Analyze and Predict Temperature & Humidity

This project focuses on collecting environmental data, analyzing trends, and predicting future temperature and humidity values.

Arduino App (click here)

+) Designed and implemented an embedded IoT system using ESP32 and DHT11 sensor

+) Programmed in Arduino C++ to acquire and process real-time environmental data

+) Integrated SSD1306 OLED display via I2C to visualize temperature and humidity

+) Developed control logic to trigger LED indicators based on temperature thresholds

+) Debugged hardware/software integration including wiring, sensor calibration, and serial communication

VS Code App (click here)

+) Engineered a real-time embedded system integrating ESP32 and environmental sensors for continuous data acquisition

+) Developed a cross-platform data pipeline (ESP32 → Python) for live sensor streaming and analysis

+) Performed data preprocessing and filtering to enhance signal quality and reliability

+) Designed interactive visualization tools for real-time monitoring of temperature and humidity trends

+)Built and evaluated a machine learning model (linear regression) for predictive analysis of environmental data