Offline_SOS_System

Pub.dev Package: Link GitHub Repository: Link Imagine getting into a serious car crash in a remote area-a mountain pass, a highway dead zone, or a rural road with zero cell signal. You open your safety app, or its automated background trigger fires... only to hang indefinitely because it relies on a cloud API to process sensor data or verify the crash. That single point of failure bugged me for months. Emergency safety features shouldn’t depend on a stable 5G connection. If an engine can detect a crash instantly via onboard physics, our software should be able to do the same on-device. So, I built and open-sourced offline_sos_system -a pure Dart, 100% offline crash detection engine powered by on-device TensorFlow Lite. 💡 Why Build This? Most existing Flutter solutions for safety or impact detection suffer from one of three issues: - Cloud Dependency: They stream raw accelerometer data to a backend server for ML inference. (Fails in dead zones). - Simple Threshold Logic: They rely solely on basic G-force > X spikes, leading to massive false-positive rates (like dropping your phone on a table or hitting a pothole). - Heavy Native Dependencies: They require complex, platform-specific iOS/Android native code bindings that are difficult to maintain or integrate into clean Dart architectures. I wanted a solution that was pure Dart/Flutter at the developer layer, handled complex multi-axis motion patterns via Edge AI, and never made a single network request. ⚙️ How It Works Under the Hood The package handles the entire pipeline locally on the device: - Continuous Telemetry Buffering: Ingests high-frequency raw data from the device’s accelerometer and gyroscope sensors. - Signal Preprocessing & Feature Extraction: Filters noise, down-samples vector streams, and converts raw hardware readings into structured tensor windows. - On-Device Inference: Runs the preprocessed window through an embedded TensorFlow Lite model using tflite_flutter . - Headless Event Stream: Outputs a clean, reactive stream of crash confidence events-allowing your application logic to decide what happens next (e.g., triggering a local alarm, queuing an offline SMS, or fetching last-known GPS coordinates). 🛠️ Quick Implementation Here is how simple it is to initialize and listen for crash events in Flutter: dart import 'package:offline_sos_system/offline_sos_system.dart'; void main() async { WidgetsFlutterBinding.ensureInitialized(); // Initialize the offline SOS engine final sosEngine = OfflineSosSystem(); await sosEngine.initialize(); // Listen to real-time crash detection events sosEngine.crashStream.listen((CrashEvent event) { if (event.isCrashDetected) { print('CRASH DETECTED!'); print('Confidence Score: ${event.confidence}'); print('Impact Force: ${event.gForce}G'); // Trigger your app's local emergency protocols here } }); // Start monitoring sensor telemetry await sosEngine.startMonitoring(); } Top comments (1) Great insight!!!!