10 Object Detection Projects You Can Build with a Raspberry Pi Camera

With your camera and a Raspberry Pi, you can now detect and identify objects in real time. I’ve built several object detection projects using the Raspberry Pi, and in this post, I’ll share some practical ideas you can start building yourself.

Many object identification projects are realistically achievable with a Raspberry Pi camera. They range from simple setups, such as smart door monitoring, to more advanced systems, such as crop pest detection.

You’ll find a mix of projects here, from quick ones you can put together in an afternoon to more advanced ideas you can build on over time. Just pick something that feels right for your level and give it a try.

If you’re looking for inspiration for your next Raspberry Pi project, I’ve put together a list of 75+ ideas with full descriptions, difficulty ratings, and links to tutorials. Whether you’re a beginner or more advanced, there’s something here for you. Grab the list for free here!

1. Check Who’s at the Door Before Opening

Smart doorbell with face detection.

The first Raspberry Pi project I ever built with a camera was a basic home security camera. The setup was dead simple: a Raspberry Pi Camera module, MotionEye installed, a few configuration tweaks, and suddenly I could pull up a live feed on my phone. It felt like magic at the time.

But looking back, it was also pretty dumb. It recorded everything equally: the wind blowing a leaf, a cat walking by, an actual person at the door. But now that AI is here, the landscape changes completely.

With this project, you turn your Raspberry Pi into a smart doorbell that actually understands what it’s seeing. Instead of just buzzing when something moves, the system uses face detection to tell you who is at the door: a familiar face, a delivery person, or someone completely unknown. That distinction matters a lot at 10 PM when you’re deciding whether to answer.

You can configure the system to send custom notifications to your phone, capture snapshots when motion is detected, and even help you keep track of deliveries. When you compare this to a regular doorbell, this project gives you intelligence, automation, and customization all in one.

To get started, you’ll need a Raspberry Pi Camera paired with a lightweight object detection model like YOLO, which can comfortably handle the job. You are only monitoring a small area (your doorstep), not high-speed traffic.

2. Find Out What Your Pet Really Does All Day

Pet activity tracker.

I’ll be honest, the first time I left my dog home alone for a full workday, I came back convinced he’d spent the whole time sleeping. Then I watched a YouTube video of animals left alone at home, and realized I was probably very wrong. Turns out pets have entire secret lives the moment the door clicks shut.

This project turns your Raspberry Pi into a simple pet activity tracker that lets you monitor what your dog or cat is really doing while you’re away.

For this project, you don’t need to spend any extra money getting the Raspberry Pi AI Kit. You can use the Raspberry Pi Camera together with a lightweight model like YOLO to detect when your pet is active, resting, pacing, or suddenly doing laps around the living room for no apparent reason.

The system can log activity patterns throughout the day and even trigger short video recordings when movement is detected.

To get started, you’ll need a:

• Raspberry Pi (4 or 5),
• Raspberry Pi Camera module, and
• Power supply.

From there, check out the YOLO object detection tutorial for Raspberry Pi and the Raspberry Pi Camera documentation to get your camera feed up and running.

3. Build Your Own Backyard Wildlife Documentary

Wildlife camera.

I grew up watching Nat Geo Wild documentaries and always assumed that kind of footage required expensive equipment, a film crew, and a lot of patience sitting in a hide for hours. What I didn’t expect was that a $35 computer could come surprisingly close.

Imagine turning your backyard into your own private nature channel? With a Raspberry Pi and a camera module, you can build a wildlife monitoring system that automatically detects and records animals that wander into your garden.

Whether it’s birds, monkeys, rodents, or other local wildlife, this project lets you observe nature in a whole new way without sitting outside for hours.

The real magic happens at night. Before my Raspberry Pi, I tried using my phone to record a time-lapse at night, and animals I never knew passed through my area started showing up in the recordings. Over time, the footage started to look like a proper mini-documentary.

Now with a Raspberry Pi, you can design the system to start recording automatically when motion or specific animals are detected. That will ensure you are not wading through hours of empty footage. You define what triggers a recording, and the Raspberry Pi does the watching.

For better low-light performance, I’d recommend looking at the Raspberry Pi AI Camera. The improved sensor makes a noticeable difference after dark.

To get started, you’ll need a:

• Raspberry Pi,
• Pi camera (the AI Camera is worth it here),
• Weatherproof enclosure, and
• Power source.

Our motion detection guide and Ultralytics YOLO documentation are good starting points. You’ll also want to explore picamera2 for camera control.

4. Spot Home Intruders

Home security system.

Motion-sensor security cameras have a flaw I’ve run into repeatedly: false alarms. A tree branch sways in the wind, your cat walks past, a car drives by, and suddenly, you’re getting pings at 2 AM. After enough false alerts, you start ignoring them, which defeats the purpose entirely.

This project takes a smarter approach. Instead of triggering on any movement, the Raspberry Pi uses real-time object detection to distinguish humans from everything else. That means fewer false alarms and faster, more reliable alerts when something actually warrants your attention.

You’re also not limited to a single camera at the front door. Multiple cameras can feed a continuous stream to a single Raspberry Pi, giving you full coverage without building out an expensive dedicated system.

For this one, I’d strongly recommend the Raspberry Pi AI Kit. Analyzing continuous video feed from different cameras is quite demanding for the Raspberry Pi CPU alone. Without a dedicated processing unit, you’ll likely see lag or missed detections when you need the system most.

To get started, you’ll need:

• A Raspberry Pi 5,
• The Raspberry Pi AI Kit,
• One or more camera modules, and
• A local network setup.

The Raspberry Pi AI Kit guide walks through installation, and this multi-camera tutorial covers managing multiple feeds.

5. Never Run Out of Stock Again

Retail shelf monitoring system.

Running a small shop teaches you one thing very quickly: the shelf doesn’t announce when it’s empty. A product quietly sells out, no one flags it, and the next customer asking for it is the first time you find out. I’ve heard this same story from almost everyone who’s run a small kiosk or retail setup. Manual stock checks work in the beginning, but they don’t scale.

This project puts a small Raspberry Pi camera above your shelves and lets it do the watching instead. Using object detection, the system can identify when products are running low or missing entirely and send you a notification before customers start asking.

The setup is simple: a mounted camera, decent lighting, and a Raspberry Pi running detection in the background. Think of it as a quiet retail assistant that never takes a break and never forgets to check the shelves.

For this use case, the Raspberry Pi AI Kit is worth it. Continuous video, multiple products in frame, and fast detection throughout the day add up, so the AI Kit keeps performance smooth without maxing out the CPU.

To get started, you’ll need:

• A Raspberry Pi 5 with the AI Kit,
• A camera module,
• Mounting hardware, and
• Lighting.

Take a look at Ultralytics YOLO for retail shelf monitoring and the Raspberry Pi AI Kit setup guide to get the detection pipeline running.

Want even more ideas? I put together a free resource with over 75 Raspberry Pi project ideas, each with a quick description, tutorial link, and hardware requirements. Whether you’re just starting out or looking for something to do this weekend, this list will keep you busy for a while. Just click here to get instant access.

6. Count Your Farm Animals Automatically

Smart farm animal counter.

Counting livestock sounds straightforward until you actually try it. Animals move constantly, they cluster together, they wander into corners, and by the time you’ve finished your count, half the herd has shifted. On a small farm, it’s manageable—annoying, but manageable. As numbers grow, the room for error grows too.

Placing a camera at the entrance to a pen and letting a Raspberry Pi handle the count changes that completely. Animals are tracked as they enter or leave, and the system keeps an accurate running record without anyone having to stand there with a clicker. At the end of the day, the data is already logged. Did all the goats make it back in? The system knows.

Because you’re dealing with continuous video, multiple moving animals, and the need for real-time accuracy, the Raspberry Pi AI Kit, combined with a high-quality Raspberry Pi camera, is the right setup here. It’s the kind of task that will push a standard Pi harder than you’d expect.

To get started, you’ll need:

• A Raspberry Pi 5 with the AI Kit,
• The Raspberry Pi HQ Camera,
• Weatherproof housing, and
• A mounting position at the enclosure entrance.

The YOLO object tracking documentation covers the tracking logic, and this Raspberry Pi camera setup guide handles the hardware side.

7. Catch Pests Before They Destroy Your Plants

Crop pest detection camera.

Pest damage rarely shows up all at once. It starts with a few spots on a leaf, some tiny holes, and a cluster of insects you almost miss. By the time it’s visible enough to notice during a normal walkthrough, the problem has already spread. I am into farming myself, and I’ve seen this pattern enough times to appreciate how much a few extra days of early detection matter.

AI-powered agricultural drones exist for exactly this reason, but they’re built for commercial scale and commercial budgets. For a home garden or small growing operation, a Raspberry Pi mounted on a stand above your plants can do something surprisingly similar.

Using object detection, the system can identify insects, unusual leaf patterns, and early signs of infestation, flagging problems at the first hint of trouble rather than after the damage is done. If you want to cover more ground, you can even mount the camera on a rail system with small motors to have it move along a row of plants automatically.

The Raspberry Pi AI Kit is recommended here. Detecting small pests and subtle plant changes in real time requires faster inference than a standard Pi can deliver reliably.

To get started, you’ll need:

• A Raspberry Pi 5 with the AI Kit,
• A close-focus camera module,
• A sturdy mount or rail system, and
• Good lighting.

The PlantDoc dataset is a useful resource for training or fine-tuning a plant disease detection model, and the Ultralytics YOLO docs cover getting detection up and running.

8. Measure Traffic Congestion Patterns

Traffic monitoring system.

There’s a stretch of road near where I live that turns into a complete standstill every weekday around 8:15 AM. It’s not random but follows a pattern tied to a nearby school. Once you know to look for it, the rhythm becomes obvious. But without any data, it just looks like chaos.

This project turns a Raspberry Pi into a compact traffic monitoring station. Mount a camera in a good vantage point, and the system detects and counts vehicles as they pass. Over time, it builds a picture of peak hours, traffic density, and congestion trends. Essentially, a small-scale version of what smart cities deploy, built with accessible hardware.

For accurate results on a busy road, the Raspberry Pi AI Kit is a perfect choice. Fast-moving vehicles and higher-resolution feeds need the extra processing power to keep detection reliable without lag. Pair it with the Raspberry Pi HQ Camera mounted at a height to capture the full road clearly.

To get started, you’ll need:

• A Raspberry Pi 5 with the AI Kit,
• The Raspberry Pi HQ Camera,
• A high mounting position, and
• Power.

The YOLO vehicle detection guide has pre-trained car detection capabilities, and this tutorial on object counting covers how to build the logic.

9. Never Lose a Tool on Your Desk Again

Object tracker for a mini AI lab.

My electronics workbench is organized in that special way where I know exactly where everything is, right until the moment I actually need something. The screwdriver is there somewhere, hiding between a voltage regulator and a connector I haven’t identified yet.

Does that issue sound familiar? Now, what if you had a Raspberry Pi as your assistant that constantly monitors what’s happening and where every single item is placed on your working table?

This project mounts a Raspberry Pi camera above your workspace and uses a lightweight model to track what’s on the table. Since the environment is controlled—fixed lighting, mostly stationary objects—you don’t need heavy real-time processing. A standard Raspberry Pi handles it comfortably.

What makes this one fun is how far you can take it. Start with basic object tracking, and you can expand it into an automated inventory checker for components, a system that identifies parts in real time, or even a reminder that flags when tools aren’t returned to their designated spot. The scope grows naturally from whatever frustrates you most about your current workspace.

To get started, you’ll need:

• A Raspberry Pi (4 or 5),
• A camera module, and
• An overhead mount.

A good starting point is this YOLO object detection tutorial and the picamera2 library for camera control. If you want to build out a custom object recognition model for your specific tools, Roboflow makes it straightforward to label and train on your own images.

10. Check Attendance in Record Time

Smart attendance scanner.

I’ve sat through enough manual sign-in processes to know there has to be a better way of checking attendance. The manual method looks so disorganized; the clipboard making its way around the room, people squinting to read the handwriting above theirs, and someone inevitably writing their name in the wrong column.

By the time the sheet returns to the front, half the names are barely legible, and the whole process has taken far longer than it should.

With a Raspberry Pi, a camera, and a face detection model like YOLO, you can build an attendance scanner that handles everything automatically. Walk in, get detected and get logged. No clipboards, no roll calls, no chasing people down afterward to fill in the sheet.

For small groups — a classroom, a workshop, a regular team meeting — a standard Raspberry Pi with a camera module is more than enough. You don’t need high frame rates or the AI Kit for this. Hook it up to a display for live visual feedback, connect a local database to store records, and you’ve got a system that works quietly in the background and keeps a permanent log.

It’s also one of the more immediately useful projects on this list — you can build it, deploy it, and start actually using it in a real setting.

To get started, you’ll need:

• A Raspberry Pi 4 or 5,
• A camera module,
• An optional display, and
• A simple database like SQLite.

The face recognition library for Python is a popular starting point, and this Raspberry Pi face detection tutorial covers the basics. For storing and querying attendance logs, this SQLite Python guide will get you set up quickly.

These Raspberry Pi AI projects show just how powerful a small single-board computer can be when combined with computer vision and the right models. Whether you’re improving security, automating monitoring, or just experimenting for fun, each idea gives you a practical way to turn AI into something you can actually use.

Whenever you’re ready, here are other ways I can help you:

Test Your Raspberry Pi Level (Free): Not sure why everything takes so long on your Raspberry Pi? Take this free 3-minute assessment and see what’s causing the problems.

The RaspberryTips Community: Need help or want to discuss your Raspberry Pi projects with others who actually get it? Join the RaspberryTips Community and get access to private forums, exclusive lessons, and direct help.

Master your Raspberry Pi in 30 days: If you are looking for the best tips to become an expert on Raspberry Pi, this book is for you. Learn useful Linux skills and practice multiple projects with step-by-step guides.

Master Python on Raspberry Pi: Create, understand, and improve any Python script for your Raspberry Pi. Learn the essentials step-by-step without losing time understanding useless concepts.

You can also find all my recommendations for tools and hardware on this page.