Projects
SMART WATER IRRIGATION SYSTEM [Mar'21-May’21]
Developed a functional model of a smart irrigation system designed to automatically water plants. This system utilizes the ESP8266 microcontroller, which is controlled via the internet. The core component of this setup is a soil moisture sensor that monitors the moisture level of the soil in real-time. When the sensor detects that the soil is too dry, it triggers a DC motor and an electric check valve to release water to the plants. This automated process ensures that plants receive the right amount of water as needed, optimizing water usage and promoting healthier plant growth.
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Patent application filled E-12/8001/2023/DEL [ ID P00000319 ]
Platform used: Arduino IDE (C/C++)
Embedded tool: Node MCU ESP8266 Wi-Fi module
Skills: IoT, Timer interrupt, Programming(C/C++)
OBJECT DETECTION USING OPEN-CV [Jan’22- Mar'22]
Approached the challenge of object detection and human face recognition by implementing a comprehensive solution that involved designing our own cascade classifiers. This approach utilizes the power of machine learning and artificial intelligence to achieve accurate and efficient detection. By leveraging these advanced technologies, we were able to optimize our datasets seamlessly, enhancing the overall performance and accuracy of the detection system. This solution not only improved the recognition capabilities but also ensured a more streamlined and effective process for handling and processing large volumes of data.
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Platform used: VS code.
Skills: Open cv (Python),Linux,(DBMS),AI-ML
LED BLINKING USING SOUND SENSOR [Dec'22]
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This is a fun project which is worked on principle of Analog to Digital converter and it is design using an arduino module to control an LED based on input from a sound sensor having in-built capacitive microphone, peak detector and an amplifier (LM386, LM393). The sound sensor captures audio signals and converts them into an electrical signal, which is then fed into the Arduino microcontroller. The Arduino processes this signal to determine the presence and intensity of the sound. In response, it controls the LED to blink in sync with the detected sound. This setup provides a visual indication of audio cues and can be used for applications such as alerts, signaling, or interactive displays.
DESIGN A DRONE USING TEENSY 4.0
MICRO CONTROLLERS [Aug’22-Dec'23]
Designed a drone prototype aimed at providing hands-on learning in various fields including mechanical design, electronics, and software development. This project offered comprehensive exposure to prototyping, coding, and sensor integration. The drone's balance and stability were achieved through a PID control system by desiging a closed loop system with feedback response, implemented using machine learning techniques on the Teensy 4.0 microcontroller. Additionally, we used the MPU-6050 calibration sensor to fine-tune the drone's performance, ensuring precise control and responsiveness. This project not only enhanced our understanding of drone technology but also provided valuable practical experience in integrating complex systems.​
Platform used: Arduino IDE.
Skills: Embedded C, Control System, PID.
DESIGN DIFFERENT TYPES OF ANTENNAS USING CST SOFTWARE [Jan’23-April '23]
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Using CST (Computer Simulation Technology) software, we undertook a project to design various types of antennas and created 3D models of antennas, setting up simulation parameters, defining material properties, and specifying the frequency range, analyze each antenna's performance.The simulations provided detailed data on radiation patterns, gain, directivity,input impedance, and bandwidth. By analyzing these results, we optimized the designs to meet specific requirements and improve efficiency.This project enhanced our understanding of different types of antennas and their applications and also provides valuable hands-on experience in using CST studio software electromagnetic simulation and offering insights into practical challenges in diffrents types of antenna design.
PN Junction Fabrication [Feb'23-March23]
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we perform PN junction fabrication as part of our semiconductor technology coursework.
The process involves several key steps:
1.Material Preparation: We start with high-purity silicon wafers, which are thoroughly cleaned and polished to prepare them for the fabrication process.
2.Doping: We introduce specific impurities into the silicon wafer to create p-type and n-type regions.This is done using techniques such as diffusion or ion implantation. For p-type doping, we use elements like boron, while for n-type doping, elements like phosphorus or arsenic are used.
3.Photolithography: We apply a photoresist layer to the wafer and use photolithography to define the areas for doping. This involves exposing the photoresist to light through a mask, then developing the resist to create a pattern.
4.Etching: After photolithography, we use etching to remove the unwanted material, exposing the areas where doping will occur.
5.Diffusion or Ion Implantation: We then proceed with diffusion or ion implantation to introduce dopants into the exposed regions of the wafer.
6.Annealing: The wafer undergoes annealing to activate the dopants and repair any damage caused during the implantation process.
7.Metallization: We deposit metal layers onto the wafer to form electrical contacts. This is done using techniques like evaporation or sputtering, followed by patterning and etching.
8.Testing and Packaging: Finally, we test the fabricated PN junctions for their electrical properties and performance. Successful devices are then cut from the wafer, packaged, and prepared for further use.
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This hands-on experience in the laboratory helps us understand the principles and techniques involved in semiconductor fabrication and the creation of functional PN junctions.
Design various types of FSM [Sep'23-Nov'23]
I have designed various types of Finite State Machines (FSM), including overlapping and non-overlapping FSMs, which are essential for managing different operational states and transitions in digital systems. Utilizing these FSM designs, I developed a basic washing machine controller that handles sequential operations such as filling, washing, draining, rinsing, and spinning. Additionally, I designed a traffic light controller that efficiently manages traffic signals, ensuring safe and orderly traffic flow at intersections
SOFTWARE SIMULATION OF OBSTACLE AVOIDING SELF-DRIVING ROBOT [Aug’23-Nov '23]
We implemented a software solution incorporating decision-making algorithms to enable obstacle avoidance and autonomous path creation, ensuring the completion of its destination. The core component of this project is the Rapidly-exploring Random Tree (RRT) algorithm, which is specifically designed for efficient path planning in complex environments.
Our solution begins with the software analyzing the environment to identify obstacles and free spaces. Using the RRT algorithm, the system generates a tree of possible paths from the starting point to the destination. The RRT algorithm incrementally builds this tree by randomly sampling points in the space, connecting them to the nearest existing nodes while avoiding obstacles. This approach allows the algorithm to quickly explore large, high-dimensional spaces and find a feasible path as shown in the video.
The decision-making algorithms are integrated into this framework to dynamically update the path in real-time.
