Automatically Populating the Biomimicry Taxonomy for Scalable Systematic Biologically-Inspired Design

Abstract

Although Biologically-Inspired Design (BID) is gaining popularity, state-of-the-art approaches for systematic BID are still limited by the required interactive work which is proportional to the applied biological database size. This interactive work, depending on the adopted methodology, might encompass model instantiation for each strategy in the biological database, classification into a predefined scheme or extensive result filtering. This contribution presents a first scalable approach to systematic BID with the potential to leverage large numbers of biological strategies. First, a focused webcrawler, based on a combination of Support Vector Machines (SVM), continuously searches for biological strategies on the Internet. The solution to this needle-in-a-haystack task is shown to produce biological strategies interesting for cross-domain Design-by-Analogy (DbA). These resources are then automatically positioned into Ask Nature’s well-known Biomimicry Taxonomy; a 3-level hierarchical classification scheme that enables designers to identify biological strategies relevant to their specific design problem. This paper details the architecture of the proposed system, and presents results indicating the feasibility of the applied approach.