Publication | Open Access
Biomimetic bio-inspired biomorph sustainable? An attempt to classify and clarify biology-derived technical developments
154
Citations
21
References
2017
Year
EngineeringBioenergyBiological Concept GeneratorsBio-inspired DesignEducationSustainable DesignBiomimetic ChemistryData ScienceBiology-derived Technical DevelopmentsBiostatisticsBio-inspired AircraftEcotechnologyBiological DataSupervised LearningBionicsBiomimetic SystemKnowledge TransferBio-inspired SystemsBiomolecular EngineeringBioprospectingSustainability AssessmentBio-inspired SystemBiotechnologySynthetic BiologyClassificationSustainabilityTechnology
The systematic transfer of biological concepts to technical applications has gained attention in recent decades, especially as bio‑derived products are often marketed as sustainable. This paper aims to clarify the sustainability discussion of bio‑derived developments by incorporating descriptive, normative, and emotional perspectives. The authors constructed a supervised‑learning dataset of 70 biology‑derived and technology‑derived developments with nine attributes, trained a decision‑tree classifier to assign them to 17 classes, and applied it to a building‑sector case study. The classifier achieved 90 % accuracy, and the study also highlights additional sustainability and aesthetic qualities of selected bio‑derived applications.
Over the last few decades, the systematic approach of knowledge transfer from biological concept generators to technical applications has received increasing attention, particularly because marketable bio-derived developments are often described as sustainable. The objective of this paper is to rationalize and refine the discussion about bio-derived developments also with respect to sustainability by taking descriptive, normative and emotional aspects into consideration. In the framework of supervised learning, a dataset of 70 biology-derived and technology-derived developments characterised by 9 different attributes together with their respective values and assigned to one of 17 classes was created. On the basis of the dataset a decision tree was generated which can be used as a straightforward classification tool to identify biology-derived and technology-derived developments. The validation of the applied learning procedure achieved an average accuracy of 90.0%. Additional extraordinary qualities of technical applications are generally discussed by means of selected biology-derived and technology-derived examples with reference to normative (contribution to sustainability) and emotional aspects (aesthetics and symbolic character). In the context of a case study from the building sector, all aspects are critically discussed.
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