Presenter: Edgar U. Falfan

Group Members: Michael Mahoney

Faculty Sponsor: Hao Loi

School: Quinsigamond Community College

Research Area: Computer Science

Session: Poster Session 1, 10:30 AM - 11:15 AM, Auditorium, A4

ABSTRACT

Traditional travel planning required users to manually coordinate transportation, accommodation, meals, and activities across multiple platforms—a time-consuming and often overwhelming process that continued throughout the trip. This project addressed the following question: How can autonomous AI help improve the pre-trip logistics under budget and preference constraints? The hypothesis was that an autonomous AI agent could optimize travel experiences by proactively managing routine tasks and providing real-time, contextually relevant recommendations.

The methodology involved developing a travel assistant system where users input their itinerary with dates, destinations, budget constraints, preferred attractions, and personal preferences regarding food and shopping. The AI agent operated autonomously throughout the trip, continuously comparing transportation options between destinations, identifying accommodations within budget, and discovering points of interest aligned with user preferences that travelers might not have initially considered. The system integrated historical and real-time weather data to recommend optimal daily activities, located nearby restaurants, convenience stores, and public restrooms based on the current location, and suggested contextually relevant shopping opportunities.

The results demonstrated that autonomous AI significantly improved travel efficiency by automating multifaceted tasks that typically required constant human attention. The system saved time through automated comparisons and recommendations and enhanced the overall travel experience by highlighting opportunities that travelers might otherwise have missed. This research contributed to understanding how autonomous AI agents can transform everyday experiences by managing the operational complexity of travel, allowing users to focus on enjoyment and exploration.

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