Star Aristocracy

Non‑Intrusive Diagnostics for Modern Firearms

The Weapon Health Monitor v0.1 is a compact, external telemetry module designed to bring real‑time diagnostics, maintenance forecasting, and environmental awareness to small arms without modifying internal components or affecting reliability.

Built for field technicians, training programs, security organizations, and data‑driven armories, the module transforms a traditionally analog tool into a measurable platform.

Core Capabilities

• Shot Detection via Sensor Fusion

A built‑in IMU captures vibration and rotational signatures while a thermal sensor monitors heat cycles. Combined, they produce a highly accurate firing‑event classifier without interacting with the firearm’s internal mechanics.

• Environmental Exposure Logging

Temperature, humidity, and shock events are continuously recorded, creating a historical profile of wear conditions and corrosion risk.

• Predictive Maintenance Index

Using a weighted model of firing cycles, heat stress, and exposure conditions, the system calculates a live MaintenanceScore—a simple, readable indicator of equipment health.

• Modular Mounting Architecture

Attaches externally via Picatinny or M‑LOK clamps. No gunsmithing. No permanent changes.

• Data Export for Analysis

All telemetry is logged in standard CSV format and can be fed into:

• dashboards
• training analysis suites
• armory management tools
• custom analytics pipelines

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Technical Overview

• IMU: 6‑axis accelerometer/gyroscope
• Environment Suite: temperature + humidity
• Processor: microcontroller or SBC (ESP32 / Raspberry Pi Zero)
• Power: rechargeable cell
• Data Output: USB‑C or wireless (optional prototypes)
• Enclosure: polymer, weather‑resistant, low‑profile design

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Why It Matters

Firearms lack the diagnostic infrastructure that every modern machine—from drones to cars—relies on. Maintenance remains manual, reactive, and guess‑based.

The Weapon Health Monitor introduces:

• quantified wear
• clearer maintenance cycles
• actionable training feedback
• fleet‑level operational insight

It’s a step toward a future where armories operate with the same clarity as digital systems: measurable, trackable, predictable.

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Prototype Status

The v0.1 prototype includes:

• fully functional sensor fusion
• firing‑event classification
• environmental logging
• maintenance scoring algorithm
• CSV export and terminal visualization

Next iterations will focus on:

• on-device LED indicators
• encrypted wireless sync
• cloud dashboards
• expanded sensor suite

import time
import csv
from datetime import datetime
import random

# ---------------------------------------
# MOCK SENSOR READS (Replace with real libs)
# ---------------------------------------

def read_imu():
    # accel_x, accel_y, accel_z, gyro_x, gyro_y, gyro_z
    # Replace this with mpu6050 or mpu6886 library calls
    return {
        "accel": random.uniform(0.8, 1.2),     # vibration baseline
        "gyro": random.uniform(0.0, 1.5)       # rotational shock
    }

def read_env():
    # Replace with BME280 calls
    return {
        "temp": random.uniform(20, 45),        # °C
        "humidity": random.uniform(20, 90)     # %
    }

# ---------------------------------------
# FUSION + CLASSIFICATION
# ---------------------------------------

def is_firing_event(accel, gyro, temp):
    """
    Basic classification of firing using combined sensor thresholds.
    Tunable for real hardware.
    """
    return (
        accel > 1.5   # big vibration spike
        and gyro > 2  # rotation spike
        and temp > 30 # heat jump
    )

# ---------------------------------------
# MAIN PROGRAM LOOP
# ---------------------------------------

MaintenanceScore = 100.0
round_count = 0

print("Starting Weapon Health Monitor v0.1...")

with open("weapon_health_log.csv", "w", newline="") as f:
    writer = csv.writer(f)
    writer.writerow([
        "timestamp", "temp", "humidity", "accel", "gyro",
        "round_count", "MaintenanceScore"
    ])

    while True:
        env = read_env()
        imu = read_imu()
        
        accel = imu["accel"]
        gyro = imu["gyro"]
        temp = env["temp"]
        humidity = env["humidity"]

        # Detect firing
        if is_firing_event(accel, gyro, temp):
            round_count += 1
            MaintenanceScore -= 0.5  # fouling/wear
            print(f"[SHOT DETECTED] Total rounds: {round_count}")

        # Environmental wear modeling
        if temp > 40:
            MaintenanceScore -= 0.05

        if humidity > 70:
            MaintenanceScore -= 0.02  # corrosion risk

        # Floor limit
        MaintenanceScore = max(MaintenanceScore, 0)

        # Logging
        writer.writerow([
            datetime.now(), temp, humidity, accel, gyro,
            round_count, MaintenanceScore
        ])

        # Output to terminal
        print(f"T={temp:.1f}°C  H={humidity:.1f}%  Rounds:{round_count}  Health:{MaintenanceScore:.2f}")
        
        time.sleep(0.5)