RapidQuake is a Spring Boot web platform for earthquake awareness, user safety confirmation, family coordination, and controlled emergency operations.
It is designed for simple deployment, privacy-first location handling, and responsive use across desktop and mobile devices.
- Live earthquake map with USGS feed integration
- User safety confirmation flow during emergency broadcasts
- Trapped-user reporting with rescue workflow
- Family safety network for connected account visibility
- Role-based access for public users and admin staff
- Privacy guardrails: admin location visibility is restricted to trapped users only
- Backend: Spring Boot, Spring Security, Spring Data JPA, Thymeleaf
- Frontend: Thymeleaf templates, Bootstrap, Vanilla JavaScript, Leaflet
- Database: H2 (local/dev) with optional migration path to MySQL
- Build tool: Maven
RapidQuake stores operational location data in the database for emergency features and does not rely on persistent browser storage for critical safety state.
- Normal condition: admin does not see user live location
- Emergency condition: location is shown to admin only for users marked as trapped
- Permission denied flow: app falls back to saved/network-based location hint where available
- Java 17+
- Maven 3.9+
mvn spring-boot:runDefault app URL:
Main runtime settings are in:
src/main/resources/application.properties
Typical deployment variables to externalize:
- datasource URL / username / password
- active profile
- logging levels
- server port
- Development can run with embedded database settings
- For production, use a managed MySQL/PostgreSQL instance and externalized credentials
- Keep schema migrations under version control (Flyway/Liquibase recommended)
mvn testRecommended minimal production path:
- Build artifact:
mvn clean package- Run packaged app:
java -jar target/*.jar- Place behind reverse proxy (Nginx/Caddy) with HTTPS
- Use environment variables for secrets (never commit credentials)
- Enable periodic backups for production database
- CSRF protection is enabled for authenticated form/API actions
- Role checks separate admin and user workflows
- Admin endpoints should only be exposed through authenticated channels
src/main/java/com/rapidquake/— backend controllers, services, repositories, modelssrc/main/resources/templates/— Thymeleaf templatessrc/main/resources/static/— CSS/JS/imagessrc/test/— integration and security tests
- UI is optimized to remain responsive on mobile, tablet, and desktop
- Map interactions include button fallback for devices with gesture/trackpad inconsistencies
- Emergency workflows are designed to avoid requiring page refresh for core user actions
This project currently has no explicit open-source license file.
Add a LICENSE file before public distribution.
Shifting the paradigm from reactive detection to proactive prediction.
RapidQuake is a next-generation safety platform designed to predict localized seismic risks using Artificial Intelligence. By analyzing real-time geolocation data against historical geological patterns, RapidQuake aims to provide users with critical lead time before an earthquake occurs, rather than just alerting them after the shaking has started.
Traditional earthquake warning systems are fundamentally reactive.
- They rely on physical sensors to detect ground motion that has already begun.
- They race to transmit warnings to nearby populations.
- For people near the epicenter, this often results in a "blind zone" where the alert arrives too late—or simultaneously with the destructive waves.
RapidQuake takes a proactive approach. Instead of waiting for the ground to shake, the system functions as a continuous risk assessment engine.
It calculates the probability of a seismic event occurring at a user's specific location in the immediate future. If the calculated risk exceeds a safety threshold, the system issues a preemptive High-Risk Advisory, allowing users to take protective action (Drop, Cover, and Hold On) before the event manifests.
Risk levels can vary significantly even within the same city. RapidQuake monitors the user's exact geolocation coordinates to generate personalized risk scores rather than broad, region-wide broadcasts.
At the core of the system is a machine learning classifier trained on vast datasets of historical seismic activity. It evaluates complex patterns to determine the likelihood of an earthquake, outputting a probability score (0% - 100%) for the current location.
Time is the most critical resource in disaster management. The system is architected for low latency, ensuring that from the moment a high-risk pattern is identified, an alert reaches the user's device in under two seconds.
To prevent panic and alert fatigue, the system utilizes intelligent filtering. Alerts are only distributed to users within a relevant impact radius based on the predicted magnitude of the event (e.g., a 20km radius for minor tremors vs. a 500km radius for major events).
Trust is paramount. RapidQuake includes an independent validation subsystem that continuously polls official USGS (United States Geological Survey) data. It cross-references confirmed earthquakes with the system's past predictions to audit accuracy and refine the AI model over time.
- Location Tracking: The system securely receives the user's current position.
- Inference: These coordinates are fed into the AI model, which analyzes geological stability in that sector.
- Decision Making:
- Low Risk: The system continues monitoring silently.
- High Risk: The system triggers an immediate alert event.
- Notification: A visual and auditory advisory is pushed to the user's interface.
- Validation: Post-event, the system compares its prediction against official government data to measure success.
- Life Safety: Providing seconds or minutes of lead time allows individuals to move away from glass, secure heavy objects, or exit dangerous structures.
- Infrastructure Protection: Future iterations could automate shutting down gas lines, stopping trains, or pausing heavy machinery based on high-probability forecasts.
- Data Science Application: Demonstrates the viable application of Supervised Machine Learning in the field of disaster management and geology.
Email: arjunpatil011@gmail.com
Disclaimer: RapidQuake is an experimental project developed for educational and research purposes. It is not intended to replace official government emergency alert systems.