A Small Design Experiment: Observing My Parrot Friend

It Started With a Parrot

For a while, a parrot visited my window ledge almost every day. It didn’t scream, destroy things, or act like a typical bird. Instead, it just sat there and watched me work. Quietly. Judgmentally. Like a tiny green supervisor.

At some point, it started to feel oddly familiar. Almost intentional. Like some long-lost ancestor checking in to see if I was doing something useful with my life. Then one day… it stopped coming.

Days passed. Then weeks. The window ledge stayed empty. This led to a spiral of questions:

• Is it still coming when I’m not around?

• Has it changed its routine?

• Or… worst case?

  
  

Instead of overthinking it forever, I did what any reasonable designer would do. I built a system.

My parrot friend

The Question Became a Design Problem

The real problem wasn’t “where is the parrot?” The problem was: I had no way of knowing. I couldn’t sit at the window all day. Checking randomly was just guessing. What I needed wasn’t more effort — it was continuous observation.

The empty window sill 🙁

So, I decided to design a small, always-on bird detection setup using simple hardware and code. Not to obsess over live feeds, but to quietly collect evidence over time.

Also, full honesty: I couldn’t get it to detect parrots specifically (yet). So, I made it detect any bird, and I’d review the captures now and then to see if my friend ever showed up.

The Setup (Nothing Fancy)

The setup was intentionally simple:

• A Raspberry Pi

• A webcam placed on the window ledge

• A lightweight bird detection model

• A small web page to review what was captured

  
  

Camera on the window sill

The camera watches the ledge continuously. When the system is confident that a bird is present, it saves a frame and logs the time. No notifications. No alarms. No constant monitoring. Just… watching.

Designing the Logic Was the Real Work

The hardest part wasn’t the hardware or the code. It was deciding what counts. Real life is messy:

• Changing sunlight looks like motion

• Leaves move

• Shadows move

• Pigeons behave like pigeons

  
  

So, the design work went into:

• Filtering false positives

• Setting confidence thresholds

• Adding cooldowns so it doesn’t save 200 near-identical frames

• Deciding what’s useful to look at later

  
  

This is where it stopped feeling like a tech project and started feeling like design.

The Interface (Built for Restraint)

I made a simple web interface to review the system:

• Live view of the ledge

• Bird count for the day

• Recent bird captures

• Rough time windows when birds usually appear

  
  

The goal wasn’t to create a flashy dashboard. It was to make something I could check occasionally, to see if my dear parrot friend had returned.

The Result (Plot Twist)

The system worked. Beautifully. It detected birds reliably. Logged them. Showed patterns. Predicted visit windows. And the result? Only pigeons! So many pigeons, uhhh!

The parrot never showed up. Which, oddly enough, was still an answer.

What This Taught Me as a Designer

• You don’t need deep coding skills to build meaningful systems.

• One simple idea + basic hardware can go a long way.

• Most design decisions are about what to ignore.

• Real environments are noisy — systems must be forgiving.

• Sometimes, the most important outcome is confirming that something isn’t happening (sorry parrot friend).

  
  

Manifesting my dear *parrot friend's retur.

And somewhere out there, the parrot is either watching… or has moved on.

In loving memory of my dear parrot friend.

Expanding the Experiment

The Next Steps

After the initial success of my bird detection system, I thought about expanding the project. What if I could track the types of birds that visited? Or even create a database of their behaviours? This could lead to fascinating insights about urban wildlife.

Collaborating with Others

I also considered reaching out to fellow designers and tech enthusiasts. Sharing ideas and collaborating could enhance the project. Imagine a community of bird watchers, all contributing to a larger understanding of our feathered friends.

Future Innovations

The possibilities are endless! I could integrate machine learning to improve detection accuracy. Or even develop an app that alerts users when specific birds arrive. This could turn a simple observation project into a full-fledged research initiative.

Conclusion

In the end, this small design experiment taught me valuable lessons about observation, design, and the importance of asking questions. Whether it’s a parrot or a pigeon, every encounter offers an opportunity for learning and growth.

So, here’s to my parrot friend — wherever you are!