AI Trip Planner
Prof. Aparna R. Khairkar
Dept. Of Information Technology,
Prof Ram Meghe College of Engineering and Management, Badnera, Amravati, Maharashtra India, 444701 Sant Gadge Baba Amravati university Amravati Maharashtra aparna.khairkar@prmceam.ac.in
Prof. Monika S. Shirbhate
Dept. Of Information Technology,
Prof Ram Meghe College of Engineering and Management, Badnera, Amravati, Maharashtra India, 444701
Sant Gadge Baba Amravati university Amravati Maharashtra monikashirbhate@gmail.com
Utkarsha D. Mude
Dept. Of Information Technology,
Prof Ram Meghe College of Engineering and Management, Badnera, Amravati, Maharashtra India, 444701
Sant Gadge Baba Amravati university Amravati Maharashtra mudeutkarsha@gmail.com
Hadee A. Khan
Dept. Of Information Technology,
Prof Ram Meghe College of Engineering and Management, Badnera, Amravati, Maharashtra India, 444701 Sant Gadge Baba Amravati university Amravati Maharashtra Hadeekhan924@gmail.com
Ishwari S. Deshmukh
Dept. Of Information Technology,
Prof Ram Meghe College of Engineering and Management, Badnera, Amravati, Maharashtra India, 444701
Sant Gadge Baba Amravati university Amravati Maharashtra ishwarideshmukh04@gmail.com
Diya J. Dave
Dept. Of Information Technology,
Prof Ram Meghe College of Engineering and Management, Badnera, Amravati, Maharashtra India, 444701
Sant Gadge Baba Amravati university Amravati Maharashtra davediyaj12@gmail.com
1. ABSTRACT
Travel planning is essential for creating efficient and enjoyable travel experiences, yet existing approaches often fail to address the challenges of time-consuming research, fragmented information sources, and lack of personalized recommendations. traditional travel planning methods require users to manually search across multiple platforms
for destinations, accommodations, and itineraries, leading to inefficient decision-making and limited customization. this paper presents ai trip planner, an ai-powered travel planning system designed to automatically generate personalized
travel itineraries based on user preferences, budget, and
travel duration. developed using web technologies, and the google gemini api, the proposed system integrates intelligent itinerary generation, destination recommendation, and user- input based customization within a single platform. by incorporating natural language processing and ai-based recommendation mechanisms, the system enables users to quickly create optimized travel plans and receive relevant travel suggestions. results indicate that this approach
improves travel planning efficiency and personalization while reducing the effort and time required for manual trip organization, benefiting travelers, tourists, and travel enthusiasts.
