Year: 2025
Type: article
Abstract: Tourism is a rapidly growing industry, and travelers often seek personalized recommendations to explore destinations that align with their interests. TripMitra is a web-based travel recommendation system designed to provide intelligent and customized travel suggestions based on user preferences and interactions. The system incorporates machine learning algorithms to enhance the accuracy of recommendations and features an image-based search that allows users to upload a photo to find visually similar destinations.Developed using Flask (Python) for backend processing, OpenCV for image analysis, MySQL for secure data storage, and Google Maps API for navigation and location-based services, TripMitra provides an interactive and user-friendly experience. Additionally, real-time weather updates help travelers make informed decisions while planning their trips. By leveraging computer vision and recommendation algorithms, TripMitra enhances the way travelers discover new destinations. The platform aims to create a seamless travel planning experience by integrating intelligent search mechanisms and data-driven recommendations. Keywords: Travel recommendation system, Flask, OpenCV, Google Maps API, MySQL, machine learning, personalized travel, tourism technology.
DOI: 10.55041/ijsrem45112
Author: Komal Sheshnarayan Pandey
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409599477