🧩Core Technology

1. Insurance Enrollment, Payment, and Compensation Mechanisms

Insurance Enrollment:

  • Automatic Enrollment: When users enter their flight information into the DApp, smart contracts automatically handle the insurance enrollment process.

  • Condition Setting: Enrollment conditions (e.g., delay times, compensation amounts) are recorded on the blockchain, ensuring transparency. Payment

  • Automatic Payment: If users select paid insurance, the smart contract automatically processes the payment using ORB coins or other cryptocurrencies.

  • Real-Time Payment Confirmation: Upon payment completion, insurance enrollment is confirmed immediately, and this process is recorded on the blockchain. Compensation Processing

  • Automatic Compensation: When conditions such as flight delays or cancellations are met, smart contracts automatically initiate the compensation process.

  • Immediate and Transparent Processing: Compensation is processed without delays and recorded on the blockchain. ORB Coin and Other Cryptocurrency Integration

2. ORB Coin

  • Compensation Tool: ORB coins are used as the primary means for compensating insurance subscribers.

  • Platform Liquidity: ORB coins are traded within the platform and can be used to purchase additional insurance products and other services.

3. Integration with Other Cryptocurrencies

  • Payment and Compensation: Various cryptocurrencies, including Bitcoin and Ethereum, are integrated as payment and compensation methods.

  • Scalability: The platform plans to integrate more cryptocurrencies in the future. Security and Transparency Design

4. Blockchain-Based

  • Immutable Records: Records of smart contracts are stored on the blockchain and cannot be altered.

  • Automated Processing: Contracts are executed automatically without intermediaries, enhancing speed and reliability.

5. Enhanced Security

  • Encryption: Data and transaction histories are encrypted, and smart contract code undergoes security audits.

  • Decentralization: Smart contracts run on a decentralized network, eliminating single points of failure. Data Collection Methods

6. User-Entered Data

  • Flight Information: Collects flight information entered by users. Check-In/Check-Out Data: Collects check-in and check-out information provided by users.

  • Surveys and Feedback: Collects travel-related surveys and feedback.

7. Automated Data Collection

  • Real-Time Flight Status: Gathers real-time flight status through airport and airline APIs. User Behavior Data: Automatically collects user behavior data within the DApp.

8. External Data Sources

  • Weather Information: Collects weather data from external sources to predict potential flight delays.

  • Travel-Related Data: Collects external data on travel trends and price fluctuations. Data Security and Privacy

9. Data Encryption

  • Encryption in Transit: Protects data transmission using SSL/TLS encryption protocols. Encryption at Rest: Data stored in databases is encrypted.

10. Access Control

  • Permission Management: Minimizes and manages data access permissions.

  • Anonymization and Pseudonymization: Anonymizes or pseudonymizes personal identifiers for analysis.

11. Compliance with Privacy Regulations

  • GDPR Compliance: Data collection and processing comply with GDPR and other regulations.

  • Data Retention: Data is retained only for the necessary period and securely deleted when no longer needed. AI-Based Analysis and Personalized Recommendation System

12. AI/ML Model Training WNDJFMF 먁

  • Data Preprocessing: Prepares data for AI/ML model training. Behavior Pattern Analysis: Analyzes user behavior data to learn preferences.

  • Clustering and Segmentation: Groups users based on similar behavior patterns.

13. Personalized Recommendations

  • Travel Recommendations: Provides travel destination suggestions based on users' past records and behavior patterns.

  • Insurance Product Recommendations: Analyzes travel routes and risks to recommend suitable insurance products.

14. Lowest Fare Flight Recommendation System

Price Prediction Models

  • Historical Data Analysis: Analyzes past data to predict price fluctuations.

  • Real-Time Price Monitoring: Tracks flight price changes in real-time.

15. Alert System

  • Price Alerts: Provides notifications when prices drop to predefined levels.

  • Recommendation Timing: Suggests the optimal times for purchases.

16. User Customization

  • Preferred Airlines and Routes: Recommends the lowest fares based on user preferences.

  • Various Filter Options: Offers filter options to support personalized recommendations. User Experience and Interface Design

17. Personalized User Experience

  • Custom Dashboards: Allows users to customize dashboards according to their preferences. Real-Time

  • Feedback Loop: Incorporates user feedback instantly to continuously improve the service. This project aims to securely collect and protect data, provide personalized travel experiences through AI-based analysis, and maximize user convenience with a lowest fare flight recommendation system and intuitive UI/UX design.

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