Hi, I'm Jigme Nidup

The Fab Lab Inventory System is a comprehensive, full-stack web application built to solve inventory management challenges in makerspaces, fabrication labs, and educational workshops.

This is an innovation week hackathon project at Vellore Institute of Technology where we identify various plant disease by sending the leaf image to a CNN model trained in various plant disease images. It gives us the disease name, cause of disease and how to treat it in multiple languages.

A decentralized application (DApp) for storing and visualizing IoT sensor data on the Sui blockchain. This project combines a Next.js frontend with a Move smart contract and supports three ESP32 integration approaches: on-device transaction building (advanced), offline signing (production), and server-side signing (development).

Here we are using DHT11 to sense temperature and humidity values from the environment. The data is then displayed on a 128x64 OLED using STM32F103C8T6. We are also using custom icons for weather to be displayed on the OLED.

In this project we are going to use the ESP32 CAM and RFID rc522 Module to authenticate a user by their RFID tag and Face. This project involves using a python web server that takes in the base64 image data from esp32 cam and identifies the user using open cv face recognition.

Smart Dashboard System using ESP32 microcontrollers, designed to monitor and control environmental parameters in indoor spaces. The system comprises two ESP32 boards: one for sensing data and another for displaying the readings. The sensing microcontroller has various sensors, including the DHT11 for temperature and humidity, MQ135 for air quality, and MQ9 for CO2 levels. Additionally, a buzzer is used to signal changes and assist in light control. Data from these sensors is transmitted over Wi-Fi via the MQTT protocol to a cloud service, where it is processed and shared with the display module.