UFO Hunters Built an Open-Source AI System To Scan the Skies

An anonymous reader shares an excerpt from a Motherboard article: Now, frustrated with a lack of transparency and trust around official accounts of UFO phenomena, a team of developers has decided to take matters into their own hands with an open source citizen science project called Sky360, which aims to blanket the earth in affordable monitoring stations to watch the skies 24/7, and even plans to use AI and machine learning to spot anomalous behavior. Unlike earlier 20th century efforts such as inventors proposing "geomagnetic detectors" to discover nearby UFOs, or more recent software like the short-lived UFO ID project, Sky360 hopes that it can establish a network of autonomously operating surveillance units to gather real-time data of our skies. Citizen-led UFO research is not new. Organizations like MUFON, founded in 1969, have long investigated sightings, while amateur groups like the American Flying Saucer Investigating Committee of Columbus even ran statistical analysis on sightings in the 1960s (finding that most of them happened on Wednesdays). However, Sky360 believes that the level of interest and the technology have now both reached an inflection point, where citizen researchers can actually generate large-scale actionable data for analysis all on their own. The Sky360 stations consist of an AllSkyCam with a wide angle fish-eye lens and a pan-tilt-focus camera, with the fish-eye camera registering all movement. Underlying software performs an initial rough analysis of these events, and decides whether to activate other sensors -- and if so, the pan-tilt-focus camera zooms in on the object, tracks it, and further analyzes it. According to developer Nikola Galiot, the software is currently based on a computer vision "background subtraction" algorithm that detects any motion in the frame compared to previous frames captured; anything that moves is then tracked as long as possible and then automatically classified. The idea is that the more data these monitoring stations acquire, the better the classification will be. There are a combination of AI models under the hood, and the system is built using the open-source TensorFlow machine learning platform so it can be deployed on almost any computer. Next, the all-volunteer team wants to create a single algorithm capable of detection, tracking and classification all in one. All the hardware components, from the cameras to passive radar and temperature gauges, can be bought cheaply and off-the-shelf worldwide -- with the ultimate goal of finding the most effective combinations for the lowest price. Schematics, blueprints, and suggested equipment are all available on the Sky360 site and interested parties are encouraged to join the project's Discord server. There are currently 20 stations set up across the world, from the USA to Canada to more remote regions like the Azores in the middle of the Atlantic [...]Once enough of the Sky360 stations have been deployed, the next step is to work towards real-time monitoring, drawing all the data together, and analyzing it. By striving to create a huge, open, transparent network, anyone would be free to examine the data themselves. In June of this year, Sky360, which has a team of 30 volunteer developers working on the software, hopes to release its first developer-oriented open source build. At its heart is a component called 'SimpleTracker', which receives images frame by frame from the cameras, auto-adjusting parameters to get the best picture possible. The component determines whether something in the frame is moving, and if so, another analysis is performed, where a machine learning algorithm trained on the trajectories of normal flying objects like planes, birds, or insects, attempts to classify the object based on its movement. If it seems anomalous, it's flagged for further investigation.

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