#06 Steve McDaniel and Bob McGwier - Developing Sensors for Tracking UFOs
Analysis Summary
Summary
The encounter involves Steve McDaniel and Bob McGuire, who are leading a civilian project called Skyhub. This project aims to gather credible data on UAPs using machine learning cameras and sensors. Steve became interested in UAPs after the New York Times article in 2017, which reported on government videos of UAPs. Bob's interest was sparked by similar events and his background in science and technology. They plan to collect high-quality video and sensor data to analyze UAP phenomena. The impact of this encounter is their commitment to creating a global citizen science project that encourages public participation in UAP research.
Program Intelligence Analysis
The Skyhub project aims to gather credible data on UAP phenomena through a global network of smart cameras and sensors. The initiative emphasizes transparency and open-source collaboration, with a commitment to sharing data publicly. Recent evidence of non-ballistic motion captured by Skyhub raises intriguing questions about UAPs.
Skyhub has captured compelling video evidence of an object exhibiting non-ballistic motion in Houston, Texas.
Steve McDaniel
“The only way to really make progress here is through science and observational science is the perfect methodology to use to explore this.”
Bob McGuire
“This is really about creating a comprehensive data set that can be used by the academic community to do hard research into the UFO phenomenon.”
Managed by: Skyhub
Collect credible data on UAP phenomena through a global network of sensors and cameras
Skyhub aims to create a global observational science project to gather credible data on UAP phenomena using machine learning smart cameras and sensor arrays.
Skyhub has captured compelling video evidence of an object exhibiting non-ballistic motion in Houston, Texas.
The technology and algorithms used in Skyhub are based on advancements in machine learning and AI that have become accessible to civilians.
Skyhub's data will be shared publicly under a Creative Commons license, ensuring transparency and preventing commercialization.