AI-based real-time travel itinerary automatic generation system and method

Abstract

The present invention provides a technology that automatically generates an optimal travel itinerary tailored to a traveler's budget and preferences by utilizing AI and real-time data analysis. It analyzes the budget, schedule, accommodation, and activity preferences entered by the traveler to provide a personalized itinerary recommendation function that reflects data such as real-time price fluctuations, traffic, weather, and congestion levels, and includes an automatic adjustment function when the itinerary is changed.

Description

Technology Field

[0001] The present invention relates to a system and method for automatically optimizing a user's travel itinerary and budget by utilizing artificial intelligence (AI) and big data analysis, and includes technologies such as a travel recommendation engine, real-time data analysis, and automatic generation of a user-customized itinerary. Background Technology

[0002] Existing travel itinerary planning services cause inconvenience as users must search for and combine schedules individually, and travel package products also make it difficult to create personalized itineraries by providing pre-determined courses. Furthermore, user convenience is low because they do not consider real-time price fluctuations or booking availability. To solve these problems, the present invention provides a technology for recommending customized itineraries based on real-time data. The problem to be solved

[0003] This invention is a technology that automatically generates an optimal travel itinerary tailored to a traveler's budget and preferences by utilizing AI and real-time data. It provides a function that automatically recommends a personalized itinerary by analyzing the budget, schedule, accommodation, and activity preferences entered by the traveler, while reflecting real-time price fluctuations, traffic, weather, and congestion levels.

[0004] Existing travel itinerary planning services require travelers to search for and combine information themselves, which consumes a significant amount of time and effort, and standardized travel package products make it difficult to recommend personalized itineraries. Furthermore, they do not consider real-time price fluctuations or booking availability, resulting in low user convenience and making it difficult to efficiently utilize the travel budget. To solve these problems, the present invention provides a real-time data-based automatic travel itinerary optimization technology. means of solving the problem

[0005] The present invention consists of the following elements:

[0006] User input module: Receives input for budget, schedule, preferred destinations, accommodation type, etc.

[0007] Data Collection and Analysis Module: Collects and analyzes real-time data such as flight tickets, accommodation prices, traffic, and weather.

[0008] AI Schedule Optimization Engine: Automatically generates user-customized travel itineraries through machine learning and reinforcement learning algorithms.

[0009] Real-time Schedule Adjustment Module: Automatically adjusts the schedule in the event of unexpected variables such as aircraft delays or reservation cancellations.

[0010] User Interface (UI): Schedules can be viewed and modified on web and mobile applications. Effects of the invention

[0011] It can eliminate the hassle of users having to manually search for and combine schedules.

[0012] You can reduce costs through real-time price comparison and optimized budget allocation.

[0013] The schedule can be automatically adjusted in response to unexpected situations during the trip (weather changes, reservation changes, etc.).

[0014] Provides user-customized recommendation services through AI learning.

[0015] We continuously improve the accuracy of itinerary recommendations by reflecting user feedback after the trip. Brief explanation of the drawing

[0016] Figure 1 is an overall configuration diagram of an AI-based automatic travel itinerary generation system. Figure 2 is a flowchart of the user input and real-time data collection of the present invention. Figure 3 is an example diagram of the learning and optimization process of an AI recommendation engine. Figure 4 is an example diagram of the real-time schedule adjustment and update process. Specific details for implementing the invention

[0017] The model applies a deep learning-based travel recommendation algorithm.

[0018] Data integration utilizes APIs from global OTAs (e.g., Booking.com, Expedia).

[0019] UI / UX Design: Provides intuitive schedule editing functions.

[0020] The real-time optimization feature reflects unexpected variables such as flight delays and accommodation changes. Explanation of the symbols

[0021] 100: User device (smartphone, tablet, web application) 110: Data Analysis and AI Recommendation Engine 120: Real-time Price Fluctuation and Reservation Availability Check Module 130: Schedule Adjustment and Update Module

Claims

Claim 1 It is an AI-based system that analyzes user input data to automatically generate real-time optimized travel itineraries. Claim 2 It is a schedule optimization algorithm that reflects real-time price fluctuations, availability, traffic, and weather data. Claim 3 It includes features that automatically adjust and recommend the best alternative when the travel itinerary changes.

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