Alright folks, gather ’round! Today I’m gonna walk you through my “tall heights tour” project. It was a bit of a rollercoaster, but hey, that’s what makes it fun, right?
First off, the idea. I wanted to build something that could automatically capture images from various tall structures to track the surroundings. Simple enough, or so I thought.
So, I started by scouting out some locations. This took way longer than expected. Finding spots with the right height, view, and, crucially, access, was a pain. Ended up settling on a few buildings downtown.
Next up, hardware. I snagged a couple of high-resolution cameras ’cause image quality is key, right? Also got some weatherproof enclosures to protect them from the elements. And, of course, a Raspberry Pi to control everything.
The fun part: wiring everything up. I spent hours fiddling with cables, making sure the cameras were properly connected to the Pi and that the power supply was stable. There were a few sparks (literally!), but nothing I couldn’t handle.
Then came the software. I wrote a Python script to handle image capture, scheduling, and storage. Used some libraries for image processing to tweak the photos for better quality. Debugging was a nightmare – spent way too long chasing down syntax errors and figuring out why the cameras weren’t triggering correctly.
Once the system was running smoothly on my desk, it was time to deploy it. Getting permission to install everything on the buildings was another hurdle. Had to convince building managers that my project was harmless. Lots of paperwork and meetings later, I finally got the green light.
Installation day! With a bunch of zip ties and some heavy-duty adhesive, I secured the camera enclosures to the chosen spots. Made sure everything was level and pointed in the right direction. It was a bit nerve-wracking, but the view from up there was pretty awesome.
After the installations, it was monitoring time. The script automatically captured images at set intervals. I set up a cloud storage account to upload the photos so I could check on things remotely. There were some hiccups along the way – the internet connection went down a few times, and the camera angles needed some tweaking – but I managed to keep everything running.
Data analysis was next. I looked at the images over time, tracking changes in the surrounding environment, like traffic patterns and construction projects. I even tried some machine learning algorithms to automatically identify certain objects in the images, like cars or pedestrians.
And that’s pretty much it! I learned a ton about hardware, software, and project management. The tall heights tour was a wild ride, but I’m proud of what I accomplished.
