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Review Paper

Advancement of traditional smoke detectors to smart: A survey

This paper focuses primarily on the importance of smoke detectors that can be utilized in house, office, and shop, security gas station to detect smoke and fire. Safety becomes an important issue when fire detection is present in the home so that children and the elderly who are unable to fight fire smoke can use it. Prior research shows that are many deaths have occurred due to suffocation caused by causalities like sudden fire, circuit failure, unwanted fire hazards. A survey of various existing techniques of smoke detectors and how the techniques grew from traditional to smart, is given in this paper.

Published by: Parul Tyagi, Dilip Yadav, Mukul Dev

Author: Parul Tyagi

Paper ID: V6I3-1464

Paper Status: published

Published: June 11, 2020

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Research Paper

Non-invasive optical intravenous monitoring system

This paper emphasizes Intravenous Fluid Bottle monitoring in hospitals using an innovative non-invasive optical approach. For good patient care in hospitals, the management of fluid and electrolyte bottles is the most fundamental thing required. In all hospitals, an assistant/nurse is responsible for monitoring the bottle’s electrolyte level. But unfortunately, most of the time the observer may forget to change the bottle at the correct time due to a busy schedule which can lead to fatal conditions like air embolism due to air bubbles in IV pipe when the bottle gets empty. To overcome this critical situation, an intravenous optical sensor system is proposed to measure the liquid level from outside the bottle. The device is designed such that it can be easily replaced from one bottle to another. This device can avoid any fatal condition and ease the workload of nurses.

Published by: Abhay Sahu, Rushad Mehta

Author: Abhay Sahu

Paper ID: V6I3-1411

Paper Status: published

Published: June 11, 2020

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Research Paper

Neural Networks based image classification for animal Intrusion Detection System

Agriculture plays a major role in the development of a country. Issues concerning agribusiness have been continually thwarting the advancement of the nation. Farmers face a huge number of issues, for example, the insufficiency of water for irrigation, harm to crops because of pests and wildlife. In any case, productivity is decreased by the wild creatures trampling over harvests and eating them. This project provides a solution for these problems without hurting creatures or setting human life at stake. In this project, we use Raspberry pi to protect the farmland from animals. Classification of the intruded animals is done using the photos taken utilizing the Convolutional Neural Network. This way it is easy to arrive at useful information regarding the intrusions and take measures against it.

Published by: Sushmitha Shankar B., Vidya R., Thanushree M., K. Apoorva

Author: Sushmitha Shankar B.

Paper ID: V6I3-1486

Paper Status: published

Published: June 11, 2020

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Research Paper

Real-time facial expression recognition using CNN

Enhancing modern day machines or computers to recognize various facial expressions and to understand human emotions from them in real time is an exigent research subject. Through this paper, I put forward a solution to recognize emotions by understanding different facial expressions by collecting live video through a Flask App created. I deploy a Flask App to video stream live feed captured through the local camera attached to the machine or computer system. The video captured is fed to various image extraction techniques. The facial features are identified by different operations provided by OpenCV and the region consisting of parts of the face are made to surround or enclose by a contour. This region, enclosed by the contour is used as an input to Convolutional Neural Network (CNN). The CNN model created consists of six activation layers, of which four are convolution layers and two are fully controlled layers. Each layer is designed to undergo several training techniques. The main objective of this project is to demonstrate the accuracy of Convolutional Neural Network model designed. The paper is concluded by discussing the outcomes of our project and the ways to improve the efficiency of the model. The scope of this project is also analyzed to enhance technologies developed in the near future.

Published by: Revanth Krishna

Author: Revanth Krishna

Paper ID: V6I3-1492

Paper Status: published

Published: June 11, 2020

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Research Paper

Research paper on physical activity and fitness patterns among university students in Mumbai

Due to the increase in the workload and the observable increase in the competition amongst the youth, the health and fitness of oneself are put as a secondary priority amongst them. This research was conducted to test this very reason and to check its validity. As not many studies are carried out on targeting this specific set of the population on this subject, this research was carried out to understand the physical activity patterns among university students and their perception towards the same. Descriptive research was carried out where a cross-sectional data on physical activity levels were collected (Self-reported data). The attitudes, motivations, demotivation, food consumption patterns, and the perception of them regarding their health and fitness were collected from the respondents. A sample of 122 was used where there were 63 women and 59 men. This study gathered quantitative data through structured questionnaires to understand each of the objectives. Descriptive statistics were used to analyze data where the mean, median, mode, and standard deviation was calculated and a number of correlations were made using the same. It was found that respondents aging from 15-26 have low levels of physical activity. Moreover, when a comparison was made between males and females on their levels of physical activity, women were found to do easier levels of physical activity. The BMI was likewise determined, so as to discover the class of weights that individual’s fall into. While the vast majority expressed that practicing was imperative to them, they, despite everything neglected to work out for adequate hours per week. While individuals know and have the correct disposition towards working out, they have recently been unsuccessful when it came to really work out. At the point when it went to the reasons why individuals work out, the most well-known ones were to get fitter or more grounded or accomplish a positive inclination. Be that as it may, when it went to the demotivation of working out the most widely recognized reasons were the lack of time, energy, and inspiration to work out. Some different elements that were a consequence of individuals being overweight were their temptations/cravings to eat fast food. A greater part of the respondents said that they expended cheap food in any event 2-3 times per day. 15-26 years old have busy lifestyles and hence are much harder to reach. A targeted intervention could be carried out in order to educate people about the importance of the physical activity.

Published by: Salonee Jambusaria, Sara Berry, Shivam Bhadra, Shrutika Sanghvi

Author: Salonee Jambusaria

Paper ID: V6I3-1465

Paper Status: published

Published: June 11, 2020

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Research Paper

Intelligent surface heating using LSTM networks

Electrically heated blankets have been around the market for a long time. They are extremely handy during winters, as they can be used to warm beds. There have been many advances in the control systems to ensure that the desired temperature of the blanket is maintained. The drawback of such systems is its power consumption. Commercially available heating blankets use about 200 watts of power. On average, an adult’s body occupies only about 60 to 70 percent of the total sleeping area of a bed. Existing technologies heat the full blanket irrespective of the users sleeping position and orientation. This results in wastage of power due to inefficient heating of the blanket. In this paper, we present an intelligent heating system that uses Long Short Term Memory (LSTM) to learn the sleeping patterns of the user to predict the future position and orientation of the user to maximize its overall efficiency.

Published by: Rushad Mehta, Abhay Sahu

Author: Rushad Mehta

Paper ID: V6I3-1410

Paper Status: published

Published: June 11, 2020

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