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Research Paper

Reimagining the city’s identity by strengthening the inner core – A research enquiry for design intervention

A city is its’ past legacy and its present identity. While each city must strive to keep marching forward and upgrade to suit the latest demands of its’ residents, it is important to strike a balance between the past and the present. Flowing towards future ambitions as an urban setting doesn’t necessarily imply a disconnect from its past legacy. The legacy lends the city's identity and gives the citizens a sense of familiarity. Therefore, modern urban planning must not only work towards embracing transition and change of modernity but also strike a balanced relationship between the urban and natural environment. This all-inclusive approach is the soul and crux of cultural heritage management as well. As modernization, commercialization, and urbanization continue to threaten a multitude of historical precincts and buildings, recording and celebrating their existence, acknowledging their contribution to national identity, preserving their associations with the city’s identity today, and protecting them from extinction becomes chiefly important, the corresponding benefit of which is promoting tourism as well. The heritage precincts of Aurangabad city encompass areas surrounding the multitude of the city’s gates of historical significance.

Published by: Kapil Gujarathi, Kuldeep Bhatia, Tushar Paithankar

Author: Kapil Gujarathi

Paper ID: V7I4-1153

Paper Status: published

Published: July 2, 2021

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Research Paper

Driver Fatigue Detection using Deep Learning

Fatigued driving is becoming a dangerous and widespread occurrence for drivers, and it is a key contributor to deadly car accidents. To detect tiredness in drivers, machine learning researchers used a variety of sources of data. The morphological features of both the eye and mouth regions were combined in this work, which looked at the fatigue detection problem in terms of feature quantities, classifiers, and modelling parameters. This particular YOLO model is trained to detect two classes. They are “eyes_open” and “eyes_closed”. As soon as the model detects that a person is closing his/her eyes it rings an alarm to alert the driver and passengers.

Published by: Sujay S., Aditya Ashok Illur, Poornima Kulkarni, Rekha B. S.

Author: Sujay S.

Paper ID: V7I4-1151

Paper Status: published

Published: July 2, 2021

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Research Paper

Automatic number plate recognition using contours and Convolution Neural Networks

Image processing technology is used in Automatic Number Plate Recognition (ANPR). Automatic Number Plate Recognition (ANPR) is useful for identifying stolen vehicles, smart parking systems, and the use of automobiles in unlawful operations. Character recognition is the first step of ANPR, followed by character segmentation and localization. The technique uses contours and morphological processes to locate the number plate initially. We execute character segmentation after localization. Convolution neural networks (CNN) are used by a segmented character to recognize things because they are known to be good at it. The trained CNN model has an 85.31% accuracy rate.

Published by: Adithya M., Sumitha B. S., Rahul K., Nitish Kumar P., Pramod G. N.

Author: Adithya M.

Paper ID: V7I4-1139

Paper Status: published

Published: July 2, 2021

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Research Paper

A Study to Investigate the security issues in IMD

With the ever-growing rise in smart devices and their applications in most sectors, there is a need for security as the information is transmitted using a wireless medium of transmission. One of the most profound health care devices is the implantable medical devices used for monitoring and control of vital organs such as neural systems, heart, and cochlear implants. Although IMDs provide quick and cost-effective diagnostic features to the patients there exist some design constraints and software threats that need attention. There is a chance of leakage of confidential data pertaining to the person with IMD by attackers, thereby manipulating the parameters of the devices causing the patient’s life to be at high risk. In our paper, the different types of IMDs and their constraints are addressed. As the emphasis is on the security aspects of these devices, their requirements, the attack vectors, the type of attacks encountered, and the protection mechanisms implemented to date are also discussed.

Published by: Sahana, Sindhu Rajendran, Vibha Narayan R., Rahul Pinny

Author: Sahana

Paper ID: V7I3-2210

Paper Status: published

Published: July 2, 2021

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Research Paper

Highway navigation system using light fidelity technology

This study shows how Li-Fi technology can be used to create a smart highway navigation system. Light fidelity technology is a type of visible light communication that employs light as a medium to transmit high-speed data at a rate far faster than Wi-Fi. Here, the proposed prototype is tested using PROTEUS 8 professional software to see what potential there is for employing LiFi in highway routing. Atmega328 is used in the transmitter and receiver portions, and it is programmed using the Arduino IDE. The transmitter component uses high-intensity LEDs to convey high-speed data to moving cars. The LDR module is also utilized in the receiver section to detect the signal generated by the LEDs. On the receiver's LCD, information about the current location and future diversions is presented based on the received signal. As a result, this technology is better suited to automatic navigation on motorways and wide roads.

Published by: Pramod B. N., Sumitha B. S., Pavan Angadi, Nitish Nishant, Manu S.

Author: Pramod B. N.

Paper ID: V7I3-2234

Paper Status: published

Published: July 1, 2021

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Research Paper

Face mask detection system

Face masks have become an increasingly important part of the human lifestyle. Ever since the pandemic began, people have been encouraged to wear face masks to curb the spread of Covid-19. The aim of this project is to replicate on a computer what human beings are able to do so effortlessly - detect the presence of faces in their field of vision. This project aims at using a camera placed in different places around the area, to capture images and detect the presence of a facemask in real-time. The proposed Face Detection System is an application that automates the detection of frontal human faces in a given image. The existence of a mask is indicated by a green square around the person’s face along with the percentage of accuracy of the positioning of the mask. The absence of the mask, however, is indicated by a red square around the person’s face, and its related percentage is also displayed to be accurately used for detecting whether a person is wearing a mask properly or not.

Published by: Korakam Mrudula, M. Sion Kumari, Landa Jayashree, Madala Meghana, Meesala Gnana Deepika

Author: Korakam Mrudula

Paper ID: V7I4-1137

Paper Status: published

Published: July 1, 2021

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