What it does
Solves 81% female travelers' safety anxiety via real-time SOS with police coordination, ID-verified companion matching, and AI route planning. Community features enable shared itineraries and UGC travelogues.
Your inspiration
Research revealed 81% prioritize safety, yet no platform combined robust protection with trusted social interaction. Inspired by women's need for "travel buddies" with verified identities, we created the dual-core "GPS safety net + credit-based matching" system. Real-world scenarios (e.g., harassment alerts, wilderness safety) drove feature designs.
How it works
Safety System: SOS Alert: Triggers GPS location sharing with local police within 8s (patent-pending quick-response protocol) Adaptive Safety DB: Delivers scenario-specific guides (urban/wilderness) via machine learning analyzing user location/time Trust Network: Companion Matching: ID verification + behavioral credit scoring (e.g., trip completion rate) UGC Authenticity: Blockchain-timestamped travelogues to prevent fake content AI Planning: AR-enhanced Navigation: Overlays safety zones/police stations on camera view Tech Stack: Android Jetpack Compose, AWS Location Service, TensorFlow Lite
Design process
Phase 1: Research & Definition Analyzed 2023-2024 travel data (Fig.1): 81% female travelers prioritize safety, yet 76% felt existing apps lacked real-time protection. Defined core user persona: Solo female travelers (25-35yo) needing instant SOS and trust-based companionship. Phase 2: Solution Framework Developed dual-core architecture (Fig.1 right): ▶︎ Safety Core: GPS-triggered police alerts (patent-pending <8s response) ▶︎ Social Core: ID + behavioral scoring (e.g. trip completion rate) for companion matching Storyboarded critical scenarios: harassment alert workflow, wilderness rescue guidance. Phase 3: Prototyping & Testing Built interactive prototype (Fig.2) with 3 key flows: ▶︎ SOS System: One-tap emergency with location auto-sharing ▶︎ Companion Hub: Credit-verified profile browsing ▶︎ AR Planner: Safety POI overlay on live camera view Iterated 3 versions based on 40+ user tests, optimizing SOS activation time by 62%. Phase 4: UI Implementation Established design system (Fig.2): ▶︎ Primary color: #22A9A3 (safety psychology verified) ▶︎ Emergency components: Red accent with haptic feedback
How it is different
Gender-focused SOS: Only product with direct police coordination tech in China Behavioral Credit: Analyzes 12+ data points (e.g., emergency button usage) for companion reliability AR Safety Integration: Real-time hazard alerts via camera view (e.g., dark alley warnings) Single-workflow Design: Unifies planning/safety/social features reducing 73% app-switching
Future plans
AI Risk Prediction: Analyze travel patterns to pre-alert dangers Local Guardian Network: Partner with female-owned businesses as safe havens AR Navigation: Overlay safety info on real-world views via camera Eco-expansion: Integrate female-centric products/services marketplace
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