๐ŸŒŸ 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.

๐ŸŽฏ 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

๐Ÿ—๏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

๐Ÿ“‹ 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

๐Ÿ› ๏ธ Technology Stack

ComponentTechnology
ApplicationRust, egui, wgpu
Build SystemBuildroot / Yocto
KernelLinux 6.x + PREEMPT_RT
Init Systemsystemd (minimal) or s6
FilesystemSquashFS + OverlayFS
Bootloadersystemd-boot / GRUB2
ContainersPodman (optional)

๐Ÿ”ง 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

๐Ÿ“ Project Structure

glowbarn-os/
โ”œโ”€โ”€ Cargo.toml              # Rust workspace manifest
โ”œโ”€โ”€ hal/                    # Hardware Abstraction Layer (Rust)
โ”‚   โ”œโ”€โ”€ Cargo.toml
โ”‚   โ”œโ”€โ”€ src/
โ”‚   โ”‚   โ”œโ”€โ”€ lib.rs          # Core traits & HardwareManager
โ”‚   โ”‚   โ”œโ”€โ”€ i2c.rs          # I2C sensors
โ”‚   โ”‚   โ”œโ”€โ”€ spi.rs          # SPI devices
โ”‚   โ”‚   โ”œโ”€โ”€ gpio.rs         # GPIO control
โ”‚   โ”‚   โ”œโ”€โ”€ usb.rs          # USB enumeration
โ”‚   โ”‚   โ”œโ”€โ”€ audio.rs        # Audio capture
โ”‚   โ”‚   โ”œโ”€โ”€ camera.rs       # Camera/thermal
โ”‚   โ”‚   โ””โ”€โ”€ sdr.rs          # Software-defined radio
โ”‚   โ””โ”€โ”€ examples/
โ”œโ”€โ”€ sensors/                # Sensor Fusion Library (Rust)
โ”‚   โ”œโ”€โ”€ Cargo.toml
โ”‚   โ””โ”€โ”€ src/
โ”‚       โ”œโ”€โ”€ lib.rs          # Event types
โ”‚       โ”œโ”€โ”€ fusion.rs       # Multi-sensor fusion
โ”‚       โ”œโ”€โ”€ anomaly.rs      # Anomaly detection
โ”‚       โ”œโ”€โ”€ recording.rs    # Session recording
โ”‚       โ””โ”€โ”€ triggers.rs     # Trigger automation
โ”œโ”€โ”€ app/                    # Application (Rust)
โ”‚   โ”œโ”€โ”€ Cargo.toml
โ”‚   โ””โ”€โ”€ src/
โ”‚       โ”œโ”€โ”€ main.rs         # Daemon
โ”‚       โ”œโ”€โ”€ cli.rs          # CLI tool
โ”‚       โ””โ”€โ”€ config.rs       # Configuration
โ”œโ”€โ”€ buildroot/              # Buildroot external tree
โ”‚   โ”œโ”€โ”€ board/glowbarn/     # Board-specific files
โ”‚   โ”œโ”€โ”€ configs/            # Defconfigs for targets
โ”‚   โ”œโ”€โ”€ package/            # Custom packages
โ”‚   โ””โ”€โ”€ overlay/            # Root filesystem overlay
โ”œโ”€โ”€ kernel/                 # Kernel patches and configs
โ”œโ”€โ”€ firmware/               # Firmware blobs (if needed)
โ”œโ”€โ”€ tools/                  # Build and deployment tools
โ”œโ”€โ”€ docs/                   # Documentation
โ””โ”€โ”€ tests/                  # Integration tests

๐ŸŽฏ Target Platforms

PlatformArchitectureStatus
Generic x86_64x86_64Planned
Raspberry Pi 4/5ARM64Planned
Raspberry Pi Zero 2WARM64Planned
Intel NUCx86_64Planned
NVIDIA Jetson NanoARM64Future

๐Ÿ” 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

๐Ÿ“œ License

GNU General Public License v3.0 (GPLv3)


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:

โ”œโ”€โ”€ hal/                    # Hardware Abstraction Layer
โ”‚   โ”œโ”€โ”€ src/
โ”‚   โ”‚   โ”œโ”€โ”€ lib.rs          # Core HAL traits & HardwareManager
โ”‚   โ”‚   โ”œโ”€โ”€ i2c.rs          # I2C: HMC5883L, BME280, MLX90614
โ”‚   โ”‚   โ”œโ”€โ”€ spi.rs          # SPI: ADS1256, MCP3008
โ”‚   โ”‚   โ”œโ”€โ”€ gpio.rs         # GPIO: PIR, laser grid, PWM
โ”‚   โ”‚   โ”œโ”€โ”€ usb.rs          # USB: serial, HID devices
โ”‚   โ”‚   โ”œโ”€โ”€ audio.rs        # Audio: EVP, infrasound, spirit box
โ”‚   โ”‚   โ”œโ”€โ”€ camera.rs       # Camera: V4L2, thermal, night vision
โ”‚   โ”‚   โ””โ”€โ”€ sdr.rs          # SDR: RTL-SDR, EMF analyzer
โ”‚   โ””โ”€โ”€ examples/
โ”‚       โ”œโ”€โ”€ sensor_demo.rs
โ”‚       โ””โ”€โ”€ emf_scanner.rs
โ”œโ”€โ”€ sensors/                # Sensor Fusion & Analysis
โ”‚   โ””โ”€โ”€ src/
โ”‚       โ”œโ”€โ”€ lib.rs          # Event types, ParanormalEvent
โ”‚       โ”œโ”€โ”€ fusion.rs       # FusionEngine, multi-sensor correlation
โ”‚       โ”œโ”€โ”€ anomaly.rs      # Z-score, EMA, CUSUM, IsolationForest
โ”‚       โ”œโ”€โ”€ recording.rs    # EventRecorder, session management
โ”‚       โ””โ”€โ”€ triggers.rs     # TriggerManager, automated responses
โ””โ”€โ”€ app/                    # Main Application
    โ””โ”€โ”€ src/
        โ”œโ”€โ”€ main.rs         # Daemon entry point
        โ”œโ”€โ”€ cli.rs          # CLI management tool
        โ””โ”€โ”€ 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.