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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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Research Paper

Disaster Risk Management of Higher Risk Areas on Floods and Landslides in Rwanda

Due to its topography, several areas of Rwanda are located in high-risk areas. Recently, disasters like floods and landslides have the potential to delay the economic development in terms of damaged infrastructures, displacement and loss of life of the people. In addition, climate change and increase in extreme weather patterns have also increased in recent years. According to the figures from the Ministry of Disaster Management and Refugee (MIDMAR), from January up to May 2018, over 80 people had been killed in rains that had been affecting central and Northern-Western Rwanda, while 74 others were injured. At least 28 people died from heavy rain which resulted in floods along Sebeya River and other areas where people live on steep hills were affected by landslides. Furthermore, 898 houses were also destroyed, while over 1,500 hectares of crops were damaged over the same period. Known as “the land of a thousand hills”, Rwanda is one of Africa’s most densely populated countries. Therefore, population increase has resulted in pressure on land use resulting in the construction of human settlements in areas highly susceptible to floods and landslide. In Rwanda more areas are prone to floods and landslides and this is due to various aspect such as topographic, land use type, lack of adequate information and others. Disaster risk management as a worldwide issue, knowledge of disaster-prone areas in Rwanda, can be assumed as an additional tool for detailed information acquisition, henceforth contributing to effective disaster risk management. it is in this regard that this work was conducted to provide information on disaster risk of floods and landslides and their management options in Rwanda. The result revealed that the most vulnerable areas prone to floods and landslides are located in the North-Western while floods had affected the country more than landslides.

Published by: Venuste Kabalisa, Mugisha Francis Kagambira

Author: Venuste Kabalisa

Paper ID: V7I3-1819

Paper Status: published

Published: June 17, 2021

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Research Paper

Gender difference in developing loneliness and obsession compulsion symptoms during COVID-19 pandemic

The purpose of current study was to identify the gender difference in developing loneliness and obsession compulsions symptoms during Covid-19 pandemic. Participants (N=120) including males (n=60) and females (n=60) were selected from Faisalabad city of Punjab, using purposive sampling technique. UCLA Loneliness scale version 3 (Russel, 1996) and Y-BOCS (Goodman et al., 1989 a,b) were used to measure the loneliness and obsession compulsion symptoms. For analytic purpose, independent t- sample test was applied, using Statical Package for Social Science version 26. Findings of analysis indicated that females are more prone to develop loneliness, which is indicated by t =-3.404 at p=.001< .001. Also, females developed more obsession compulsion symptoms as compared to males, which was indicated by t =-3.022 at p=.003 < .001.

Published by: Huma Javed, Adeeba Arjmand, Mahira Arshid, Summan Zahid

Author: Huma Javed

Paper ID: V7I3-1735

Paper Status: published

Published: June 17, 2021

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