The construction industry faces significant challenges, including the urgent need to minimize environmental impact and develop more efficient building methods. Additive manufacturing, commonly known as 3D-printing, has emerged as a promising solution due to its advantages, such as rapid fabrication, design flexibility, cost reduction, and enhanced safety. This technology enables the creation of structures from digital models through automated layering, presenting opportunities for mass production with innovative materials and architectural designs. This article focuses on developing eco-friendly earthen-based materials stabilized with 9 % cement and 2 % rice husk (RH) for large-scale 3D-printed construction. The raw materials were characterized using geotechnical tests for soil, water absorption tests for natural fibers, and SEM-EDS to examine their microstructure and elemental composition. Key properties such as rheology, printability (pumpability and extrudability), buildability, and compressive strength were evaluated to ensure the material's optimal performance in both fresh and hardened states. By utilizing locally sourced materials such as soil and rice husk, the mixture significantly reduces environmental impact and production costs, making it a sustainable alternative for large-scale 3D-printed construction. The material was integrated into architectural and digital fabrication techniques to construct a bioinspired housing prototype showcases the practical application of the developed material, demonstrating its scalability, adaptability, and suitability for innovative and costeffective real housing solutions. The article highlights the feasibility of using earthen-based materials for sustainable 3D-printed housing, thereby opening new possibilities for advancing greener construction practices in the future.

In recent years, the rapid development of the world's economy has led to the large-scale development and utilization of ecological resources on the earth, due to which the ecological environment has been continuously and seriously damaged, resulting in the waste of resources, soil erosion, land desertification, etc. To avoid further damage to the ecological environment and ecological resources, improve the utilization rate of ecological resources, and ensure the sustainable development of human society, it is necessary to evaluate the ecological environment. In this study, we collected the required data using the Delphi method and remote sensing technology. Secondly, the green Olympic building evaluation system (which refers to the CASBEE method in Japan) was used to evaluate the impact of green roofs on architectural design and the urban ecological environment. Third, a deep learning (DL)-based hybrid model, which consists of a convolutional neural network (CNN) and long-short-term memory (SLSTM), known as CNN-LSTM, was used to evaluate the impact of green roofs on urban ecology and building architectural design. The influence of thermal comfort on the indoor environment of green roof buildings was studied. For experimentation, six samples of Shanghai Thumb Plaza, Splendid Tesco Point, Chaoshan Yuan Hotel, Green Management Office, Huangpu District Domestic Waste Transfer Station, and Changning District Fuxin Slaughterhouse were selected as evaluation objects, and the effect of green roofs on building design and urban ecology was evaluated from six levels: ecological, ornamental, safety, functional, social, and economic. Both the CASBEE and DL-based methods, CNN-LSTM, performed well and increased the evaluation results to some extent. The CNN-LSTM model increased the accuracy of the system by 3.55%, precision by 3.50%, recall by 4.46%, and F1-score by 3.30%. Overall, this study summarizes the existing problems of green rooftop buildings in Shanghai at this stage, which is conducive to formulating optimization strategies to improve the ecological benefits of green roof buildings and has important practical significance for realizing the sustainable development of human society.