CAIBI ASSESSMENT

AI-on-the-edge-device

An ESP32-CAM project that reads existing water, gas or electricity meters and publishes the readings digitally.

CAIBI VERDICTBUILD IT

It adds digital reporting to a meter that already works. The value is in avoiding replacement hardware and extracting more use from the equipment you already have.

Build with AI See the build I built this

AI CAN HELP

Useful work to hand to AI

Recognition
Configuration help
Troubleshooting

AI CAN'T DO

The physical boundary

Mount the camera rigidly in front of the real meter
Create stable lighting and remove glare from the physical installation
Choose and adjust the final camera angle and distance
Verify that the recognised reading matches the actual meter over time

BUILD WITH AI

Start with the project, not a blank prompt.

The CAIBI build pack gives an AI assistant the source, the known constraints, the useful AI work and the physical boundary. It is designed to help you move faster without pretending the AI has built the thing for you.

Preview the full build brief

I want to build AI-on-the-edge-device.

Source project: https://github.com/jomjol/AI-on-the-edge-device

Use the source as the authority. Do not invent parts, dimensions, prices or capabilities that are not published.

AI can help with: Recognition, Configuration help, Troubleshooting.
AI cannot physically do: Mount the camera rigidly in front of the real meter, Create stable lighting and remove glare from the physical installation, Choose and adjust the final camera angle and distance, Verify that the recognised reading matches the actual meter over time.
Tools and capabilities involved: ESP32-CAM.
CAIBI's main concern: Mounting, lighting and camera alignment are part of the system. Recognition software cannot compensate for a poor physical installation.

Start by checking the source, confirming the current parts and build instructions, then give me a staged plan. Clearly separate source facts from your suggestions. Stop and ask me to verify anything that depends on physical fit, wiring, calibration or safety.

THE BUILD

How it actually comes together

Check the source ↗

YOU

Check camera hardware compatibility

Start with an ESP32 camera board supported by the project documentation. Camera choice and illumination directly affect recognition quality.

AI + YOU

Flash the current release

Install the firmware over USB using the project web installer, Espressif tooling or esptool. Later updates can be installed over Wi-Fi.

AI + YOU

Prepare the SD card

Use the built-in setup route or prepare the FAT formatted SD card manually as documented.

YOU

Mount and light the meter

Fit the camera so the meter face is stable, well lit and repeatable. This physical setup is part of the recognition system, not a cosmetic detail.

AI + YOU

Configure the reading regions

Use the web interface to align the image and define the regions that the model should read. AI can help interpret settings and troubleshoot, but you must validate the actual readings.

AI + YOU

Send the readings somewhere useful

Connect the finished device to MQTT, InfluxDB, Home Assistant or the REST API once recognition is reliable.

WHAT YOU NEED

Key components

ESP32 board with a supported camera
Integrated or external illumination
FAT formatted SD card
USB connection for initial flashing
Meter-specific mounting or 3D printed housing
Wi-Fi network for setup, updates and integrations

AFTER THE FIRST BUILD

Ways to take it further

Water meter readerGas meter readerElectricity meter readerHome Assistant integrationMQTT outputInfluxDB logging

OTHER WAYS TO GET THERE

You do not have to follow one route.

ORIGINAL BUILDFollow the creator route

Use the published source, files and instructions as the baseline.

↗AI ASSISTEDUse the CAIBI build pack

Start from the source with prompts that keep the AI inside the verified build information.

→ALTERNATIVE PROJECTVerhoBot

A compact ESP32 curtain robot built to automate an existing curtain rail without ropes or pulleys.

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REVIEWED RESOURCES

Useful places beyond the main source

DOCSAI-on-the-edge-device documentation

Current setup, compatibility and installation documentation.

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MADE BY PEOPLE

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SOURCE · CAIBI · BUILDERS

What supports the verdict

SOURCEjomjol

Source available with active documentation and releases

The project digitises existing water, gas and electricity meters with an ESP32 camera rather than replacing the meter.
The source describes the hardware as small and affordable, with a supported board and camera costing less than about €10 before mounting and other extras.
The project includes a web interface, OTA updates, MQTT, InfluxDB, Home Assistant support and a REST API.
The source provides separate 3D printable housing options for different meter types.

Open source ↗

CAIBIBUILD IT

It adds digital reporting to a meter that already works. The value is in avoiding replacement hardware and extracting more use from the equipment you already have.

Evidence: Strong
Biggest challenge: Mounting, lighting and camera alignment are part of the system. Recognition software cannot compensate for a poor physical installation.

BUILDERSNo published reports yet

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BUILT IT?

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What worked and what changed
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