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[Display omitted] • Simple blade coating technique to achieve large-scale self-assembly of graphene oxide (GO) flakes into anisotropic films with gradient structures and controlled patterning. • Statistical analysis method utilizing scanning electron microscopy images for the characterization of materials with macroscopic surface morphology. • Sensing/actuation behavior, responding to external stimuli such as temperature, humidity, and light. • Robust and flexible materials are suitable for application as integral building elements in the bioinspired design of sustainable smart housing and green constructs. Sustainable structural design, utilizing material to imitate natural biological systems, presents both promise and challenges. By avoiding interfacial problems encountered in composite counterparts, such designs offer self-adaptive materials for smart housing and green architecture, etc. In this study, we demonstrate the feasibility of large-scale self-assembly of graphene oxide (GO) flakes into anisotropic films through a simple blade coating technique. Through the application of blade coating to a highly concentrated nematic GO suspension, we successfully fabricate GO films with morphological gradient and patterning. Additionally, we propose a statistical analysis method utilizing scanning electron microscopy (SEM) images for the characterization of materials with macroscopic surface morphology. Furthermore, we explore the application of these GO films as low-dimensional soft actuators, revealing their outstanding stimuli-responsive performance and self-adaptation to environment. Such robust and flexible films can be used as integral building elements in the bioinspired design of sustainable smart housing facilitating remote robotization and sensing capabilities. [ABSTRACT FROM AUTHOR]