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3rd International Conference for Advancement in technology, ICONAT 2024

作者： rahul, S.G. rajkumar, r. Abburi, rudrakonda Sai Kumar reddy, B. Trivikram raja, C.H. Teja, K. Pavan Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350354171

This paper presents the design, development, and implementation of a scalable Condition Monitoring System for controlled-environment greenhouse farming. To continuously monitor key environmental elements influencing crop growth, the system interfaces an ESP32 microprocessor with various sensors that measure temperature, water level, humidity, light intensity, and methane. The developed system prioritizes the selection of sturdy hardware parts that are specially made to endure the various circumstances found in a greenhouse. To guarantee ideal growing circumstances for crops, the gathered data can be displayed in the live IoT Blynk portal and possibly examined using the threshold values that have been established. The proposed technology provides real-time insights and data visualization into the greenhouse environment to improve agricultural productivity, yield, and resource efficiency. This project aids in outperforming conventional greenhouse systems in economic aspects by providing automation and real-time data insights for ideal plant growth. In terms of sustainable agriculture, this is a paradigm change that encourages resource optimization, decreased environmental impact, and maybe higher agricultural yields. © 2024 IEEE.

关键词： Environmental monitoring

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IoT Based on Non-invasive Glucometer 7th

IoT Based on Non-invasive Glucometer

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7th International Conference on Smart Trends in Computing and Communications, SmartCom 2023

作者： Premalatha, P. Poonguzhali, E. rekha, r. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9789819908370

diabetes mellitus is named the most important developer source of any kind of major disease and if it’s not treated properly then the majority of it gives severe health-related issues and leads to death. This is considered one of the non-contagious diseases, and it occurs when the sugar level within the blood increases above an average value. Therefore, regular calculation of blood glucose levels could be the condition to take care of sugar patients. Existing techniques for the determination of blood glucose levels are invasive methods that carry small single-use needles that are directly pricked into a finger to collect blood samples out of the body so it's passed to the fresh test tube for further processing chemically to see the number of sugar molecules present there. However, tolerating and reducing the patient's pain and the use of strips of those techniques have led to the process of non-invasive techniques. The near-infrared LEd and photodetector determine the sugar and insulin concentration. The attentiveness of glycemia within the blood sample is estimated by the level of infrared emission in the blood. The total concentration level of sugar molecules is on the LCd in an appropriate unit. To start the process, insert the fingertip in between the NIr-LEd and NIr-Pd. The reflected signal is fetched by the NIr-Pd. The evaluation value obtained from it'll be filtered out and then amplified. The noise has been removed by FFT. The filtered signal and amplified to attach to an NPN transistor for getting the negative value and for early showing the evaluated value within the LCd. The signal has been connected to Arduino port A0. Finally, the output value is displayed on the LCd display. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Light emitting diodes

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Crop Yield Prediction: Leveraging Machine Learning for Sustainable Agriculture 2

Crop Yield Prediction: Leveraging Machine Learning for Susta...

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2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Keerthi, K. Tejaswi, K. Shalini, S. Kishore Kumar, K. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Cse Chennai India

ISBN: (纸本)9798350368413

: Accurate crop yield prediction is essential for ensuring food security and optimizing agricultural practices. Traditional methods often rely on historical data and expert knowledge, which may not always be sufficient. This research explores the application of machine learning techniques to predict crop yield based on various factors such as soil properties, weather conditions, and crop management practices. By analyzing historical agricultural data, this research study aims to develop robust predictive models. The research utilizes random Forest, a abstract- powerful machine learning algorithm to extract patterns from the data and make accurate yield predictions. The results of this study can provide valuable insights to farmers, enabling them to make informed decisions about crop selection, resource allocation, and risk management. By integrating machine learning, this research contributes to the development of sustainable agriculture practices and improves food security. © 2024 IEEE.

关键词： Adversarial machine learning

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design of a Ka-band Micro Strip Printed Antenna at 31 GHz for millimeter Wave Wireless Communication 2

Design of a Ka-band Micro Strip Printed Antenna at 31 GHz fo...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Sathish, M. Paik, Harikrishna Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology Dept. of ECE Tamil Nadu Chennai India

ISBN: (纸本)9798350365269

In recent years, printed antennas operating at millimeter wave (mmW) frequencies have gained more popularity for next generation wireless communication systems to meet the need for faster data rate, massive bandwidth and large coverage area. This paper proposes the design of a Ka-band microstrip patch antenna resonating at 31GHz for mmW communication. The proposed antenna has a rectangular geometry with non-resonating rectangular slots at the edges and along the sides of the patch. Further, a Sierpinski fractal slot and a pair of chevron shaped slots are loaded to achieve better impedance matching and wide bandwidth. The overall dimension of the antenna is 7×6×0.508 mm3 which is integrated on rogers rT/duroid 5880 substrate with ϵr = 2.2 and tan δ = 0.0009. The results reveal that the proposed design achieves wide bandwidth of 1.46 GHz (30.26-31.72 GHz) centered at 31GHz and exhibits total gain of 7.95dB. The performance of the antenna demonstrates its applicability for mmW communications. © 2024 IEEE.

关键词： Millimeter waves

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SEr Analysis using GFdM System with Maximal ratio Transmission technique under Ω − μ Fading Channel

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Journal of Engineering science and technology review 2023年第3期16卷 1-6页

作者： Jada, Lingaiah Shiyamala, S. School of Electrical and Communication Engineering |ECE Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Tamilnadu AvadiChennai600 062 India

Generalized frequency division multiplexing (GFdM) system with maximal ratio transmission (MrT) scheme is considered to analyse the symbol error rate (SEr) performance over Ω − μ fading channel. In present days, low latency and low consumption of energy devices are used and these can be achieved using multicarrier techniques. The GFdM is one such multicarrier technique which has a capable to provide these requirements. Low out-of-band (OOB) radiation is one of the GFdM technique's main benefits. Initially, in this study, GFdM-MrT system is used to investigate the SEr expression analysis in Ω − μ fading. Initially, we have addressed the closed form of novel mathematical analysis of SEr expression under Ω − μ fading channel. The rayleigh, Nakagami-m, and Nakagami-q fading channels are all special instances in the suggested derivation. Later, a Monte-Carlo simulation-based test-bed is developed in MATLAB software and simulations are evaluated for various values of fading parameters, different roll-off factors, and the number of transmitting antennas Nt. The GFdM-MrT technology provides lower SEr values and it is more dependable for highspeed communications, it can be inferred. The main object of this paper is to compare the SEr of GFdM-MrT system with GFdM system without using MrT technique in Ω − μ fading channel for different comparing parameters like at number of transmitting antennas Nt, different values of roll-off factors (β) and fading parameters α and μ © 2023 School of science, IHU. All rights reserved.

关键词： Fading channels

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Performance and Analysis of Skin Cancer detection Using deep Learning 3

Performance and Analysis of Skin Cancer Detection Using Deep...

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3rd IEEE International Conference on Intelligent techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Hemanth, P. dhanujay, L. Girinadh, G. Bennet, M. Anto Subha, K.J. Jeyaraj, Josephine Pon Gloria Department of ECE Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Avadi Chennai600062 India

ISBN: (纸本)9798350361186

Skin cancer is notably one of the most dangerous expressions of this ailment, originating from dNA damage in skin cells that results in the formation of genetic abnormalities or mutations on the skin. The insidious characteristic of skin cancer lies in its inclination to gradually spread to other parts of the body, underscoring the importance of early detection for successful treatment. Given the increasing prevalence of skin cancer, its elevated mortality rate, and the significant expenses associated with medical interventions, prompt diagnosis becomes imperative. Acknowledging the severity of these challenges, researchers have developed various methods for the early identification of skin cancer. Parameters such as the symmetry, color, size, and shape of lesions are utilized to distinguish skin cancer and differentiate benign cases from melanoma. This paper explores deep learning approaches applied to the early detection of skin cancer, presenting the study's findings through tools, graphs, tables, techniques, and frameworks. This enhances comprehension and contributes to the body of knowledge in this critical field. © 2024 IEEE.

关键词： diagnosis

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riddance of Weed Using an Agri-robot Employed by Arduino and ESP32 CAM 15

Riddance of Weed Using an Agri-Robot Employed by Arduino and...

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

作者： Vinod, dasari Naga Kamalesh, A. Bhaskar, B. Teja, B. ravi Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India

ISBN: (纸本)9798350370249

This article presents the enhancement of a weed detection robot designed to automate the identification and riddance of unwanted vegetation in agricultural fields. The robot integrates a suite of hardware components, including an ultrasonic sensor, Arduino microcontroller, ESP32 CAM, robotic hand, L293d motor driver, battery, power supply module, Bluetooth module, and dC motor for locomotion. The dC motor is utilized to drive the wheels of the robot, enabling it to traverse the agricultural terrain efficiently. The ultrasonic sensor facilitates obstacle detection, ensuring safe navigation through the field while avoiding collisions. Meanwhile, the ESP32 CAM captures visual data of the surroundings, which is processed by machine learning algorithms to identify and classify weeds. Upon identifying weeds, the robotic hand, controlled by the Arduino microcontroller via the L293d motor driver, is deployed to remove the unwanted vegetation. The Arduino microcontroller acts as the central processing unit, orchestrating the operation of all components and executing decision-making algorithms. Additionally, the inclusion of a Bluetooth module enables remote monitoring and control of the robot, providing farmers with real-time updates on weed infestation levels and operational status. The weed detection robot offers a solution for weed management in agriculture and obtained 97% accuracy, promising increased crop yields and reduced labor costs through efficient weed riddance. ©2024 IEEE.

关键词： dC motors

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Implementation of Smart Solar Power System Monitoring and Automated Cleaning Mechanism with Python based Embedded technology 4

Implementation of Smart Solar Power System Monitoring and Au...

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4th International Conference on Intelligent technologies, CONIT 2024

作者： dhal, P.K. reddy, C.Jaswanth Kumar, r S Aswin Sabareesh, S. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Electrical and Electronics Engineering Chennai India

ISBN: (纸本)9798350349900

The research paper focuses on the design and implementation of a 55 Watts solar power monitoring and automated cleaning system integrated with Python-based embedded technology. The system aims to maximize the efficiency of solar power generation by monitoring the output of the solar panel and automatically cleaning it when necessary to maintain optimal performance. The system consists of voltage and current sensors to monitor the solar panel output, a dHT11 sensor to measure temperature and humidity. The Ldr sensor is to detect ambient light levels. The data from the sensors are processed by an Arduino Uno board and sent to a Node MCU board which communicates with a server to log and display the data on the LCd screen. The Python program running on the Node MCU board analyses the sensors and triggers an automatic cleaning mechanism using an L293 driver to move cleaning brush across the surface of the solar panel. This ensures the solar panel remains free from dust and dirt. © 2024 IEEE.

关键词： Python

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Alzheimer's disease recognition and detection using Machine Learning 5

Alzheimer's Disease Recognition and Detection using Machine ...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Bennet, M. Anto Jeyaraj, Josephine Pon Gloria Subha, K.J. Vidhya, Ch. Sri Yamini, K. Pasha, P. Laljan Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Ece Chennai Avadi600062 India

ISBN: (纸本)9798331504403

Alzheimer's disease is a neurological disorder marked by memory loss, diminished cognitive function, and difficulties with day-to-day activities. As the world's population ages, Alzheimer's disease has become a major public health concern. This review looks at what is now known about Alzheimer's disease, including its causes, diagnosis techniques, and therapies. Amyloid plaques and tau neurofibrillary tangles are examples of abnormal protein clumps that accumulate in Alzheimer's disease pathogenesis and cause synaptic dysfunction, neuronal death, and eventually cognitive impairment. Familial forms of Alzheimer's disease have been linked to genetic mutations, including those in the APP, PSEN1, and PSEN2 genes. © 2024 IEEE.

关键词： Machine learning

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Historical Strategies Flow detection for Organizations using Machine Learning

Historical Strategies Flow Detection for Organizations using...

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2024 International Conference on Integration of Emerging technologies for the digital World, ICIETdW 2024

作者： dilip Charaan, r.M. Sankar, M. Sivaprakash, P. Vimala Ithayan, J. Chithambaramani, r. Marichamy, d. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science & Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala Institute of Science and Technology Department of ECE Chennai India Vel Tech Rangarajan Dr. Sagunthala Institute of Science and Technology Department of CSE Chennai India

ISBN: (纸本)9798331541170

Companies hire a wide variety of strategies to attain their enterprise dreams, which could embody diverse elements in their operations. The venture investigates the feasibility of predicting a company's future profitability using machine studying based on ancient strategic facts. With the emergence of gadget gaining knowledge of and information mining in current years, new thoughts and methods have emerged in the detection of bizarre network flows for monetary statements. This explores the application of device studying techniques, especially random forest and selection tree algorithms, for historic method waft detection in organizations. It targets to increase a robust methodology to research historical statistics and perceive patterns that screen strategic shifts or traits over time. By leveraging random woodland and choice tree algorithms, which are well-perfect for class responsibilities and function selection, the have a look at seeks to offer precious insights for strategic choice-making. The proposed technique involves preprocessing the statistics, choosing applicable functions, and schooling the ML models to come across historical method flows. The outcomes are predicted to beautify underneath-status of ways businesses evolve their strategies through the years, thereby supporting in enhancing strategic making plans and decision-making procedures. The model's powerfulness is classified on a checking out set to decide its accuracy in forecasting profitability, and discover styles which might be related to future earnings increases. It demonstrates the capability of device getting to know to transport past surely detecting abnormalities in monetary statements. By reading a broader variety of ancient strategic information, the performance won is above 85% to 95%. This deeper information empowers businesses to make informed choices about aid allocation. This approach offers several benefits over traditional forecasting techniques. The version can probably help ag

关键词： Profitability

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