Poster Session 4, 2:15 PM - 3:00 PM: Room 163 [C32]

Smart Travel App

Presenter: Trevor Kkaaya

Faculty Sponsor: Bo Jin Hatfield

School: Salem State University

Research Area: Artificial Intelligence

ABSTRACT

Modern travel planning requires users to manually search across multiple websites, mapping tools, and review platforms, resulting in incomplete workflows and inefficient itinerary design. The purpose of this project is to develop and evaluate a unified, AI-powered platform that streamlines travel discovery, itinerary generation, and trip documentation within a single interface. By combining these processes, the system aims to reduce planning frustration while maintaining personalization and user control.The platform integrates a large language model API (Groq) to generate structured, day-by-day itineraries based on user-defined inputs such as destination, duration, pace, budget, and personal interests. Natural language place search is supported through external geospatial APIs, enabling users to query locations conversationally (e.g., “local coffee shops in Paris”). Additional features include drag-and-drop itinerary editing, collaborative trip sharing, favoriting and pinning of locations, and a digital travel diary for storing notes and photos.The system was implemented using a Next.js frontend, a Fastify backend API, Google OAuth authentication, and Supabase for secure data persistence. By combining AI-assisted content generation with structured user interaction design, the project demonstrates how large language models can be integrated into scalable web architectures to support intelligent, user-centered planning systems. This work offers a reusable model for AI-augmented workflow design in consumer applications.

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