General Task Report

14 / 9 / 2025

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Level 0 Report - Sevanthi B R

TASK 2 : API

An API (Application Programming Interface) is a set of rules and protocols that allow different software applications to communicate with each other. It acts as a bridge between a client and a server.

For this project, I used the OpenWeather API to build a simple Weather Web App. It works by taking a city name from the user, calling the OpenWeather API to fetch real-time weather data, and displaying it on the webpage.

TASK 3: WORKING WITH GITHUB

I familiarized myself with GitHub by learning how to create branches, commit changes, and raise pull requests. I started by creating a new branch from the main repository, then made corrections to the add() function in VS Code. After staging and committing the changes, I pushed the branch to GitHub and finally compared it with the main branch to create a pull request.

TASK 4: GET FAMILIAR WITH THE COMMAND LINES ON UBUNTU

I started the task by creating a folder named test and adding a blank file inside it. I then listed its contents and went on to generate about 2,600 subfolders within the same directory.

In addition, I created two text files with random content, concatenated them, and displayed the combined output on the terminal.

TASK 5: LINEAR REGRESSION FROM SCRATCH

Linear Regression is a fundamental supervised learning algorithm used to model the relationship between a dependent variable (target) and one or more independent variables (predictors). It assumes a linear relationship between the input and output, meaning the output changes at a constant rate as the input changes.

Key Concepts

• Best-Fit Line: In simple linear regression, the best-fit line is represented by the equation:

  y = mx + b

  Where:

  • y is the predicted value (dependent variable)
  • x is the input (independent variable)
  • m is the slope of the line
  • b is the intercept

  The goal is to find m and b that minimize the error between the observed data points and the predicted values.

• Least Squares Method: This method minimizes the sum of squared differences between the actual values and the predicted values, called residuals:

$$ \text{Residual} = y_{i} - \hat{y}_{i} $$

Where:

• $y_i$ is the actual observed value
• $\hat{y}_i$ is the predicted value from the line for that $x_i$

TASK 6: THE MATRIX PUZZLE

In this task, I worked with a scrambled matrix stored in a .npy file. I started by loading the data and reshaped it into a 2D array since the total number of elements formed a perfect square. I experimented with various transformations, including flips, rotations, and transpose. Finally, applying the transpose operation revealed the correct image, which turned out to be a smiley face.

Matrix Puzzle

TASK 7: CREATE A PORTFOLIO WEBSITE

I made a personal portfolio website using HTML and CSS.

Link to my code

Link to my website

TASK 8: RESOURCE ARTICLE USING MARKDOWN

Markdown is an easy-to-use markup language that is used with plain text to add formatting elements like headings, bulleted lists, URLs to plain text without the use of a formal text editor or the use of HTML tags. I have written an article on "Deep Sea Exploration"

Link to my article

TASK 9 : TINKERCAD

I built a small radar system using a servo motor and an ultrasonic sensor. The servo moves the sensor left and right while the sensor measures how far away objects are. The Arduino then shows the angle and distance on the Serial Monitor, which helps map out where obstacles are.

TASK 10: SPEED CONTROL OF DC MOTOR

I learned how to control a DC motor using an Arduino and the L298N motor driver. I used a potentiometer to change the motor’s speed and a push button to change its direction, which helped me understand motor control better.

TASK 12: SOLDERING PRE-REQUISITES

Soldering is a process that uses a heated metal alloy (solder) to join two or more metal components, such as wires or electronic parts, together to form a permanent electrical connection.

TASK 13: 555 ASTABLE MULTIVIBRATOR

Components used:

• 555 IC Timer
• Capacitors (C1 & C2 - 0.1μF )
• Resistors (R1=5kΩ(parallel) & R2=10kΩ)
• VRPS (5V)
• Oscilloscope

I built the circuit and checked the output using Oscilloscope . The observed duty cycle was 59.47 % .

TASK 14: KARNAUGH MAPS AND DREIVING LOGIC CIRCUITS

Burglar Alarm using K-map

I first used a truth table to list all the possible input combinations and identify when the alarm should go off. Then, I used a Karnaugh Map (K-map) to simplify the logic, which helped me design the final logic circuit for the alarm. Finally, I tested the circuit to make sure the alarm only activated for the correct cases.

TASK 15: ACTIVE PARTICIPATION

I participated in the CodeFury 8.0 hackathon conducted by IEEE UVCE Computer Society.

TASK 16: DATASHEETS REPORT WRITING

I read about the MQ135 gas sensor, its working, specifications, and calibration and wrote a short note on it along with the Freundlich adsorption isotherm.

MQ135 Gas Sensor

Introduction

The MQ135 is a semiconductor gas sensor used in air-quality monitoring.
It detects gases like NH₃, CO₂, Benzene, Alcohol,and smoke, making it popular in indoor monitoring and pollution detection.

Key Specifications

• Operating voltage: 5V DC
• Detection range: 10 to 1000 ppm for various gases
• Output types: Analog and digital
• Preheat time: 2 to 5 minutes for stable readings
• Sensitivity: Adjustable via the onboard parameter

Pins: VCC (5V), GND, A0 (Analog), D0 (Digital threshold output).

Calibration

Calibration involves:

• Measuring baseline resistance (Ro)in clean air.
• Comparing Rs/Ro at known gas concentrations (from datasheet curves).

Typical ranges:

• NH₃: 10–300 ppm
• CO₂: 350–10000 ppm
• Benzene/Alcohol: 10–300 ppm

Freundlich Adsorption Isotherm

Equation:

x/m = k · C^(1/n)

Where:

• x/m → amount of gas adsorbed per unit mass of the adsorbent (adsorption capacity)
• C → concentration of the gas (or solute)
• k, n → constants that depend on the nature of the adsorbent, gas, and temperature

Logarithmic form:

log(x/m) = log k + (1/n) log C

This equation is of the form: y = mx + c

A straight line when plotted between log(x/m) and log(C).

Conclusion

The MQ135 is a low-cost, versatile sensor for detecting multiple gases.
With proper calibration (using datasheet curves + adsorption models), it is widely used in environmental monitoring and research.

TASK 17: INTRODUCTION TO VR

INTRODUCTION TO VR

Virtual Reality (VR) is a computer-generated simulation that immerses users in a three-dimensional, interactive environment that feels real. Using specialized devices like VR headsets, gloves, or motion controllers, users can see, hear, and even interact with virtual objects as if they were physically present in that environment. Unlike traditional screens, VR surrounds the user’s senses, creating a sense of presence that allows for realistic experiences .

DIFFERENCES BETWEEN VR AND AR

Environment: VR creates a fully virtual world that replaces reality, while AR adds digital elements to the real-world environment.

Devices: VR typically requires headsets and sometimes controllers, whereas AR can work with smartphones or tablets.

Immersion: VR offers complete immersion, blocking out the physical world, while AR allows users to stay aware of their surroundings.

User Experience: VR transports users into a different environment, while AR enhances the real-world experience by overlaying useful digital information.

TRENDS

Standalone & Wireless Headsets – VR devices are moving away from cables and PCs, becoming lightweight, self-contained, and more accessible.

Mixed Reality (MR) Integration – Headsets now combine VR with AR features, allowing users to switch between full immersion and real-world overlays.

AI-Enhanced VR – Artificial Intelligence is being used to generate environments, adapt experiences, and personalize training or gaming scenarios.

Healthcare & Education Applications – VR is expanding into therapy, rehabilitation, medical simulations, and immersive classroom learning.

Improved Immersion & Haptics – Advances in graphics, sound, and tactile feedback are making VR experiences more realistic and interactive.

TECHNOLOGY STACK

The VR technology stack combines hardware and software to create immersive experiences. Hardware includes headsets, motion controllers, sensors, haptic devices, and powerful GPUs for rendering. On the software side, engines like Unity and Unreal Engine build 3D environments, while SDKs and frameworks such as OpenXR and SteamVR ensure device compatibility. New XR operating systems, AI-driven content, and cloud/5G support are also being developed to make VR more realistic, responsive, and widely accessible.

INDIAN COMPANIES

Tata Elxsi – Provides AR/VR solutions for industries like automotive, healthcare, and retail, including training and product design.

Simulanis Solutions – Specializes in VR/AR-based education and training platforms for manufacturing and pharma.

SmartVizX – Focused on VR solutions for real estate and architecture, offering virtual walkthroughs and visualizations.

Jio (Tesseract) – Developing mixed reality hardware such as Jio Glass and immersive communication/learning platforms.

TASK 18: SAD SERVERS

I used Linux commands to solve the "Command Line Murders" puzzle. It was a fun experience finding clues and solving the mystery to make the server happy. I used two clues and found the culprit. Upon finding the correct solution, I received a confirmation message, successfully completing the task.

TASK 20: NOTEBOOK NINJA

In this task, I learned how to structure a professional and readable Jupyter Notebook by organizing my work with titles, headers, bullet lists, styled text, images, and embedded code snippets using Markdown. I practiced Markdown basics for data storytelling and used them to make the notebook visually clear and engaging. On the coding side, I declared variables, performed a simple calculation and created a simple Matplotlib plot. Overall, this exercise helped me build confidence in presenting my work neatly, develop the habit of documenting my thought process clearly, and gain experience in blending narrative with technical content in a structured way.

Link to notebook

TASK 21: INTRO TO MACHINE LEARNING

Link to my report