🌟 GlowBarn OS - Paranormal Research Operating System

A specialized, lightweight operating system for paranormal investigation, environmental monitoring, and multi-modal anomaly detection research.

🎯 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

🏗️ 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

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📋 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

🛠️ 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)

🔧 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

📁 Project Structure

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

🎯 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

🔐 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

📜 License

GNU General Public License v3.0 (GPLv3)

🔗 Related Projects

• glowbarn-rs - Main application
• glowbarn - Original Python prototype

---

Status: � 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:

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

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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

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Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

GNU General Public License v3.0 - see LICENSE for details.