Learning Eco-Innovation from Nature: Towards Identification of Solution Principles Without Secondary Eco-Problems

Livotov, Pavel; Mas’udah, Mas’udah; Sekaran, Arun Prasad Chandra

doi:10.1007/978-3-030-61295-5_14

Cited by 5 publications

(2 citation statements)

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“…The methodology employed in this study adopts the Solution-Driven Approach (SDA) outlined in Table 1, which builds upon our recent study on learning eco-innovation from nature (Livotov et al, 2020). This SDA was modified from the method introduced by Helms et al (2009) and utilized to identify ecoinventive principles in natural systems for solving eco-engineering contradictions, as previously demonstrated in our research (Mas'udah et al, 2021;Mas'udah et al, 2022).…”

Section: Solution-driven Design Approachmentioning

confidence: 99%

“…Natural systems, with their intricate and dynamic components, offer a valuable source of wisdom that can enhance the efficiency and sustainability of process design. Nature has always been a source of inspiration for innovation and has led to several scientific design approaches (Livotov et al, 2020;Bianciardi et al, 2023). Instead of imposing our industrial system on nature, we should allow nature to influence our industrial and innovation system.…”

Section: Introduction and Research Questionsmentioning

confidence: 99%

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Nature's lessons, AI's power: sustainable process design with generative AI

Mas'udah,

Livotov

2024

Proc. Des. Soc.

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In the realm of process engineering, the pursuit of sustainability is paramount. Traditional approaches can be time-consuming and often struggle to address modern environmental challenges effectively. This article explores the integration of generative AI, as a powerful tool to generate solution ideas and solve problems in process engineering using a Solution-Driven Approach (SDA). SDA applies nature-inspired principles to tackle intricate engineering challenges. In this study, generative AI is trained to understand and use the SDA patterns to suggest solutions to complex engineering challenges.

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