Authors: Assistant Professor Sangeeta Mohapatra, Kartik Biradar, Tushar Malwade, Aryan Lanke
Abstract: In today’s mobile-centric era, travelers increasingly rely on real-time, personalized information to enhance their tourism experiences. This paper presents the design and implementation of a context-aware mobile application that recommends nearby tourist attractions, optimizes visitation routes, and provides detailed information about local accommodations and dining options. Building on recent advancements in mobile computing, route optimization, and context-aware systems, our work details the system’s architecture, data acquisition methods, hybrid recommendation engine, and routing algorithms. Experimental results demonstrate improvements in route efficiency and recommendation accuracy while maintaining real-time responsiveness. The paper also discusses potential enhancements using machine learning techniques and further integration with urban data streams.
