IOT system for monitoring and notifying data from segment displays using image processing techniques 📸🔢🔍

This project integrates an ESP32-CAM with a Raspberry Pi to read and interpret digital displays from a multimeter, enhancing visibility and publishing data to a feed.

Multimeter	Device

Overview 📝

The ESP32-CAM captures images of a multimeter's 7-segment display, serving them over HTTP using its IP address. The Raspberry Pi then processes these images:

1. Image Capture: ESP32-CAM captures images of the multimeter's display.
2. Image Processing: Raspberry Pi receives images, enhances them for readability, and performs OCR using Tesseract to extract digits.
3. Data Interpretation: Recognized digits are processed, interpreted, and published to a feed at regular intervals.

Execution 🚀

Input	Perspective	Threshold	Corrected Orientation

Flood Fill	Corrected And Clean Orientation Image	Morphology

cd raspberrypi/build
cmake ..
make && ./main
[100%] Built target main
Starting image processing...
Image saved to: ../assets/input.jpg
Image loaded successfully.
Applying thresholding...
Correcting image orientation...
Applying morphological operations...
Morphological processing complete.
Performing OCR...
Tesseract initialized.
Image set for OCR.
OCR output: 8035
OCR complete.
Exiting...

Feed and Dashboard

Dashboard

Feed

Report 📚

For a detailed explanation of the project, including methodologies and results, please refer to the project report.

License 📄

This project is licensed under the MIT License. See the LICENSE file for details.