Hey r/UFOs! Long-time lurker. *New account made for this project. Like many of you, I’m tired of shaky phone videos that lack context and...
This is an automated archive made by the Lemmit Bot.

The original was posted on /r/ufos by /u/SteadySignals on 2024-12-08 14:22:37+00:00.

Hey r/UFOs! Long-time lurker.

*New account made for this project.

Like many of you, I’m tired of shaky phone videos that lack context and supporting evidence. (I say I’m tired of it but I still get excited seeing some of it). To address this, I’ve started a project creating an automated system to capture high-quality UFO data with multiple forms of verification.

Why This Matters:

• Most UFO footage is low quality and lacks supporting data, making it hard to verify or analyze.
• With multiple data points (video, EM fields, thermal imaging, etc.), we can establish patterns and eliminate false positives.
• The system runs 24/7, capturing anomalies that human observers might miss.

When a potential unidentified object is detected, the system will:

  1. Record high-resolution footage from initial detection to departure.
  2. Cross-reference with real-time flight data via FlightAware and ADS-B Exchange to rule out known aircraft.
  3. Generate a comprehensive event package with timestamp-matched sensor readings, weather conditions, and more.

Each event will be stored in its own uniquely tagged folder, making it easy to analyze patterns and share findings.

Core Components:

• 4K Reolink PTZ Camera 360 degree: Mounted upside-down for a full view of the sky with AI object detection powered by YOLO.
• RM3100 Magnetometer: For detecting electromagnetic anomalies.
• Thermal Imaging Camera: Adds thermal verification to detections.
• LoRa Receiver: Links magnetic anomalies to approximate sky reference points.
• Raspberry Pi 4: Runs the entire system, manages data collection, and performs real-time analysis.

What Makes This System Unique?

1.  Multi-sensor approach: Not just video, but electromagnetic and thermal data for better verification.
2.  AI-powered detection: Reduces human error and bias.
3.  24/7 operation: Ensures no object goes unnoticed.
4.  Open data sharing: All findings will be posted here, raw and unedited, for transparency.

Progress So Far:

• ✅ Base system assembled and weatherproofed.
• ✅ Basic object detection working.
• 🔄 Magnetic sensor calibration in progress.
• 🔄 Initial test runs underway.

Next Steps:

1.  Adding a smart telescope with auto-tracking to zoom in on detected objects.
2.  Implementing machine learning for pattern recognition.
3.  Setting up a public data repository for all findings.

Community Input Needed:

This is still a work in progress, and I’m learning as I go. If anyone has expertise in:

  1. Optimizing Raspberry Pi programming for multi-sensor systems.
  2. Integrating sensors and syncing data for better correlation.
  3. Data analysis methods for anomaly detection.
  4. I’d like the community to name this project. “SkyWatch” or something haha? I’d like the community to decide since it’s supposed to be for everyone. (Including me obviously).

Please feel free to comment or message me. I’ll share any interesting findings right here on the subreddit. Also, I live in NJ.