Smart Travel Assistance using Artificial Intelligence

作者：Prof. Minal Solanki and Shruti Khandagale · 发表于：International Journal of Advanced Research in Science, Communication and Technology · 年份：2026 · DOI：10.48175/ijarsct-31909

Smart travel using Artificial Intelligence (AI) is transforming the tourism and transportation industry by providing intelligent, personalized, and efficient travel solutions. Traditional travel planning methods are often time-consuming and lack customization. AI technologies such as machine learning, natural language processing, and predictive analytics enable automated itinerary planning, real-time recommendations, traffic prediction, and smart booking systems. This paper explores various AI-based approaches used in smart travel systems, including recommendation engines, chatbots, and route optimization models. The study highlights how AI improves user experience, reduces travel time, and enhances decision-making. It also discusses challenges such as data privacy, model accuracy, and real-time processing. The research concludes with future directions involving IoT integration, autonomous vehicles, and smarter urban mobility systems. This paper presents a comprehensive study of AI-based smart travel systems, focusing on their architecture, methodologies, applications, and performance. The proposed system integrates modules such as recommendation engines, route optimization algorithms, and AI chatbots to enhance user experience and operational efficiency. Furthermore, the paper discusses key challenges including data privacy, computational complexity, and prediction accuracy. Future advancements such as integration with Internet of Things (IoT), autonomous vehicles, and smart...