BALARITHIK REDDY GADE

worked together on an IoT-enabled smart home automation project that employed sensors and gadgets to detect incidents (including gas leaks, fires, and intrusions) in real time.

created a system architecture that combines motion, environmental, and ESP32 microcontroller sensors (DHT11, MQ2, and PIR) to collect and transmit data in real time.

analyzed sensor data and used machine learning models (such as logistic regression and decision trees) to accurately identify anomalous behavior.

used scikit-learn and Python to train prediction models, identify features.

Tools & Technologies Used IoT Platforms: NodeMCU, ESP32, and Arduino IDE
Sensors: MQ2, PIR, and DHT11
Languages: C++ (Arduino) and Python
Libraries: Matplotlib, NumPy, and scikit-learn
Communication: HTTP and MQTT
Visualization: ThingSpeak, Blynk