Week planned work hours: 68.25 (16.9 as Risk Response)
Week total worked hours: 58.5
Hour balance: Ahead by 3 hours

Programming Languages

Embedded systems (ESP32 and ESPCAM): C++

Backend: Python (Flask)

Machine Learning: Python (YOLO)

Communication: UART and Wi-Fi

Application

The application server will be split into two threads. One thread will function as a server, handling image capture from the ESPcam and the ML service, while the other will act as a client, receiving data from the ESP32, displaying it on the web interface, and sending commands from the interface back to the ESP32. Each thread will communicate with its respective components over Wi-Fi.

Web Aplication Diagram

File

web_pplication_class_diagram_v2.drawio

ESP32 and ESPCAM Communication

Weight Acquisition by Load Cell

The system was implemented in C++ utilizing the olkal/HX711_ADC library for load cell calibration and weight measurement.