Smart tourism route planning from the perspective of Internet of Things and smart communication

The multidimensional integration of technology iteration, policy orientation, market demand and industry coordination provide a complete support system for smart tourism route planning from concept to implementation and also provides a technical basis for improving tourists’ satisfaction with scenic spots and tourism experience. In this context, improving the effect of tourism route planning combined with artificial intelligence is of great significance to improve the development quality of tourism enterprises and scenic spots. This paper combines the Internet of things and smart communication technology to study tourism route planning, aiming to improve the effect of tourism route planning and enhance the personal experience of tourists. This paper proposes the GKDF (Gaussian Kernel Density Filter) user clustering algorithm and combines it with the collaborative filtering recommendation algorithm to construct scenic spot and route recommendation algorithm, which is used for personalized recommendation of scenic spots and route planning. Combined with experimental analysis, it can be seen that the tourism route planning system can effectively improve the rationality and personalization of tourism route planning compared with similar applications. Tourism route planning needs to combine Internet of things technology and smart communication technology on the basis of personalized needs to provide reliable and accurate decision support for tourists, reduce tourism costs, and play an important role in improving the competitiveness of tourism enterprises.