About The Umwelt Project
Our Approach
The Umwelt Project is revolutionizing UAP (Unidentified Aerial Phenomena) research by utilizing cost-effective, scalable technology. Our approach is inspired by the groundbreaking "Eye on the Sky" study, which provided valuable insights into UAP characteristics. By focusing our sensors on specific parts of the electromagnetic spectrum identified in this study, we've dramatically reduced costs while maintaining high-quality data collection.
Cost-Effective Innovation
Unlike traditional UAP research that relies on expensive, custom equipment costing hundreds of thousands of dollars, we've adopted a more accessible approach. By using consumer-grade hardware like the Raspberry Pi and it's ecosystem, we've significantly lowered the cost of each Node. This cost reduction allows us to deploy a much larger number of nodes, creating a more comprehensive data collection network.
Core Components
Raspberry Pi Ecosystem
We chose to use the Raspberry Pi Ecosystem as it became apparent that the amount of compute needed to run all these cameras, radios and motors dictated that we distribute compute among a network of Raspberry Pi Computers, with each Pi only handling 1 or 2 sensors MAX. They handle primary computing tasks, data processing, and coordination of various sensors, providing a flexible and scalable foundation for the project.
Camera Sensors
We utilize a range of camera sensors, including the Raspberry Pi Camera modules that have the Sony IMX series of sensors, narrowing down what performs best for the low light nature of this project. The Sony IMX STARVIS family of sensors can get very expensive, especially the ones designed for astrophotogrophy, so compromise at some point in necessary.
Software Defined Radios & Antennas
Our array incorporates software-defined radio (SDR) technology, such as the HackRF One, capable of scanning a wide range of frequencies. RTL-SDR USB radio dongles are cheap and can be used to monitor ADSB, ATC communications and more. Combined with specialized antennas, both omni-directional and directional, this setup allows us to detect and analyze potential RF emissions from UAPs.
Use of Artificial Intelligence
This project wouldn't be possible without the current state of AI technologies. We rely heavily on AI of various types to help streamline the project. From helping with building this website, to helping code apps that allows us to test our sensors quickly and efficiently. We will use Computer Vision to help us automate object detection and filter out known objects, allowing us more time to focus on the unknowns.
The Power of Collaboration
By creating a network of these affordable, standardized sensor arrays, we're democratizing UAP research. Our open-source approach encourages collaboration among researchers, hobbiests, makers and anyone else interested from anywhere in the world, pooling data and insights to advance our understanding of these phenomena.