BHAVNEET KAUR
Bachelor of Engineering (Honours) in Computer Engineering, York University
I’m a dedicated Computer Engineering graduate from York University, With a strong foundation in software development, hardware systems, and embedded design, I aim to create user-centric solutions that make technology more accessible and meaningful.
My experience spans across C++, Python, Java, and Verilog HDL, along with practical work in embedded systems, AI-based automation, and digital logic design. Through academic and personal projects, I’ve developed a deep interest in integrating AI and IoT technologies to build efficient, real-world systems.
Beyond academics, I value creativity, teamwork, and continuous learning. I enjoy contributing to community initiatives and exploring opportunities that challenge me to grow both as an engineer and as a problem-solver.
Projects
1
York University Parking System
Designed and implemented an end-to-end Java-based Smart Parking Management System that automates parking space allocation, booking validation, and payment processing through a modular GUI-driven application. The system was architected following Object-Oriented Design (OOD) principles and integrated multiple Software Design Patterns(Singleton, Composite, Factory, Observer, and Prototype) to ensure scalability, modularity, and maintainability
2
Bluetooth Controlled Car Using Arduino UNO & HC-05
Designed and built a Bluetooth-controlled robotic car using Arduino Uno, HC-05 Bluetooth module, and an L298N motor driver to enable wireless movement through smartphone commands. The system processes directional input via UART serial communication and drives DC motors for forward, reverse, and turning actions. Implemented embedded C++ logic for real-time command execution, improving control precision and response time.
3
Morse Code Translator (FPGA-Based Digital System)
This project involved designing and implementing a Morse Code Display System on the Intel DE10-Lite FPGA board, written entirely in Verilog HDL.
The system converts English alphabets (A–Z) into their Morse-code equivalents, then visualizes and transmits them through both visual (LED blinking) and auditory feedback (mechanical relay clicks). The FPGA receives alphabetic input through onboard switches, encodes the signal using lookup logic, and generates precisely timed pulse sequencesrepresenting dots and dashes.
4
C4 Housing Website
(AI Chatbot)
Developed a full-scale digital housing platform in partnership with ENGAGE Toronto to help low-income residents access affordable, accessible, and sustainable housing. The website centralizes verified housing listings, financial aid resources, upcoming developments, and community forums. It features tools like filterable listings, affordability maps, financing guides, and an AI chatbot for real-time support all built to reduce digital barriers and empower users to make informed housing decisions.
Focused on inclusivity, ethics, and real-world social impact through technology.
5
Self-Watering Plant System
Created an automated irrigation setup using Arduino UNO, soil-moisture sensor, relay, and water pump programmed in C/C++ to water only when soil is dry and stops at optimal moisture.
In this system, soil moisture sensor senses the moisture level of the soil. If soil will get dry then sensor senses low moisture level and automatically switches on the water pump to supply water to the plant. As plant gets sufficient water and soil get wet then sensor senses enough moisture in soil. After which the water pump will automatically get stopped.
6
ArUco-Based Robotic Arm Tracking System
This project involved developing a vision-guided robotic arm system capable of detecting and tracking ArUco fiducial markers in real time for use in anti-explosive scanning and automated inspection scenarios. The robotic arm, powered by a Raspberry Pi 4 and a PCA9685 servo controller, combines computer vision, embedded control, and IoT integration to identify hazardous zones, scan vehicles, and autonomously align to targets while minimizing human exposure to potential threats.
The system was implemented using Python 3, OpenCV, Flask, and PyGame, integrating a camera feedback loop, servo motion control, and data logging through a web interface. This cyber-physical system embodies the fusion of embedded hardware, real-time image processing, and networked robotics, designed to assist in secure border or checkpoint inspections.
7
Heartbeat Sensor Circuit using LM358, IR Sensors
This project involved designing and building an analog heart-rate detection circuit that uses infrared light reflection and signal amplification to measure a person’s pulse. When a finger is placed near the IR sensor, variations in blood flow modulate the reflected light intensity. These variations are converted into voltage signals, amplified using an LM358 dual-stage operational amplifier, and then visualized on an oscilloscope while driving an LED that blinks in sync with the heartbeat.