Amid the COVID-19 pandemic, prevention and control measures became normalized, prompting the development of campuses from digital to intelligent, eventually evolving to become wise. Current cutting-edge technologies include big data, Internet of Things, cloud computing, and artificial intelligence drive campus innovation, but there are still problems of unintuitive scenes, lagging monitoring information, untimely processing, and high operation and maintenance costs. Based on this, this study proposes the use of digital twin technology to digitally construct the physical campus scene, fully digitally represent it, accurately map the physical campus to the virtual campus with real-time sensing, and remotely control it to achieve the reverse control of the twin virtual campus to the physical campus. The research is guided by the theoretical model proposed by the digital twin technology, using UAV tilt photography and 3D modelling to collaboratively build the virtual campus scene. At the design stage, the interactive channel of the system is developed based on Unity3D to the realize real-time monitoring, decision making and prevention of dual spatial data. A design scheme of the spiral optimization system life cycle is formed. The modules of the smart campus system were evaluated using a system usability scale based on student experience. The experimental results show that the virtual-real campus system can enhance school management and teaching, providing important implications for promoting the development and application of campus intelligent systems.

Previous studies may have overstated the restorative benefits of natural environments by comparing them to low-quality urban environments. Few studies have compared the stress recovery effects across various park settings. Moreover, it is unclear how depressive symptoms affect these benefits. Depressive symptoms may lessen or boost the restorative effects of viewing nature. A total of 125 participants engaged in the Trier Social Stress Test (TSST) to induce stress and were then randomly assigned to view one of five 10 min video presentations depicting greened streets, lawns, plazas, forests, or watersides. Depressive symptoms experienced over the last month were measured using the Patient Health Questionnaire (PHQ-9). The analysis revealed that, while greened streets had a physio-psychological stress-relieving effect, they were not as effective as the four park settings. The skin conductance level (SCL) declined significantly in the forest group’s first and second halves of the recovery period. However, the difference between the four park settings was insignificant at the end of recovery. Subjects viewing the four park conditions (vs. the greened street) reported that perceived stress remained stable as individual depressive symptoms increased; subjects with higher depressive symptoms reported lower perceived stress under lawn conditions. However, the SCL did not show the same trend. Our findings may support the hypothesis that natural interventions may be especially beneficial for people suffering from subclinical depressive symptoms. We also found gender differences in perceived stress and SCL reduction across all five settings, which may be due to the differences in women’s and men’s perceptions and use of restorative environments, or their responses to stressors.

This research explores the innovative application of Artificial Intelligence Generated Content (AIGC) technology in the digital restoration of ancient architectural ruins. It focuses on the unique architectural tradition of Song Dynasty single-bay Buddhist halls in the Changxi River Basin of eastern Fujian, using the Gonghoulong (宫后垄) Temple site in Ningde City, Fujian Province, as a case study. The study pioneers a collaborative research paradigm that integrates architectural archaeology with generative artificial intelligence. Through precise digital surveying and multi-source literature verification, we analyze the spatial organization of stone components at the site, revealing that the Song Dynasty Buddhist Hall at Gonghoulong Temple incorporates layered pavilion concepts, demonstrating distinctive regional characteristics that differ from official architectural practices. By leveraging AIGCpowered intelligent deduction, the study establishes a "digital archiving-intelligent deduction-dynamic intervention" restoration framework through stylized generation and virtual reconstruction simulations. The Gonghoulong Temple site, discovered in the late 20th century, contains significant architectural remains such as house foundations, ash pits, and tombs. The Changxi River Basin preserves numerous Tang-Song period single-bay Buddhist Hall ruins, indicating a unique regional architectural pattern seldom seen in Chinese history. This technological exploration aims to revive the "single-bay pavilion-style" construction wisdom of the Changxi Basin. Through digital analysis and architectural form recombination, it facilitates the virtual restoration of the Song Dynasty Buddhist Hall at Gonghoulong Temple, offering new insights into early Buddhist architecture along China's southeastern coast and establishing standardized references for the intelligent conservation of similar heritage sites across East Asia.