README

AI on the Edge Device: Digitizing Your non-digital meters with an ESP32-CAM



 Table of Contents
- Key Features 🚀
- Workflow 🔧
- Impressions 📷
  - AI-on-the-edge-device on a Water Meter 💧
  - Web Interface (Water Meter) 💻
  - AI-on-the-edge-device on an Electrical Power Meter ⚡
- Setup 🛠️
- Download 🔽
- Flashing the ESP32 💾
- Flashing the SD Card 💾
- Casing 🛠️
- Donate ☕
- Support 💬
- Changes and History 📜
- Build It Yourself 🔨
- Tools 🛠️
- Additional Ideas 💡
- Our Contributors ❤️


    
        
    













  


Artificial intelligence is everywhere, from speech to image recognition. While most AI systems rely on powerful processors or cloud computing, edge computing brings AI closer to the end user by utilizing the capabilities of modern processors.  
This project demonstrates edge computing using the ESP32, a low-cost, AI-capable device, to digitize your analog meters—whether water, gas, or electricity. With affordable hardware and simple instructions, you can turn any standard meter into a smart device.

Let's explore how to make AI on the Edge a reality! 🌟

All you need is an ESP32 board with a supported camera and some practical skills. 🛠️

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 Key Features 🚀
- 🔗 Tensorflow Lite (TFLite) integration – including an easy-to-use wrapper.
- 📸 Inline image processing (feature detection, alignment, ROI extraction).
- 💡 Small and affordable device (3 x 4.5 x 2 cm³, less than 10 EUR).
- 📷 Integrated camera and illumination.
- 🌐 Web interface for administration and control.
- 🔄 OTA interface for updating directly via the web interface.
- 🏠 Full integration with Home Assistant.
- 📊 Support for Influx DB 1 and 2.
- 📡 MQTT protocol support.
- 📥 REST API available for data access.



 Workflow 🔧
The device captures a photo of your meter at set intervals. It then extracts the Regions of Interest (ROIs) from the image and runs them through artificial intelligence. As a result, you get the digitized value of your meter.

There are several options for what to do with that value:
- 📤 Send it to a MQTT broker.
- 📝 Write it to an InfluxDb.
- 🔗 Provide access via a REST API.


   


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 Impressions 📷

+  AI-on-the-edge-device on a Water Meter 💧
  
     
  

+  Web Interface (Water Meter) 💻
  
     
  

+  AI-on-the-edge-device on an Electrical Power Meter ⚡
  
     
  

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 Setup 🛠️
There is growing documentation which provides you with a lot of information. Head there to get started, set it up, and configure it.

There are also articles in the German Heise magazine "make:" about the setup and technical background (behind a paywall): DIY - Setup 📰

A lot of people have created useful YouTube videos that might help you get started:
- 🎥 youtube.com/watch?v=HKBofb1cnNc
- 🎥 youtube.com/watch?v=yyf0ORNLCk4
- 🎥 youtube.com/watch?v=XxmTubGek6M
- 🎥 youtube.com/watch?v=mDIJEyElkAU
- 🎥 youtube.com/watch?v=SssiPkyKVVs
- 🎥 youtube.com/watch?v=MAHE_QyHZFQ
- 🎥 youtube.com/watch?v=Uap_6bwtILQ

For further background information, head to:
- Neural Networks
-