Public spaces in traditional villages are the root of the development, preservation, and inheritance of rural cultural heritage. However, these spaces in tourism-oriented traditional villages continue to suffer from issues such as inconsistent vitality, more competition than cooperation, and inefficient revitalisation. Limited by the low precision of spatiotemporal data in rural areas, previous static and materialised vitality evaluation methods have failed to explore the dynamic nature of the flow of people in traditional village public spaces. This study investigated a collaborative active perception method using Wi-Fi probes and static snapshots to assess their dynamic vitality. An empirical study was conducted using Yantou Village in Lishui City, China, as an example. The empirical results indicate that this method can qualitatively and quantitatively analyze the spatiotemporal variations and the scenarios of the dynamic vitality of small public spaces in traditional villages, deepening the cognitive depth of their vitality from time and humanity, providing a basis for the spatiotemporal synergistic enhancement of their public spaces, and offering insights for their revitalisation.

Tourist preferences for public spaces in historic districts can reflect whether renovated spaces and functional structures meet tourism demands. However, conventional big data lack the spatio-temporal accuracy needed to support a refined, dynamic study of small-scale public spaces inside historic districts. This paper, therefore, proposes using a Wi-Fi probe to evaluate the spatio-temporal dynamics of tourists’ spatial preferences in historic districts. We conducted a one-week measurement in the Xiaohe Street Historic Block in Hangzhou, China. Three indicators—visit time preference, aggregation preference, and stay preference—were used to examine the dynamic change in tourists’ spatial preferences, with 15 min as the time unit and public spaces with a radius of 25 m as the spatial unit. Our research demonstrates that, compared with conventional big data, the Wi-Fi probe offers a more reasonable and accurate method to measure tourists’ spatial preferences in historic districts at a smaller time and spatial granularity. The research findings can be applied to evaluate the effectiveness of spatial regeneration and diagnose renewal-related issues in historic districts. It can also serve as a foundation for more precise planning of public spaces in historic districts, as well as the modification of functional structures.

With the rise in rural tourism, public space use has become more complex, causing significant weekday-weekend vitality imbalances. However, the factors shaping these dynamics in traditional villages remain unclear. This study uses Wi-Fi sensing method to analyze vitality variations across weekdays and weekends, and it develops a 13-metric evaluation framework to examine how built environment factors, from both internal and external dimensions, differentially influence the vitality of public spaces in traditional villages across various time periods. Using 17 public spaces in Yantou Village, Lishui, China, as a case, it finds: (1) Historical Element Proximity consistently and significantly drives public space vitality across all periods; (2) Leisure Facility Count and Decorative Element Count demonstrate strong positive effects during weekend morning peaks. (3) Retail Facility Count significantly reduces vitality during weekend morning peak but enhances it during midday off-peak, whereas Street Vendor Count shows the opposite pattern—increasing vitality in morning peak and decreasing it in midday off-peak. Using Wi-Fi sensing’s high-resolution, real-time, and non-invasive capabilities, this study provides a scientific method to accurately assess the variations in public space vitality and their impact factors between weekdays and weekends in traditional villages, offering technical support for enhancing public space vitality and sustainably revitalizing rural heritage.

The revitalization of traditional villages is shifting from single village to contiguous areas, with a cycling network connecting these villages serving as a key facilitator for the coordinated development of their culture and tourism. However, current rural cycling network planning primarily depends on static, materialized evaluations and fails to leverage the dynamic flow of people in the region, leading to generally low utilization rates. Consequently, this study proposes a method for generating a cycling network based on flow-based attractiveness evaluation. By utilizing Wi-Fi probes to monitor the intensity and stability of people’s movement, we established an attractiveness evaluation for the preliminary cycling route. Based on this evaluation, we incorporated the shortest routes to historical attractions and the concentration of public service facilities to construct an optimal cycling network. The research then conducted an empirical study in the traditional village contiguous area of Tonglu County, China, and found that: (1) the flow attraction of the initial route was highly polarized and unevenly distributed; (2) compared to the original plan, the cycling network generated by this research demonstrated superior overall performance, with improvements in accessibility, connectivity to historical attractions and integration with public service facilities. These findings suggest that the method can be used to create a cycling network that encourages people to remain in traditional village contiguous areas, thereby promoting the synergistic development of culture and tourism.