Building image datasets for machine learning applications can be slow and expensive. SkyScan demonstrates a low-cost system that uses sensors to automate the building of datasets appropriate for computer vision models. SkyScan uses a ground-based camera and software-defined radio to capture images and correlated identity information of commercial aircraft. The SkyScan field kit software runs on a Raspberry Pi and all devices are low-power, allowing the system to run for several hours off of a portable battery.
To enable better tracking, most planes broadcast a signal known as Automatic Dependent Surveillance–Broadcast or ADS-B. This signal is at 1090MHz and can be easily received using a low cost Software Defined Radio (SDR), like the RTL-SDR which repurposes a digital TV chip.
From the ADS-B transmissions, you can get a plane's location and altitude. If you know where a plane is and where you are, you can do some math, point a camera at the plane and take a picture. If you have a Pan/Tilt camera lying around, you can have it automatically track a plane as it flies by and snap photos.