๐ GlowBarn OS - Paranormal Research Operating System
January 26, 2026 ยท View on GitHub
A specialized, lightweight operating system for paranormal investigation, environmental monitoring, and multi-modal anomaly detection research.
๐ฏ Project Vision
GlowBarn OS is a custom Linux-based operating system designed to run the GlowBarn Paranormal Detection Suite as a first-class citizen. Built for deployment on:
- Live USB - Boot on any x86_64 machine without installation
- Raspberry Pi - ARM-based field deployment
- Lightweight Machines - Intel NUC, mini PCs, old laptops
- Dedicated Research Stations - Purpose-built detection hardware
๐๏ธ Architecture
flowchart TB
subgraph stack["GlowBarn OS Stack"]
subgraph app["Application Layer"]
A1[Visual Console - egui native]
A2[Sensor Fusion Engine]
A3[Real-time Analysis]
A4[Security & Encryption]
end
subgraph framework["Framework Layer"]
F1[Hardware Abstraction Layer - HAL]
F2[Sensor Drivers - I2C, SPI, GPIO, USB]
F3[GPU Compute Interface - wgpu/Vulkan]
F4[Network Stack - MQTT, WebSocket, BLE]
end
subgraph firmware["Firmware Layer"]
W1[Custom initramfs]
W2[Minimal systemd services]
W3[Real-time kernel - PREEMPT_RT]
W4[Secure boot chain]
end
subgraph base["Base System"]
B1[Linux Kernel 6.x - custom config]
B2[Musl libc / glibc]
B3[BusyBox / CoreUtils]
B4[SquashFS root - read-only, verified]
end
end
app --> framework
framework --> firmware
firmware --> base
๐ Roadmap
Phase 1: GlowBarn Application (CURRENT)
- Core engine architecture
- 50+ sensor type implementations
- Analysis algorithms (entropy, anomaly detection)
- Multi-sensor fusion (Bayesian, Dempster-Shafer)
- Security module (AES-256-GCM, Argon2id)
- Visual console UI
- Streaming (MQTT, WebSocket)
- Compilation & testing
- Code signing
- GitHub release
Phase 2: Hardware Abstraction Layer
- I2C sensor interface (HMC5883L, BME280, MLX90614)
- SPI sensor interface (ADS1256, MCP3008)
- GPIO control (PIR, laser grid, PWM)
- USB device enumeration (serial, HID)
- Audio capture (EVP, infrasound, spirit box)
- Camera/thermal imaging (V4L2, FLIR, night vision)
- Software-defined radio (RTL-SDR, EMF analyzer)
Phase 3: Sensor Fusion Library
- Statistical baseline tracking
- Z-score anomaly detection
- Multi-sensor event correlation
- Sliding window analysis
- EMA trend detection
- CUSUM change point detection
- Isolation Forest multivariate detection
- Pattern matching
Phase 4: Application Framework
- Main application daemon
- CLI management tool
- Event recording & playback
- Trigger system
- Configuration management
- Session export
Phase 5: Firmware Foundation
- Custom Linux kernel config
- PREEMPT_RT patches for real-time
- Minimal initramfs
- SquashFS root filesystem
- Overlay filesystem for persistence
- Secure boot integration
Phase 4: Live USB Image
- ISO generation pipeline
- UEFI + Legacy BIOS boot
- Persistence partition support
- Auto-detection of sensors
- Network configuration UI
- First-boot wizard
Phase 5: Raspberry Pi Support
- ARM64 cross-compilation
- Pi-specific kernel config
- GPIO sensor integration
- Pi Camera support
- Pi Sense HAT integration
- SD card image generation
Phase 6: Distribution
- Package repositories (APT, RPM, Pacman)
- OTA update mechanism
- Telemetry (opt-in)
- Community sensor plugins
- Research data sharing network
๐ ๏ธ Technology Stack
| Component | Technology |
|---|---|
| Application | Rust, egui, wgpu |
| Build System | Buildroot / Yocto |
| Kernel | Linux 6.x + PREEMPT_RT |
| Init System | systemd (minimal) or s6 |
| Filesystem | SquashFS + OverlayFS |
| Bootloader | systemd-boot / GRUB2 |
| Containers | Podman (optional) |
๐ง Development Setup
# Clone the repository
git clone https://github.com/bad-antics/glowbarn-os.git
cd glowbarn-os
# Install build dependencies (Debian/Ubuntu)
sudo apt install build-essential git wget cpio unzip rsync bc \
libncurses5-dev libssl-dev flex bison
# Initialize Buildroot
make setup
# Configure for target
make menuconfig
# Build the image
make build
# Create bootable USB
sudo dd if=output/glowbarn-os.img of=/dev/sdX bs=4M status=progress
๐ Project Structure
glowbarn-os/
โโโ Cargo.toml # Rust workspace manifest
โโโ hal/ # Hardware Abstraction Layer (Rust)
โ โโโ Cargo.toml
โ โโโ src/
โ โ โโโ lib.rs # Core traits & HardwareManager
โ โ โโโ i2c.rs # I2C sensors
โ โ โโโ spi.rs # SPI devices
โ โ โโโ gpio.rs # GPIO control
โ โ โโโ usb.rs # USB enumeration
โ โ โโโ audio.rs # Audio capture
โ โ โโโ camera.rs # Camera/thermal
โ โ โโโ sdr.rs # Software-defined radio
โ โโโ examples/
โโโ sensors/ # Sensor Fusion Library (Rust)
โ โโโ Cargo.toml
โ โโโ src/
โ โโโ lib.rs # Event types
โ โโโ fusion.rs # Multi-sensor fusion
โ โโโ anomaly.rs # Anomaly detection
โ โโโ recording.rs # Session recording
โ โโโ triggers.rs # Trigger automation
โโโ app/ # Application (Rust)
โ โโโ Cargo.toml
โ โโโ src/
โ โโโ main.rs # Daemon
โ โโโ cli.rs # CLI tool
โ โโโ config.rs # Configuration
โโโ buildroot/ # Buildroot external tree
โ โโโ board/glowbarn/ # Board-specific files
โ โโโ configs/ # Defconfigs for targets
โ โโโ package/ # Custom packages
โ โโโ overlay/ # Root filesystem overlay
โโโ kernel/ # Kernel patches and configs
โโโ firmware/ # Firmware blobs (if needed)
โโโ tools/ # Build and deployment tools
โโโ docs/ # Documentation
โโโ tests/ # Integration tests
๐ฏ Target Platforms
| Platform | Architecture | Status |
|---|---|---|
| Generic x86_64 | x86_64 | Planned |
| Raspberry Pi 4/5 | ARM64 | Planned |
| Raspberry Pi Zero 2W | ARM64 | Planned |
| Intel NUC | x86_64 | Planned |
| NVIDIA Jetson Nano | ARM64 | Future |
๐ Security Features
- Secure Boot - Signed bootloader and kernel
- dm-verity - Verified root filesystem
- Full Disk Encryption - LUKS2 for data partitions
- Measured Boot - TPM integration
- Minimal Attack Surface - No unnecessary services
- Automatic Updates - Signed OTA updates
๐ License
GNU General Public License v3.0 (GPLv3)
๐ Related Projects
- glowbarn-rs - Main application
- glowbarn - Original Python prototype
Status: ๏ฟฝ Active Development - Rust HAL, Sensors, and Application crates complete
Last Updated: 2026-01-26
Rust Workspace
The core GlowBarn system is implemented as a Rust workspace with three crates:
โโโ hal/ # Hardware Abstraction Layer
โ โโโ src/
โ โ โโโ lib.rs # Core HAL traits & HardwareManager
โ โ โโโ i2c.rs # I2C: HMC5883L, BME280, MLX90614
โ โ โโโ spi.rs # SPI: ADS1256, MCP3008
โ โ โโโ gpio.rs # GPIO: PIR, laser grid, PWM
โ โ โโโ usb.rs # USB: serial, HID devices
โ โ โโโ audio.rs # Audio: EVP, infrasound, spirit box
โ โ โโโ camera.rs # Camera: V4L2, thermal, night vision
โ โ โโโ sdr.rs # SDR: RTL-SDR, EMF analyzer
โ โโโ examples/
โ โโโ sensor_demo.rs
โ โโโ emf_scanner.rs
โโโ sensors/ # Sensor Fusion & Analysis
โ โโโ src/
โ โโโ lib.rs # Event types, ParanormalEvent
โ โโโ fusion.rs # FusionEngine, multi-sensor correlation
โ โโโ anomaly.rs # Z-score, EMA, CUSUM, IsolationForest
โ โโโ recording.rs # EventRecorder, session management
โ โโโ triggers.rs # TriggerManager, automated responses
โโโ app/ # Main Application
โโโ src/
โโโ main.rs # Daemon entry point
โโโ cli.rs # CLI management tool
โโโ config.rs # AppConfig
Building
# Build release binaries
cargo build --release
# Binaries are in target/release/
# - glowbarn (daemon)
# - glowbarn-cli (CLI tool)
CLI Usage
# Show system information
glowbarn-cli info
# List recording sessions
glowbarn-cli sessions
# Show events from a session
glowbarn-cli events <session-id>
# Export session to JSON
glowbarn-cli export <session-id> --format json
# Generate sample config
glowbarn-cli config > /etc/glowbarn/config.toml
Configuration
# /etc/glowbarn/config.toml or ~/.config/glowbarn/config.toml
location = "Investigation Site Alpha"
session_name = "session_001"
data_directory = "/var/lib/glowbarn/data"
poll_interval_ms = 100
anomaly_threshold = 3.0
min_confidence = 0.7
auto_record = true
Quick Start
Prerequisites
- Linux build system (Ubuntu 22.04+ recommended)
- 20GB+ free disk space
- 4GB+ RAM
Build Steps
# Install dependencies
make deps
# Setup Buildroot
make setup
# Build for Raspberry Pi 4
make build-rpi4
# Or build for x86_64 PC
make build-x86
Write to SD Card
sudo dd if=buildroot-2024.02.9/output/images/glowbarn-os-rpi4.img of=/dev/sdX bs=4M status=progress
Default Login
- Username: root
- Password: paranormal
Access Web Dashboard
Open browser to: http://<device-ip>:8765
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
GNU General Public License v3.0 - see LICENSE for details.