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--- amc:ss2024:smart_water_metering:start [2024/07/30 21:33] – [System Startup] demid.dabizha
+++ amc:ss2024:smart_water_metering:start [2024/07/30 21:50] (current) – [6. Conclusion] demid.dabizha
@@ Line 54: / Line 54: @@
 === Hardware Preparation and ESP Firmware Installation ===
-  - **Connecting the Hardware**: Mount the ESP32-CAM onto the ESP32-CAM-MB. Ensure all pins are connected correctly. There is no need for additional wires when using the ESP32-CAM-MB.{{ :amc:ss2024:smart_water_metering:photo_2024-07-28_18-56-23.jpg?nolink&200 |}}
+  - **Connecting the Hardware**: Mounting the ESP32-CAM onto the ESP32-CAM-MB. Ensure all pins are connected correctly. There is no need for additional wires when using the ESP32-CAM-MB.{{ :amc:ss2024:smart_water_metering:photo_2024-07-28_18-56-23.jpg?nolink&200 |}}
   - **Power Supply**: The ESP32-CAM requires a 5V power supply, typically provided via a USB power source.
   - **Entering Flashing Mode**: This is very important step. To enter flashing mode, its needed to connect a wire between GND and GPIO0 on the ESP32-CAM-MB (I used male jumper cable to connect GND and GPIO0). This is necessary for the initial firmware flashing.
   - **Flashing the Firmware**:
       *  Download the required firmware files from the [[https://github.com/jomjol/AI-on-the-edge-device/releases|GitHub repository]] in a zip file.
-      *  Connect the ESP32-CAM-MB to the computer via a USB cable.
+      *  Connecting the ESP32-CAM-MB to the computer via a USB cable.
       *  With use of Arduino IDE upload the firmware onto the ESP32-CAM.
@@ Line 146: / Line 146: @@
 === Accuracy and Reliability ===
-The implementation of the Computer vision on the ESP32-CAM demonstrated high accuracy in reading the numerical values from the water meter. The system's ability to correctly detect and interpret the digits is critical for reliable water usage monitoring. However, occasional inaccuracies were observed due to variations in lighting conditions and reflections from the water meter cover. But this can be fixed by the methods mentioned earlier in "Dealing with Reflections".
+The implementation of the Computer vision on the ESP32-CAM demonstrated high accuracy in reading the numerical values from the water meter. The system's ability to correctly detect and interpret the digits is critical for reliable water usage monitoring. However, occasional inaccuracies were observed in the last digit due to variations in lighting conditions and reflections from the water meter cover. But this can be fixed by the methods mentioned earlier in "Dealing with Reflections".
 === Integration with Home Assistant ===
@@ Line 170: / Line 170: @@
 Every time the ESP32-CAM was powered up, the settings were reset, causing the Regions of Interest (ROIs) to shift and making it difficult to accurately capture the numbers.
 To address this, the Alignment References were turned off.
-The custom casing ensured that the ESP32-CAM and water meter maintained a consistent position, eliminating the need for re-alignment with each restart.
+The custom casing ensured that the ESP32-CAM  maintained a consistent position, eliminating the need for re-alignment with each restart.
 ==== 6. Conclusion ====
-I managed to make a working module for a water meter that is ready for use in household. The ESP32-CAM for smart water metering has shown great potential in automating water usage monitoring. The system accurately reads water meter numbers, though there were some challenges with lighting and reflections. Integrating it with Home Assistant made the system easier to use and provided real-time data for better water management.
+I managed to make a working module for a water meter that is ready for use in household. The ESP32-CAM for smart water metering has shown great potential in automating water usage monitoring. The system accurately reads water meter numbers, even though the protective plastic cover causes "inconvenient" reflections from the LED light.
-A major advantage of this project is its low cost. The ESP32-CAM and other components are affordable, making it accessible to many people. Also, the setup process, while requiring some basic technical skills, is not too complicated. Clear instructions and open-source firmware make it easier to implement.
+A major advantage of this project is its low cost. The ESP32-CAM and other components are affordable, making it accessible to many people. Also, the setup process, while requiring some technical skills, is not that complicated. Open-source firmware make it easier to implement.
 ==== Links ====
 https://jomjol.github.io/AI-on-the-edge-device-docs/