The project builds a physical IoT device using an ESP32-CAM module to photograph analog meters and run a neural network model directly on the edge hardware to recognize digit readings. The system captures images, classifies digits via a trained CNN model compiled for the embedded platform, and publishes the digitized values to a smart home or logging system. Configuration and data visualization are provided via a web interface running on the device.