| id |
acadia16_470 |
| authors |
Sollazzo, Aldo; Baseta, Efilena; Chronis, Angelos |
| year |
2016 |
| title |
Symbiotic Associations |
| doi |
https://doi.org/10.52842/conf.acadia.2016.470
|
| source |
ACADIA // 2016: POSTHUMAN FRONTIERS: Data, Designers, and Cognitive Machines [Proceedings of the 36th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-77095-5] Ann Arbor 27-29 October, 2016, pp. 470-477 |
| summary |
Soil contamination poses a series of important health issues, following years of neglect, constant industrialization, and unsustainable agriculture. It is estimated that 30% of the total cultivated soil in the world will convert to degraded land by 2020 (Rashid et al. 2016). Finding suitable treatment technologies to clean up contaminated water and soil is not trivial, and although technological solutions are sought, many are both resource-expensive and potentially equally unsustainable in long term. Bacteria and fungi have proved efficient in contributing to the bioavailability of nutrients and in aggregating formation in degraded soils (Rashid et al. 2016). Our research aims to explore the possible implementation of physical computing, computational analysis, and digital fabrication techniques in the design and optimization of an efficient soil remediation strategy using mycelium. The study presented here is a first step towards an overarching methodology for the development of an automated soil decontamination process, using an optimized bio-cell fungus seed that can be remotely populated using aerial transportation. The presented study focuses on the development of a methodology for capturing and modeling the growth of the mycelium fungus using photogrammetry-based 3D scanning and computational analysis techniques. |
| keywords |
computational design, photogrammetry, simulation, mycelium, 3d scanning, growth strategies |
| series |
ACADIA |
| type |
paper |
| email |
|
| full text |
 file.pdf (738,903 bytes) |
| references |
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