Published:
I captained a team of four Mechatronics Engineering undergraduate colleagues to build a single-axis solar tracker system that maximizes solar energy generation, leveraging Arduino and accessible electronic components. This was a class project.
Published:
I captained a team of four Mechatronics Engineering undergraduate colleagues to build a single-axis solar tracker system that maximizes solar energy generation, leveraging Arduino and accessible electronic components. This was a class project.
Published:
Trained a neural model to identify and classify simple fruits in the immediate environment. 90% training performance and 84.62% real-world success rate. This was a class Project.
Published:
I collaborated with AFEME students to assemble a tele-operated bot using ESP32 CAM, Arduino Uno, L298n motor driver, Lipo batteries, and DC motors. Programmed the bot’s functionality in C++ via Arduino IDE, with Firebase for real-time communication and React.js for a user-friendly software interface.
Published:
I collaborated with AFEME students to assemble a tele-operated bot using ESP32 CAM, Arduino Uno, L298n motor driver, Lipo batteries, and DC motors. Programmed the bot’s functionality in C++ via Arduino IDE, with Firebase for real-time communication and React.js for a user-friendly software interface.
Published:
I captained a team of four Mechatronics Engineering undergraduate colleagues to build a single-axis solar tracker system that maximizes solar energy generation, leveraging Arduino and accessible electronic components. This was a class project.
Published:
I captained a team of four Mechatronics Engineering undergraduate colleagues to build a single-axis solar tracker system that maximizes solar energy generation, leveraging Arduino and accessible electronic components. This was a class project.
Published:
Trained a neural model to identify and classify simple fruits in the immediate environment. 90% training performance and 84.62% real-world success rate. This was a class Project.
Published:
Trained a neural model to identify and classify simple fruits in the immediate environment. 90% training performance and 84.62% real-world success rate. This was a class Project.
Published:
I collaborated with AFEME students to assemble a tele-operated bot using ESP32 CAM, Arduino Uno, L298n motor driver, Lipo batteries, and DC motors. Programmed the bot’s functionality in C++ via Arduino IDE, with Firebase for real-time communication and React.js for a user-friendly software interface.
Published:
I captained a team of four Mechatronics Engineering undergraduate colleagues to build a single-axis solar tracker system that maximizes solar energy generation, leveraging Arduino and accessible electronic components. This was a class project.