SIT 2024

作者： Mathias, Ajisha Pradeepthi, Gubba Vivek, Ongole Kishore, Kummara Department of ECE Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9798350369175

Ship wake identification is crucial for analyzing ocean surface synthetic aperture radar (SAr) pictures because ship wakes typically include important vessel information. A significant proportion of detection algorithms make use of the linear traits of ship wakes by converting the lines in the spatial domain into either dark or light points in a transform domain, using techniques like the Hough or radon transforms. This study presents a novel approach for detecting ship wakes using a Gaussian Mixture Model (GMM). The method involves obtaining the radon transform of the SAr image, which enhances the visibility of linear features. In comparison to the state of art methodologies, the findings show that the method is successful in achieving greater wake detection accuracies. © 2024 IEEE.

关键词： Synthetic aperture radar

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Crop Yield Prediction Using Machine Learning techniques Based on Soil and Environment Traits - A Survey 2

Crop Yield Prediction Using Machine Learning Techniques Base...

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2nd International Conference on Emerging Trends in Information technology and Engineering, ic-ETITE 2024

作者： Mariammal, G. Sridevi, S. Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Chennai India

ISBN: (纸本)9798350328202

In research, the examination of agriculture is increasing rapidly. Crop yield prediction is an important aspect in agriculture. In earlier days, farmers get good yielding. due to the inefficiency in soil nutrients level and climatic changes crop yield level decreasing day by day. Hence, estimating the production is a crucial role in agriculture area also it helps to farmer for storing and marketing their yielded products. For predicting the precise agricultural yield, a variety of techniques, including remote sensing and machine learning, are used. This paper discussed a number of strategies for predicting crop yields that had been used by various researchers. In accordance to this review, the deployment of machine learning in agriculture indicates more effective and precise farming with fewer human assistance, as well as higher quality goods. © 2024 IEEE.

关键词： remote sensing

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5G Based Millimeter Wave Spectrum Sensing for Cellular Networks

5G Based Millimeter Wave Spectrum Sensing for Cellular Netwo...

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2025 International Conference on Multi-Agent Systems for Collaborative Intelligence, ICMSCI 2025

作者： Supraja, C. Kavitha, T. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Chennai India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509828

Spectrum is availed extensively in modern civilization. The frequency is commonly referred to as intangible radio frequency. The frequency of the Invisible radio is used to transmit wireless signals. The allocation and sensing for a spectrum in AM and FM base stations mostly takes place in the region of the electromagnetic spectrum. An intelligent radio can efficiently handle this spectrum sensing, allocation, which can assist to reduce spectrum shortages (Cognitive radio). Spectrum is distributed via the cognitive radio technology to both licensed and unlicensed users. The spectrum is allocated dynamically, and as a result of this tactic, spectrum usage will rise. The wireless sensor is made up of hundreds of wireless nodes placed within a specific radius for spectrum allocation and sensing. The most modern spectrum sensing techniques employed in cognitive radio networks will be Covered. The Two step Energy detection Algorithm is used for spectrum Sensing which produces high efficiency. In Particular, the work shows the better Coverage area by estimating distance, SNr,False Alarm Probability, detection Probability etc © 2025 IEEE.

关键词： Cognitive radio

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Optimized and Effective Feature Selection-Based Hybrid deep Learning Framework for Accurate Water Quality Prediction: A review 2

Optimized and Effective Feature Selection-Based Hybrid Deep ...

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2nd International Conference on Artificial Intelligence Trends and Pattern recognition, ICAITPr 2024

作者： Kumar, N. Ashok Jeevanantham, V. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering India

ISBN: (纸本)9798350368000

Analyzing the quality of water is essential for maintaining ecosystems, protecting human health, and guaranteeing sustainable management of water resources. Efficiency, accuracy, and scalability issues plague traditional techniques of assessing water quality. Using deep learning methods to overcome these obstacles and improve the efficacy of water quality monitoring has gained popularity in recent years. In the context of environmental monitoring, this survey study offers a thorough summary of the most recent developments in deep learning applications for water quality analysis. The context and relevance of water quality analysis are described in the introductory section, which also highlights the necessity of promptly detecting and mitigating pollutants and changes in water parameters. A summary of deep learning in environmental monitoring is also given, emphasizing how cutting-edge data-driven techniques might transform the measurement of water quality. The next part explores deep learning methods, such as CNNs, rNNs, and dBNs, that are often used in water quality study. The ability of these methods to analyze patterns in geographical and temporal data, find anomalies, and forecast factors related to water quality are highlighted. Subsequently, the investigation delves into the many uses of deep learning in environmental monitoring, with particular emphasis on applications related to remote sensing, contamination detection, aquatic habitat monitoring, and water quality prediction. Every application topic is investigated thoroughly, emphasizing important approaches, difficulties, and prospects for further study and advancement. © 2024 IEEE.

关键词： Environmental monitoring

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