offline_sos_system 0.0.5

A pure Dart, offline-first Flutter package for on-device crash and anomaly detection using hardware telemetry and TFLite.

Offline SOS System 🛡️

Edge AI • Zero-Latency Compute • 100% Offline Safety

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⚡ The Problem: Cloud Dependency is a Fatal Flaw

In critical emergencies, network infrastructure is often the first thing to fail. Traditional safety applications rely entirely on the cloud to process data and detect crashes, leading to fatal latencies or complete system failure when offline.

Offline SOS System revolutionizes application safety. By harnessing Edge AI and high-frequency hardware telemetry (accelerometer & gyroscope), this headless engine detects physical crashes and anomalies in real-time, 100% on-device. Zero ping. Zero cloud dependency. Maximum privacy.

✨ Futuristic Capabilities

• 🧠 Neural Telemetry: Processes raw hardware data locally through an advanced, bundled TensorFlow Lite (tflite_flutter) model.
• ⚡ Zero-Latency Compute: By bringing inference to the edge, anomalies are flagged in milliseconds.
• 🔌 Decoupled Architecture: Strictly headless. We handle the complex math and ML; your app handles the UI, GPS, or SMS dispatching.
• 📦 Bring Your Own Model: Seamlessly inject your own custom-trained .tflite model or fall back on our highly optimized default.

🚀 Instant Integration

We built this engine for maximum developer velocity. Instantiate the engine and start listening to the stream in under 3 lines of code.

1. Install

dependencies:
  offline_sos_system: ^0.0.2

2. Implement

import 'package:offline_sos_system/offline_sos_system.dart';

// 1. Initialize the Edge AI Engine
final SafePulseEngine engine = SafePulseEngine();

// 2. Listen for ultra-fast crash inferences
engine.onCrashDetected.listen((CrashEvent event) {
  print('💥 CRASH DETECTED at ${event.timestamp}!');
  print('📊 Confidence Probability: ${event.probability}');
  
  // Trigger your app's emergency UI, offline SMS, or siren here.
});

// 3. Start Telemetry Processing
await engine.start();

🛠️ Advanced Usage (Custom Models)

Trained a better model? Inject it instantly.

final customEngine = SafePulseEngine(
  customModelPath: 'assets/my_advanced_model.tflite'
);

🤝 Contributing

Welcome to the edge computing revolution. PRs, issues, and feature requests are highly appreciated to help push offline-first safety forward.