Intelligently automating computing device hand gestures recognition

1. Project 1: Intelligently Automating
Computing Devices Hand Gesture
Recognition
Made by: Akshit jain, Bhavya Tewari, Bhavya Verma
Mentor: Dr. Sachin Kuumar
Semester: 6th
This project used hand gesture recognition to perform various
functionalities on a device and give the user complete automation
over the machine. The major features of the project included the
adjustment of the volume of the device, brightness of the device,
control the mouse and keyboard, use hand gestures for American
sign-language, and deliver presentations using gesture recognition.
This project through this implementation studied AI, Machine
Learning, Computer Vision, and the associated python libraries in
detail. The application incorporates various features and aspects of
Artificial Intelligence and Machine Learning. The application uses
hand gesture recognition and palm detection model.
The application has a high potential for being incorporated with
more advanced AI and ML aspects. In addition to hand gesture
recognition, the implementation of fingerprint detection and facial
recognition can help execute various new features. For example, we
can unlock the device, mute or unmute the microphone, access apps,
enable gesture recognition for various functionalities and games, and
make choices.
The methodology of this project was based on the implementation of
the following major components:
 Hand Landmark and Tracking Module.
 Volume Control Basics using Hand Gestures Recognition.

2.  Advanced Volume control using hand gesture recognition.
 Hand gesture mouse control.
Project 2: Ways to use AR
Made by: Yojit Kaushal
Mentor: Gusion Dagger
Semester: 4th
The idea behind this project was to use different SDK/Tools and
Platforms for the use of AR working on the content designing in 3D.
AR in which virtual-content is seamlessly integrated with displays
real world scenes, is a growing area of interactive design. With the
rise of personal mobile devices capable of producing interesting
augmented reality environments, the vast potential of AR has begun
to be explore.
3D computer graphics, 3D modeling is the process of developing a
mathematical representation of any surface of an object (either
inanimate or living) in three-dimension via specialized software.
The basic goals of an AR system is to enhance the user’s perception
and interaction with the real world through supplementing the real
world with 3-D virtual objects that appear to coexist in the same
space as the real world.
The major focus of the project was on augmented reality and how do
we implement it which was then infused with the technology of AR in
different industrial areas so as to see how can we leverage the power
of AR.

3. Project 3: The Role of Social Media
Campaigns in Indian Elections
Made by: Prayas jain
Mentor: Dr. Sachin Kumar
Semester: 6th
The goal for this project is to collect tweets for over a month before
the polling data for an election and analyses it through various
perspective and try to figure out some patterns. For this purpose the
tweets from January to February of 2022 regarding the Uttar Pradesh
Vidhan Sabha Election were analyzed.
So through this intensive Data analysis of ours, as part of tweets we
can say that Online Campaigns at least are slowly becoming an
integral part of Indian Elections though the same is not very true
about the online debates. Currently the social media platforms are
being used just to support and amplify the campaigns running on the
ground. Not only that, but the actual public issues are still far away
from getting from getting the space deserve in the online campaigns.
Some interesting insights also indicates the failure of which led to
the observation of negligible Anti-Incumbency. Also it was observed
that the Social Media presence is somewhere directly contributing to
the results of the elections and thus can be further studied as a
parameter to predict to predict the results. Finally we can conclude

4. that IT cells are playing a major role in the development of the
overall persona of political party.
Project 4: Stock Market Prediction
Made by: Muskan Nagi, Nandan Kumar, Piyush Kumar Arun, Pratibha
Mentor: Shobha Bagai
Semester: 6th
Over the past decades, interest in prediction of markets has
increased among the market makers. But before anyone invests in
any stocks, they need to know how the stock market works
otherwise they will gain a big loss. Prediction of the stock market is
basically based on time series. Different algorithm have been used to
predict stock prices and then their accuracy score was compared.
Long-short term memory model shows the highest accuracy of 92%
among Linear Regression, Random Forest, Support Vector Machines
and ARIMA family of techniques. A web app was built using the LSTM
model.
Different stock price prediction models have been built using Linear
Regression, Random Forest, Support Vector Machine, ARIMA (Auto-
Regression Integrated Movie Average) and LSTM (Long-Short Term
Memory) techniques. Then the accuracy scores of all algorithm have
been evaluated and it was found that that LSTM models have the
highest accuracy of 92%. We found that the LSTM model works best
with stock data of the company.

5. Project 5: Grader: Android Development
Learning App
Made by: Pintu, Sai Yash, Siddharth, Vipul
Semester:
Mentor: Dr. Sachin Kumar
Summary: In the project, the aim was to create an Android learning app
named GRADER. In the app, the users could attempt mock tests of various
subjects provided in the app. Every subject contained tests and practice
questions which have to be answered/solved within a limited amount of
time .the users could also check their performance later on, bookmark
questions while solving them, and could also check the correct answers
after completing their tests. The app included the following features:
Register/Login, My Profile (User Profile), Attempt test functionality,
bookmark, Re-attempt, view answers, Scorecard, and Leader board. The
images of these functions were given inthe poster. In the modern world of
mobile phones, technology and their increasing availability and
affordability, mobile devices, particularly Android platforms play an
important role in the field of communication, entertainment and learning.
Mobile learning is the product of mobile computing and E-learning
providing resources that can be accessed anywhere. The technology used
in while developing the app included: Java SE, XML, Android SDK, Firebase,
Android Studio, and Canva. Future plans included to increase the admin
functionality, including video lectures and live classes, providing a complete
performance report, adding AI and Machine learning