AI-on-the-edge-device

AI-on-the-edge-device

Easy to use device for connecting "old" measuring units (water, power, gas, ...) to the digital world

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AI-on-the-edge-device is a project that enables users to digitize analog water, gas, power, and other meters using an ESP32 board with a supported camera. It integrates Tensorflow Lite for AI processing, offers a small and affordable device with integrated camera and illumination, provides a web interface for administration and control, supports Homeassistant, Influx DB, MQTT, and REST API. The device captures meter images, extracts Regions of Interest (ROIs), runs them through AI for digitization, and allows users to send data to MQTT, InfluxDb, or access it via REST API. The project also includes 3D-printable housing options and tools for logfile management.

README:

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

made-with-c++ Doc Total downloads GitHub release GitHub forks GitHub stars

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 metersβ€”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. πŸ› οΈ


Key Features πŸš€

  • πŸ”— Tensorflow Lite (TFLite) integration – including an easy-to-use wrapper.
  • πŸ“Έ Inline image processing (feature detection, alignment, ROI extraction).
  • πŸ’‘ Small and affordable device (3 x 4.5 x 2 cmΒ³, less than 10 EUR).
  • πŸ“· Integrated camera and illumination.
  • 🌐 Web interface for administration and control.
  • πŸ”„ OTA interface for updating directly via the web interface.
  • 🏠 Full integration with Home Assistant.
  • πŸ“Š Support for Influx DB 1 and 2.
  • πŸ“‘ MQTT protocol support.
  • πŸ“₯ REST API available for data access.

Workflow πŸ”§

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:

  • πŸ“€ Send it to a MQTT broker.
  • πŸ“ Write it to an InfluxDb.
  • πŸ”— Provide access via a REST API.


Impressions πŸ“·

AI-on-the-edge-device on a Water Meter πŸ’§

Web Interface (Water Meter) πŸ’»

AI-on-the-edge-device on an Electrical Power Meter ⚑


Setup πŸ› οΈ

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 πŸ“°

A lot of people have created useful YouTube videos that might help you get started:

For further background information, head to:


Download πŸ”½

The latest available version can be found on the Releases page.


Flashing the ESP32 πŸ’Ύ

Initially, you will have to flash the ESP32 via a USB connection. Later updates are possible directly over the air (OTA using Wi-Fi).

There are different ways to flash your ESP32:

  • The preferred way is the Web Installer and Console, a browser-based tool to flash the ESP32 and extract the log over USB:
  • Flash Tool from Espressif
  • ESPtool (command-line tool)

See the documentation for more information.


Flashing the SD Card πŸ’Ύ

The SD card can be set up automatically after the firmware is installed. See the documentation for details. For this to work, the SD card must be FAT formatted (which is the default on a new SD card).

Alternatively, the SD card can still be set up manually. See the documentation for details.


Casing πŸ› οΈ

Various 3D-printable housings can be found here:


Donate β˜•

If you'd like to support the developer with a cup of coffee, you can do so via PayPal.


Support πŸ’¬

If you have any technical problems, please search the discussions. In case you find a bug or have a feature request, please open an issue.

For any other issues, you can contact the developer via email:


Changes and History πŸ“œ

See the Changelog for detailed information.


Build It Yourself πŸ”¨

See the Build Instructions for step-by-step guidance.


Tools πŸ› οΈ


Additional Ideas πŸ’‘

There are some ideas and feature requests which are not currently being pursuedβ€”mainly due to capacity constraints on the part of the developers. These features are collected in the issues and in FeatureRequest.md.


Our Contributors ❀️

jomjol
jomjol
caco3
CaCO3
haverland
Frank Haverland
Slider0007
Slider0007
SybexX
michael
nliaudat
Nicolas Liaudat
Zwer2k
Zwer2k
phlupp
phlupp
jasaw
jasaw
dockSquadron
dockSquadron
rdmueller
Ralf D. MΓΌller
cristianmitran
cristianmitran
michaeljoos72
michaeljoos72
henrythasler
Henry Thasler
amantyagiprojects
Naman Tyagi
pixeldoc2000
pixel::doc
mad2xlc
Stefan
jochenchrist
jochenchrist
parhedberg
parhedberg
slovdahl
Sebastian LΓΆvdahl
RaHehl
Raphael Hehl
muggenhor
Giel van Schijndel
LordGuilly
LordGuilly
toolsfactory
Michael Geissler
ppisljar
Peter Pisljar
ralf1307
Ralf Rachinger
SkylightXD
SkylightXD
ottk3
Sven Rojek
Turbo87
Tobias Bieniek
yonz2
Yonz
Yveaux
Yveaux
flooxo
flox_x
kalwados
kalwados
kub3let
kub3let
pfeifferch
pfeifferch
rstephan
rstephan
smartboart
smartboart
mkelley88
Matthew T. Kelley
rainman110
Martin Siggel
myxor
Marco H
Innovatorcloudy
KrishCode
joergrosenkranz
Joerg Rosenkranz
queeek
Ina
eltociear
Ikko Eltociear Ashimine
040medien
Frederik Kemner
hex7c0
Francesco Carnielli
dkneisz
Dave
CFenner
Christopher Fenner
PLCHome
PLCHome
austindrenski
Austin Drenski
adarazs
Attila Darazs
wetneb
Antonin Delpeuch
AngryApostrophe
AngryApostrophe

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