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AI Based license Plate recognition using CNN

The discovery based on the artificial intelligence of the Indian license plate is our theme. We have created a program that is able to take a photo from the surrounding area. At the end of the hardware, we need a pc (or raspberry pi) and a camera and at the end of the software, we need a library to download and process data (image). We have used OpenCV (4.1.0) and Python (3.6.7) for this project To get something (license plate) in the picture we need another tool that can see the Indian license plate to use Haar cascade, pre-trained on Indian license plates (to be updated soon) be YOLO v3). Our main objective is to establish a system that gives us the license plate number of a vehicle when given a low definition image captured by a surveillance camera at toll collection centres. Mostly our system is demanded for the purpose of traffic monitoring. Hence we designed a system that lessens the manual work of entering the license plate numbers. And also we built a system that increases the speed of processing toll collections or traffic violation punishments. Our model is built on convolutional neural networks where several mathematical computations are done within the six hidden layers and give the output characters using contour detection and character segmentation.

Published by: K V Yaswanth, Anvesh Donthi, A Venkata Ramana, Dr. M. Poornachandra Rao

Author: K V Yaswanth

Paper ID: V7I3-2167

Paper Status: published

Published: June 28, 2021

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Research Paper

Age and Gender Detection using OpenCV

In this fast emerging world Artificial Intelligence plays a very vital role in every field of science . Everything is being automated from operating a remote to driving a car using Artificial Intelligence. We show a glimpse of such automated experience with this project. In this project we show how easy it is to detect faces and identify gender along with gender with the help of CNN(Convolutional Neural Networks) and OpenCV. Using these fields of Artificial Intelligence we can reduce the use of hardware components and complexities in this project. Along with CNN and OpenCV we use Adience dataset so that the output is achieved with accurate values in training and validation. For the output to be determined even with multiple parameters we use pre-trained model that is caffee model along with OpenCV. The proposed model can be used in surveillance purposes or in medical purposes.

Published by: Mahija Kante, Dr. Esther Sunandha Bandaru, Gadili Manasa, Meghana Emandi, Vanarasi Leela Lavanya

Author: Mahija Kante

Paper ID: V7I3-2163

Paper Status: published

Published: June 28, 2021

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Research Paper

DNA sequencing using Nanomanufacturing

In this paper, we nanomanufacture for the first time a novel DNA sequencing using nanoscale hole, in synthetic single digit nanometer thickness membrane. The DNA sequencing is carried out for each base of DNA to sequence and detect by placing a multimeter and the readings are taken on the edges of the synthetic single digit nanometer thickness membrane. The multimeter readings gives the voltage change readings for each base of DNA as there will be a change in concentration in the presence of DNA inside a nanoscale hole, in synthetic single digit nanometer thickness membrane.

Published by: Vishal Nandigana, Sharad Kumar Yadav, D. Manikandan

Author: Vishal Nandigana

Paper ID: V7I3-2160

Paper Status: published

Published: June 28, 2021

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Research Paper

AC nanopump design and manufacture

In this paper, we design and manufacture for the first time a novel AC nanopump to generate flow velocity. AC voltage is needed at nanoscale pump designs and manufacture because DC voltage nanopumps design and manufacture generate bubbles/cavitation/instability and are not scalable designs and are not scalable to manufacture. AC voltage driven nanopump designed in and manufactured demonstrated in this paper overcomes bubble generation/cavitation/instability and our AC nanopump is a scalable design and manufacture.

Published by: Vishal Nandigana, Sharad Kumar Yadav, Manikandan D., K. D. Jo, A. T. Timperman, N. R. Aluru

Author: Vishal Nandigana

Paper ID: V7I3-2146

Paper Status: published

Published: June 28, 2021

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Research Paper

“Restoration of ecosystems” using a trapping method of Carbon Dioxide

I have an idea to reduce the carbon dioxide from nature and save the ecosystem. Some basic chemicals required for this process. This process is the conversion process of carbon dioxide. In this process probably a new industry will be born. This process can be used in thermal power stations and burning waste paper. Because this is about 85% of the total electric power 558990 GWH generated in 2007-08 by thermal power plants in India. Thus, the total CO2 emissions can be estimated as about 523 million tons from all the thermal power plants in India. In this process, the source of carbon dioxide is the burning waste papers or thermal power plants. If we burn the paper the paper produces carbon dioxide (but not roasting the paper).

Published by: Aniket Bahadur

Author: Aniket Bahadur

Paper ID: V7I3-1924

Paper Status: published

Published: June 28, 2021

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Research Paper

Driver Drowsiness Detection System

The world is becoming automated day by day in each and every aspect. The technological approaches to solve every human problem are evolving at a great interest in this rapid advancing environment. Automated houses, cars(for instance, Tesla self-driving cars), machinery, industries can be considered as the progressive outcomes which made the human life comfort, safe and easy. Although, there exist numerous situations that are damaging and the lives of people miserably . One of those circumstances is “Road Accidents”. There may be many reasons for this problem where “Driver fatigue” is one of those. “Each year, around 1.5 lakh people die in road mishaps in India.” –The Times of India[17]. To mitigate these accidents, we develop a model based on Convolutional Neural Networks (CNNs), Deep Learning which can detect the sleepiness or fatigue and notify the driver(or the person who is driving). In this paper, we developed a model using CNN classifier that identifies whether a driver is sleepy or not. The model here also provides an alerting alarm when the driver is sleeping (whenever he/she closes eyes). The proposed model is also evaluated using large amount of data to increase its accuracy and correctness while detecting the person’s drowsiness.

Published by: Komati Jyoshna Srivalli, Dr. Esther Sunanda Bandaru, Karipireddi Swathi, Kolli Sri Mahathi Gayathri, Kommanaboina Lakshmi Prasanna

Author: Komati Jyoshna Srivalli

Paper ID: V7I3-2158

Paper Status: published

Published: June 28, 2021

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