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Review Paper

Wireless smart helmet with sensors for accident detection

In Countries like India, the major challenge is safety for two-wheeler riders. The rapid growth of two-wheeler vehicle road accidents is evident. According to a report by the National Crime Records Bureau (NCRB) In India, almost 2 lakh people die annually due to two-wheeler accidents. The government is forcing drivers to wear a helmet during driving but many of the riders are not following the rules. We would like to help society through our project, we would try to reduce the probability of deaths caused by two-wheeler vehicle accidents. In this project, we are introducing a Wireless smart helmet system that detects a person is wearing a helmet or not, and also the system can detect whether the person is drunk, here we have a Bluetooth transmitter in the helmet and a Bluetooth receiver at the bike. Two pushbuttons will be there to check whether the person is wearing the helmet or not. And an alcohol sensor is placed inside the helmet near the mouth of the rider to see whether the rider is drunk. If the accident takes place location of the accident will be sent to the predefined emergency contacts and there will be a buzzer sound and flashlight to grab attention so that the person gets immediate help. There is also another feature posture correction using haptic feedback which helps maintain the good posture of the rider. In this system, there is a switch that ensures the placing of the helmet properly. The conclusion of this paper is to prevent the accident while driving in the vehicle.

Published by: Shreaya S., Soumya C S, Shruthi Sha S

Author: Shreaya S.

Paper ID: V7I2-1220

Paper Status: published

Published: March 22, 2021

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Research Paper

Smart sanitation system

According to India Today, 80% of 1.5lakh metric ton daily garbage remains exposed which can cause cholera, dysentery, typhoid, etc. Unhygienic toilets can result in urinary tract infections, hepatitis, E.coli, etc. Proper sanitation and timely maintenance are necessary to bring this number under control. While awareness is an important tool in India, we also need to start developing sustainable models of greener and smarter cities that use analytical solutions to solve problems faced by millions of people universally. When it comes to building smart cities for a greener tomorrow, proper sanitation, clean toilets, and efficient waste monitoring systems play an important role. Therefore to overcome the challenges faced in developing a better sanitation system, the proposed solution explores, primarily developing sensor-enabled solutions to improve waste monitoring and toilet sanitation across cities.

Published by: Vaibhavsingh Rajput, Manisha Chottopadhyay, Mitali Jadhaw, Devesh Sawant, Atharva Gupte

Author: Vaibhavsingh Rajput

Paper ID: V7I2-1229

Paper Status: published

Published: March 22, 2021

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Review Paper

A survey, novel approach to detect Alzheimer’s disease at an early stage

Alzheimer's disease is one of the most common neurodegenerative disorders that predominantly affect memory. This happens when neurons lose their structure and function over time. Since there is currently no cure for Alzheimer's disease, it is important to identify the disease early and to slow its development as much as possible. Various computational approaches have been used in various studies to diagnose Alzheimer's disease. The main purpose of this paper is to analyze feature extraction and classification algorithms in order to determine the best method for diagnosing Alzheimer's disease. The following sections make up this paper: (i) a brief overview of the disease and the case; and (ii) a study of feature extraction and classification algorithms

Published by: Jovita Lasrado, Preetham Wilson Noronha

Author: Jovita Lasrado

Paper ID: V7I2-1209

Paper Status: published

Published: March 18, 2021

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Research Paper

A model to predict Covid-19 epidemics with application to India, China and Pakistan

In this work, our group builds up a differential conditions model of Coronavirus pandemics. We will probably anticipate forward in time the future number of cases from early detailed case information in areas all through the world. Our model consolidates the accompanying significant components of Coronavirus pandemics: (1) the quantity of asymptomatic irresistible people (with exceptionally gentle or no indications), (2) the quantity of suggestive announced irresistible people (with extreme side effects) and (3) the quantity of indicative unreported irresistible people (with less serious manifestations). We apply our model to Coronavirus plagues in India, China and Pakistan.

Published by: K. Ajithkumar, V. Mahendran

Author: K. Ajithkumar

Paper ID: V7I2-1213

Paper Status: published

Published: March 18, 2021

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Others

LISA (a web-based chat-bot for college website)

A chatbot is a piece of software that conducts a conversation via auditory or textual methods. Such programs are often designed to convincingly simulate how a human would behave as a conversational partner. A chatbot for a website is a chatbot that lives on your website LISA(LICET Interaction Service Assistant) is a web chatbot that helps the viewers or the users of the official website easily be able to access the information from the website that is difficult to reach. LISA is an emotionally intelligent chatbot that identifies the user’s vague request and scores with positive and negative intents.

Published by: Jaime Durga A., Abisheka A.

Author: Jaime Durga A.

Paper ID: V7I2-1205

Paper Status: published

Published: March 17, 2021

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Research Paper

Face Identification and Liveness Detection using CNN for Automated Attendance System

A real-time automated attendance system is designed using the method of live face detection and recognition. The system supports multi-user attendance and face liveness detection at the same time. The system can automatically collect face data, that will be saved in the specified dataset folder of each individual person obtained during the registration process. The face detection part of the system is based on Haar Cascade Classifier, and the face recognition part is based on the Local Binary Pattern Histogram algorithm. The algorithm implementation is based on Keras and TensorFlow framework, and the face liveness detection part is based on CNN that creates a 3D model of face detected to differentiate between real and fake images. The attendance system is written in Python language, and the user interface is designed by pywebview library. The experimental results show that the system achieves a good performance in real-time face recognition.

Published by: S. Boobathi Raj, K. Tamilselvi, S. Adharsh, S. Mohamed Javith

Author: S. Boobathi Raj

Paper ID: V7I2-1204

Paper Status: published

Published: March 17, 2021

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