Build a bird-feeder camera that sends photos to your phone (ESP32-CAM, one weekend)

Fri, 30 Oct 2026 11:14:48 +0000

"I want photos of birds at my feeder sent to my phone."

A tiny camera board next to the feeder takes a photo when something moves and sends it to your phone. It's cheap and fun; the photos are decent, not wildlife-magazine sharp.

Cost $15–30 · Time one weekend · Level some experience helps · Power USB (solar is harder)

What to buy

Part	Why this one	Rough cost
ESP32-CAM with its USB programming board (ESP32-CAM-MB)	Camera and WiFi on one small board. The add-on board makes uploading code easy.	$8–15
PIR motion sensor (e.g. AM312)	Detects warm, moving bodies. Small and low-power.	$1–3
5V USB power supply, 2 A	The camera and WiFi together draw a lot; weak supplies cause random resets.	$5
Weatherproof box with a clear window	Keeps rain and condensation off the lens.	$5–10

Prices are rough ranges, not quotes. Check the current price and stock before you order.

What to install

An Arduino sketch that wakes on motion, takes a photo and sends it through a Telegram bot (the UniversalTelegramBot library has ESP32-CAM examples). ntfy can take photo attachments too.

Runner-up: a Raspberry Pi with its camera module. It costs more and uses more power, but takes much better photos and can spot motion in the image itself.

Build it in three steps

Take a photo on your desk. Flash the camera web-server example that comes with the ESP32 Arduino package, and view the picture in a browser.
Send one to your phone. Set up the bot, and send a photo when you wave at the motion sensor.
Move it outside. Mount it 30–60 cm from the perch, facing away from the sun, and adjust from there.

What catches people out

Motion sensors miss small birds. PIR sensors are made to spot people; a small bird a metre away may not trigger one. Mount the sensor close to the perch, or take a photo every few seconds and keep only the ones that changed.
Focus. The stock lens is usually focused further away. For close-ups it can be turned carefully to refocus (it's often held by a dab of glue), or move the camera back.
Random resets. "Brownout detector was triggered" in the log means the power sagged. Use a good 5V supply and a short, thick cable.
Solar is a step up. The camera draws a lot while it's awake. Get it working on USB before you try solar.

This guide first appeared on IotMentor, a free chat mentor for small electronics builds (I make it). If your setup is different (distance, power, budget, experience), you can ask it there and it will plan your version.

Built an AI Tool That Generates Wiring Diagrams and Code for Arduino Projects. Here's What I Learned.

Tue, 26 May 2026 05:26:03 +0000

I'm not an electrical engineer. But I kept wanting to build smart devices - a mosquito trap for the garden, a nightlight my kid controls with claps, a smart dog collar.

Every time, I'd hit the same wall: which components are compatible? What pins do I connect? What libraries do I need?

So I built Make-it - you describe a device in plain English and it generates:

A complete parts list with specs
A wiring diagram with pin assignments
Working Arduino/ESP32/Raspberry Pi code
A step-by-step build guide

The technical challenge

The hard part isn't generating code - any LLM can do that. The hard part is making the output actually buildable:

GPIO pin conflict detection across multiple sensors
Component compatibility validation (will this sensor work with this board?)
Correct library dependencies and imports
Pin assignments that match the physical wiring

A raw LLM will confidently tell you to connect a sensor to a pin that doesn't support analog input. The domain layer on top catches that.

Real-world testing

I've been dogfooding by posting actual builds on Reddit:

An automated mosquito trap hit 339K views and #1 on r/homeautomation
A clap-activated nightlight for kids got 25K views on r/arduino
People are actually ordering parts and building these projects

What's next

I'm working on multi-board communication (Arduino + RPi over serial), better PCB-level layouts, and eventually simulation.

Would love feedback from anyone who's tried using AI for hardware projects. What works? What breaks?

Try it here

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