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Research Paper

Image classification based plant disease detection

Agriculture is one of the important aspects in the world, also the contribution of agriculture to the GDP of India increased to 19.9 percent in 2020-21 from 17.8 percent in 2019-20. Globally crop disease becomes a major cause of concern, so to overcome this concern a plant disease detector should be there which gives good results and increases the yield for farmers. In this scenario, the best option for dealing with crop disease identification is an Image Classification based disease detection system. The key goal of this project is to identify the disease in real-time by uploading an image of the infected plant leaf to the system. Aside from that, the system suggests remedies for the particular disease that is identified by the system. Our proposed research paper includes various phases of implementation namely data set creation, image pre-processing, image post-processing, and finally disease classification and grading. Overall, we are using machine-learning techniques to train the dataset and finding the disease for that particular plant.

Published by: Jinesh Kansara, Kartik Atul Nerkar, Mihir Manish Brahmbhatt

Author: Jinesh Kansara

Paper ID: V7I3-1927

Paper Status: published

Published: June 18, 2021

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Review Paper

Mechanical response of PTFE-based nanocomposites

Polytetrafluoroethylene (PTFE), reinforced with Boron Carbide (B4C) and Molybdenum disulphide (MoS2) were prepared by Studying the various manufacturing processes and selecting the best suitable for Producing this Composite. Mechanical Properties such as the Tension test, Compression Test, and Hardness (Shore hardness) were done and their results were studies accordingly. The Composition of (MoS2), Boron, and PTFE compounds were varied with different Percentages so as to get the Optimized Result for Tension Test, Compression Test, and Hardness.

Published by: Aashish Sulebhavi, Bharat Aldar

Author: Aashish Sulebhavi

Paper ID: V7I3-1928

Paper Status: published

Published: June 18, 2021

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Survey Report

Automatic helmet detection & license plate recognition using CNN & GAN

Enforcing the use of helmets on every bike rider is mandatory nowadays because of the high accident rate and poor road conditions. There are laws regarding safety measures that ensure the use of a helmet. But for now, they involve manual intervention which is not so effective as of now because bike riders sometimes tend to escape without any penalty/fine after breaking the safety rules like wearing a helmet while riding. Automation is a better way to deal with this problem but automation in this area comes with its own challenges. To name a few, Low-quality image frames (low image resolution, pixel density, etc.), rain, dew and fog, and partly hidden faces. The robustness of detection methodology strongly depends on the strength of extracted features and also the ability to deal with the lower quality of extracted data. The first goal of this project is to boost the potency of helmet detection and then recognizing the license number plate recognition. This model consists of many essential steps developed using today’s most advanced amp; optimized CNN, GAN models amp; libraries. It is a classification-based model that uses a supervised learning approach to train CNN and Character Segmentation algorithm. The proposed helmet detection model can be used to detect helmets and recognizes license plates even in adverse conditions using character segmentation and CNN.

Published by: Pranav Sanjay Patil, Damini Kailas Pawar, Shruti Vilas Bairagi, Varun Dipak Bharambe, Nilesh Wankhede

Author: Pranav Sanjay Patil

Paper ID: V7I3-1921

Paper Status: published

Published: June 18, 2021

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Research Paper

Agriventure – Data analytics for farming and agro-businesses

Agricultural statistics and forecasts are a valuable resource that the government has not fully used despite their significance. Our project's goal is to automate this process by incorporating data mining and analytics concepts. More precisely, our project aims to address the social issue of drought by analyzing data for every crop in the state of Maharashtra, including crop statistics, rainfall, temperature and strain, production data, and other factors. Efficient countermeasures and recommendations would be provided based on the detailed studies conducted as part of this initiative, which, if applied quickly, will assist in addressing the drought issue in our state. It will also include forecasts for increases or decreases in consumer demand for specific agricultural goods, which will support agro-based sectors and enterprises. Data may be analyzed to uncover different patterns, such as recommendations to farmers for growing specific crops based on soil type and weather forecasts, district-level rainfall, and increases or decreases in market demand for specific agricultural goods. The project's final product will be research-driven publications that detail these patterns and will be based on data collected over the last three years. Drought mitigation measures would be proposed and also crop suggestions for the drought-prone regions, which will aid in the productive operation of AgriBusinesses.

Published by: Akshita Biyani, Bhoomi Bhanushali, Drishti Jain, Charmi Savla, Sangeeta Nagpure

Author: Akshita Biyani

Paper ID: V7I3-1882

Paper Status: published

Published: June 18, 2021

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Research Paper

Effect of vibration from railways on construction sites

In consideration of effects of vibration and noise to environment, construction, and human beings . railway is more effective solution over traffic, Railway generated ground born vibrations and noise is a big problems to the peoples , construction sites near the railway lines/track. Ground-borne vibrations resulting from the railway traffic have become an important environmental issue which has aroused a great deal of public attention. In this paper, a survey of the researches conducted on the problem of vibrations resulting from trains moving on railway line/track.. the grooving network in railway track with high speed rail track there is need of improvement in railway tracks/lines. For this we are taking different methods in study , some researchers. There is more effective method is FST (floating slab track) which reduces frequency up to 15Hz, further improvement in FST we trying mass spring system which reduce vibration frequency up to 5Hz. And this is long life (up to 60years) .

Published by: Yogesh Byale, Piyush Ghate, Akshay Kandle, Amar Motegaonkar, Pranav Poshetti, Pranoti Mahajan, Dr. Sariputt Bhagat

Author: Yogesh Byale

Paper ID: V7I3-1939

Paper Status: published

Published: June 18, 2021

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Research Paper

Solution on traffic congestion for Pune

Traffic condition in most of the cities are very complex. The high increase in number of vehicles on road and increasing urbanization leads to the problem of traffic congestion, which further leads to complications and hazards on the city roads. Many arterial roads in Pune city are suffering from this problem, especially during peak traffic hours. In this work, we witnessed actual traffic congestion problems. For further analysis, we conducted traffic volume survey through manual counting of vehicles and converted this data in to the PCU coefficients. After analyzing all the work, we pinned the root problem of road and proposed a solution to avoid traffic congestions.

Published by: Shriyash Bhondve, Shreyas Galagali, Chanakya Sahasrabuddhe, Akshay Gada, Tejas Aher, Khalid Shaifullah

Author: Shriyash Bhondve

Paper ID: V7I3-1917

Paper Status: published

Published: June 17, 2021

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