This Raspberry Pi-based build aims to deter porch pirates from stealing packages left at your front door. In recent times, we’ve all relied on home-delivered goods more than ever, and more often than not we ask our delivery drivers to stash our package somewhere if we’re not home, leaving them vulnerable to thieves.

Flashing lights, sirens, flour and sprinklers

When internet shopper and AI project maker Ryder had a package stolen from his porch, he wanted to make sure that didn’t happen again. He figured that package stealers would be deterred by blaring sirens and flashing red lights. He also went one step further, wanting to hamper the thief’s escape with motion-activated water sprinklers and a blast of flour ready to catch them as they run away.

A simple motion detector wouldn’t work because it would set off Ryder’s booby traps whenever an unsuspecting cat or legitimate visitor happened across his porch, or if Ryder himself arrived home and didn’t fancy a watery flour bath. So some machine learning and a Python script needed to be employed.

How does it catch package thieves?

The camera keeps an eye on Ryder’s porch and is connected wirelessly to a Raspberry Pi 4, which works with a custom TensorFlow machine learning model trained to recognise when a package is or isn’t present. If the system detects a package, it gets ready to deploy the anti-thief traps. The Raspberry Pi sets everything off if it detects that someone other than Ryder has removed the package from the camera’s view.

And Ryder had an interesting technique to train the machine learning model to recognise him:

If you want to make your own anti-porch pirate device, Ryder has shared everything you need on GitHub.

Wanna see some cool dogs?

We can always rely on Ryder Calm Down’s YouTube channel for unique and quasi-bonkers builds.

If you’re not familiar with Ryder’s dog-detecting (and happiness-boosting) build, check it out below. We also blogged about this project when we needed a good dopamine boost during lockdown.