Algorithm Design for Path Optimization and Personalization of Sports Tourism Activities Incorporating Motion Trajectory Analysis

Abstract

Sports tourism, characterized by the fusion of sports activities and travel experiences, has gained significant popularity in recent years. Efficiently planning and personalizing sports tourism itineraries to cater to diverse preferences and constraints remains a challenging task. In this, they propose an algorithmic approach for path optimization and personalization of sports tourism activities, integrating motion trajectory analysis techniques. The system optimizes the sequence of athletic activities along a trip route while taking into account time limits, fitness levels, preferences, and geographic factors. It uses motion trajectory analysis to better comprehend the spatial and temporal features of sports activities and optimize their sequencing in travel itineraries. The technique creates personalized sports tourism experiences adapted to individual interests and limits by modelling the interaction of sports activities, geographical locations, and user choices. The algorithm uses optimization techniques such as genetic algorithms, simulated annealing, and particle swarm optimization to identify near-optimal solutions from the many alternative activity sequences. It contains representation systems, fitness evaluation criteria based on motion trajectory analysis, and optimization methods. User feedback methods fine-tune and alter itineraries depending on preferences and real-time environment. The results show that the approach may be used in a variety of sports tourism scenarios, including hiking, cycling, skiing, and water activities. Comparison with older approaches reveals improved performance, flexibility, and customisation. The strategy improves and personalizes sports tourism activities, enhancing vacation experiences for enthusiasts. Dynamic, tailored itineraries address a wide range of passenger needs and preferences by assessing motion trajectories and utilizing optimization techniques.