Due to various factors such as aging, natural environment erosion, and man-made destruction, architectural heritage has formed various diseases and cracks, especially in pathology cracks, which are the most typical masonry–timber architectural heritages, directly affecting the structural stability of masonry–timber buildings. This paper uses artificial intelligence and architecture and other multi-disciplinary research methods, taking James Jackson Gymnasium, a famous masonry–timber architectural heritage in Wuhan, as an example, using 3D laser scanning technology to obtain disease details and crack data of architectural heritage, using a Mask R-CNN model to detect crack area, using an FCN model to identify and calculate single cracks, and finally summarizing the type, location, and characteristics of cracks, analyzing the causes of cracks, and then putting forward corresponding hierarchical restoration strategies. The research results build a set of detection and repair systems of masonry–timber architectural heritage pathology cracks, which provide a set of accurate and objective pathology cracks data for architectural heritage protection and repair, and provide a reference for architectural heritage repair.

This paper focuses on the sustainable exploration of building systems, which combines ecological concepts and low-carbon designs for a comprehensive sustainability assessment investigation. The study employed the Life Cycle Assessment (LCA)-Emergy and Life Cycle Assessment (LCA)-Carbon emission methods to discuss a range of topics, including the main contributing factors, sustainability index verification, sensitivity analysis, and potential improvement measures. From an ecological sustainability perspective, the results indicate that the building operation stage plays a critical role, accounting for approximately 45% of the entire emergy in the building commercial complex. The sustainable index (ESI) is 0.354, which is below the standard of 1. Moreover, the building operation stage also significantly contributes to carbon emissions, particularly in the 50th anniversary of operation. Based on these findings, the study recommends two potential strategies to improve the ecological state and low-carbon design which involve the use of renewable energy and carbon sink improvement, respectively.

The tourism development of industrial heritage is an effective way to activate cultural heritage and can provide new solutions for the renewal and protection of industrial heritage. This study focuses on the industrial heritage in Nanjing, aiming to explore its spatial distribution pattern, tourism development strategy, and sustainable development model. This study adopts a combination of quantitative and qualitative research methods. First, relevant information on 93 sites of industrial heritage type historic buildings in Nanjing is collected. Secondly, ArcGIS was used to visualize the evolution of industrial buildings and the spatial distribution of industrial heritage type historic buildings. Finally, the spatial analysis tools of ArcGIS and the accessibility analysis method in space syntax theory are superimposed to comprehensively analyze the spatial distribution pattern and traffic accessibility characteristics of Nanjing’s industrial heritage. The research results propose a specific plan to promote the value transformation of industrial heritage through tourism: based on the spatial distribution characteristics of Nanjing’s industrial heritage along the water system and traffic arteries, a tourist route of “multi-point, two-axis, one-center” is planned; the tourism development strategy of “point protrusion, linear links, and surface darning” is implemented; and a sustainable development model under the guidance of low-carbon environmental protection goals is explored. This study provides a reference for the protective development of industrial heritage and the expansion of tourism and opens up a new perspective for the regeneration and planning of other urban heritage.

Sustainable architecture holds research significance as a necessary approach to address climate change. However, the lack of a clear definition and diverse research methods present obstacles in this field. To overcome these challenges, this study adopts an integrated approach that combines ecological and low-carbon aspects and considers the entire life cycle system. The highlight of this article is the integration of two research methods to assess the sustainability of a building system from both ecological and carbon footprint perspectives. This approach has not been extensively explored by researchers thus far. The aim is to quantitatively explore and evaluate the sustainability performance of building systems. The research findings reveal that, among the five life cycle stages, the operational stage of a building exhibits the highest proportions of emergy consumption and carbon emissions, accounting for approximately 89.4% and 90%, respectively. From an emergy analysis perspective, newly constructed building systems demonstrate qualified sustainable parameters (Emergy Sustainability Indicator (ESI) = 2.7 > 1)). However, as the building system ages and operates over time, the overall sustainable parameters gradually decrease, eventually becoming unqualified. Furthermore, carbon emissions analysis indicates that total carbon emissions accelerate with the aging of the building, highlighting the necessity of continuous inputs of material flow, energy flow, and information flow to maintain the building system’s sustainability. The cross-feedback model emerges as the most effective correction method among the input processes, although data collection poses a challenge due to its nonlinearity. This study provides a fresh perspective for architects and building managers, offering insights that contribute to mitigating climate change and promoting sustainable practices in the built environment.

The rebirth of educational architectural heritage plays an important role in the urban tourism economy, and studying the integration of educational heritage and tourism is of great significance and value. This article selects the educational heritage in Nanjing, China, from 1840 to 1952 as its research object to explore the integration and sustainable development relationship between heritage utilization and tourism. This article adopts a research method that combines qualitative and quantitative methods. First, it collects historical data and conducts on-site surveys to obtain information on 117 important educational heritage sites in Nanjing. Then, it uses ArcGIS technology to quantitatively analyze the evolution rules of modern educational buildings in Nanjing and the spatiotemporal distribution characteristics of the heritage. Finally, a cultural tourism strategy is proposed based on heritage characteristics and government policies. The research results reveal the interdependence and sustainable development relationship between the protection and utilization of educational heritage and tourism: according to the distribution characteristics of the heritage in the urban space, the "educational heritage tourism path" of the ancient city is constructed, which can promote the development of urban tourism. Subsequently, the economic value created by tourism is used to "feed back" heritage protection. This research result provides reference for educational heritage tourism in other cities in China and around the world.

From a global perspective, the ecological sustainability of building systems has always been a hot research topic, especially in China, where the annual amount of new construction is nearly half of the world. The difficulty is making a complete and accurate ecological assessment of the building system. This study has designed and adopted the LCA-Emergy-ANN framework to assess and analyze an airport building system for sustainability. The results demonstrate that building material emergy and operational stage emergy play a critical role and account for 92.4% of the entire emergy, which are the primary contributors. As the vital indicator, the emergy sustainability index (ESI) is 0.669, which is unsustainable (The eligibility standard is 1). Simultaneously, to ensure the accuracy of the data results, sensitivity analysis was performed. The artificial neural network (ANN) was used by integrating the LCA method and emergy approach to predict the sustainability trend in the long run. In the end, the optimization strategy is proposed to enhance the sustainability of the building system.