Video Gallery

A 100% custom-built and programmed drone. The drone's chassis acts as a structural PCB integrating a Teensy 4.0, MPU6050 (IMU), and BME280 sensors. I developed the flight controller from scratch in C/C++, featuring a custom-tuned PID control loop for real-time attitude stabilization based on the Carbon Aeronautics framework.

A smart child safety bracelet using an ESP8266 to communicate with a custom Android app over a fast WebSocket server. Features real-time parent-child alerts via vibration motors, flashing LEDs, and automatic 10-second timeout notifications.

An intelligent driver safety system utilizing a Raspberry Pi 5 and Computer Vision (Dlib/OpenCV) to monitor the Eye Aspect Ratio (EAR) in real-time. Upon detecting micro-sleeps, it triggers an ESP8266 via WebSockets to activate physical alerts, automatically shift vehicle gears to Neutral, and notify emergency contacts.

Embedded system designed to automate home environments (lighting and ventilation) using DHT11 and PIR sensors. Remotely controlled via the Blynk mobile app and an ESP32 microcontroller with optimized energy consumption.

A wearable assistive device for the visually impaired. Features custom 3D-printed smart glasses and a Raspberry Pi belt unit. It performs real-time object detection using YOLO/OpenCV and streams data asynchronously via WebSockets to an Android app, providing instant Text-to-Speech audio feedback to the user.

An intelligent automated solar tracking system designed to maximize energy harvesting. Built around an Arduino Uno, it uses four Light Dependent Resistors (LDRs) positioned at the panel's edges to detect light intensity. The mechatronic system dynamically adjusts its orientation across two axes (horizontal and vertical) to continuously follow the optimal light source in real-time.

An advanced agricultural monitoring system transforming crop inspection into quantifiable data. It utilizes a HuskyLens AI vision camera to instantly classify plant health (e.g., cabbages). Powered by an ESP32 microcontroller, it wirelessly logs real-time statistics to the Blynk IoT platform, allowing farmers to track yields and intervene early against crop diseases.