Evaluating Age-Friendliness of Outdoor Service Facilities in Tourist Attractions: Evidence from Visual Computing Models

Rapid population aging worldwide has created pressing demands for transformative changes in tourism management and service provision, necessitating urgent age-friendly modifications to destination infrastructure and facilities. However, the existing research on age-friendly facility assessments has often relied on methods such as surveys and field observations, which are inefficient and highly subjective, significantly limiting their applicability. This paper proposes a novel age-friendly assessment method that integrates multiple computer-vision-based object detection and recognition models. By calculating the spatiotemporal occupancy rates of resting facilities and the proportion of elderly usage, this method enables an efficient quantification of the age-friendly adequacy of rest areas. Using field data collected from the Xuanwu Lake Scenic Area, we designed accuracy analysis and validation experiments, demonstrating that this method surpasses traditional approaches in both evaluation efficiency and accuracy. The results indicate that the service facility adequacy in the FangQiao and LingQiao rest areas is insufficient, with resting facility density below four per 100 m, making it difficult to meet the resting needs of elderly visitors. This method can effectively supplement current age-friendly facility assessment practices in tourist destinations, offering a scientific and efficient basis for infrastructure upgrades tailored to elderly needs.