AI-Based Multi-User Chat for Collaborative Trip Planning
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Solution Overview
Problem
Conventional travel planning for group trips is inefficient and difficult due to the need for manual search and coordination among multiple travelers, lacking a timely and effective way to identify pertinent destinations and organize preferences.
Innovation Solution
A computing system with a chat interface and chatbot that facilitates a multi-user chat session, using machine learning to generate trip recommendations based on traveler inputs, and a separate trip board to organize selections and updates based on interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual search and coordination methods are used for group trip planning, then travelers can independently search for destinations and information, but the process becomes inefficient and time-consuming due to the need for coordinating multiple travelers' preferences and organizing planning progress
Solution Approach 1:
The system segments the trip planning process into distinct functional modules: preference collection, destination search, itinerary generation, and coordination management. Each module handles specific aspects of planning independently, allowing parallel processing of multiple travelers' requirements without bottlenecks in the overall workflow.
Solution Approach 2:
The patent introduces an intermediary system (the travel planning platform with AI assistant) that mediates between multiple travelers and travel service providers. This intermediary automatically collects preferences from all travelers, processes their requirements, coordinates suggestions, and manages planning progress, eliminating the need for travelers to manually coordinate with each other and significantly reducing coordination time.
2Adaptability or versatility
If multiple travelers coordinate their preferences and communication manually, then each traveler can express their desires and needs, but the complexity of organizing and storing planning progress increases significantly
Solution Approach 1:
The patent implements a universal trip planning platform that serves multiple functions simultaneously: collecting preferences from unlimited travelers, searching for destinations and services, generating personalized itineraries, storing planning progress, and enabling group coordination. This multi-functional system handles diverse traveler requirements through a single integrated interface, avoiding the need for multiple separate coordination tools and reducing overall system complexity.
Solution Approach 2:
The system creates digital copies of traveler preferences, planning progress, and itinerary suggestions that can be stored, replicated, and shared across all group members. These digital copies enable automatic synchronization of planning data, allowing any traveler to access and contribute to the collective planning progress without manual organization, thereby reducing the complexity of managing group planning information.
3Loss of information
If travelers search for destinations, excursions, and itineraries separately, then they can find specific travel information, but it becomes difficult to identify pertinent destinations and information in a timely and efficient manner
Solution Approach 1:
The patent implements preliminary action by having the system proactively search for and pre-process travel information (destinations, excursions, itineraries) based on collected traveler preferences before the group needs to make decisions. The AI assistant automatically generates preliminary itinerary suggestions and identifies pertinent destinations in advance, allowing travelers to review and refine options rather than searching for information separately when needed, significantly reducing information identification time.
Solution Approach 2:
The system incorporates feedback mechanisms where the AI assistant continuously monitors traveler responses to itinerary suggestions and preference inputs, automatically refining search results and destination recommendations based on group consensus and individual preferences. This feedback loop ensures that the most pertinent travel information is identified and presented efficiently, eliminating the need for travelers to manually search through unrelated information.
Data Source
AI summary
A computing system includes at least one processing circuit having at least one processor and at least one memory device. The processing circuit performs operations including: providing a chat interface to allow a plurality of travelers to initiate a chat session in which the plurality of travelers collaborate to plan a trip; receiving, via the chat session, input from the plurality of travelers related to the trip; and automatically interacting, via a chatbot, with the plurality of travelers within the chat session to plan the trip by: processing, using a machine learning model, a content of the chat session to generate one or more recommendations for the trip, wherein processing the content of the chat session includes generating the one or more recommendations using the input from the plurality of travelers; and providing the generated one or more recommendations to the plurality of travelers within the chat session.