Design of a Rural Tourism Satisfaction Monitoring System Based on the Improved INFO Algorithm

The increasing influx of tourists to scenic areas has raised significant security concerns, often surpassing the management capacity of these locations. Despite the growing need for effective solutions, many regions have not yet developed strategies to address these issues. This study aims to enhance rural tourist satisfaction monitoring systems to better manage tourist flows and improve security. The research explores rural tourist satisfaction, which has significant potential for large-scale monitoring due to its self-expanding nature. The paper discusses the critical role of tourist satisfaction within scenic areas, particularly focusing on tourist tracking systems. It also introduces key features and positioning algorithms used for monitoring satisfaction. A new collaborative positioning approach, based on subnetwork fusion, is proposed to address the limitations of traditional non-line-of-sight INFO positioning algorithms. The proposed subnetwork fusion method outperforms the traditional INFO algorithm, with a 39.7% reduction in localization error when more than 130 nodes are used. Furthermore, when anchor nodes exceed 10%, the DPeNet algorithm achieves an average precision value of 0.768, surpassing the 0.75 threshold due to its enhanced multi-channel convolution and downsampling structure, which optimally utilizes the deep features of small-sized targets. This paper introduces an innovative collaborative positioning strategy for rural tourist satisfaction monitoring, overcoming existing algorithm limitations and enhancing localization accuracy in real-time tourist management systems. The findings contribute to improving both tourist experience and safety in rural scenic areas, offering a scalable solution for broader applications in tourist destinations.