Derived from the Greek words "bios" and "mimicry", biomimicry was used by Otto Schmitt in 1957. Inspired by nature, biomimicry is used to make innovative designs and find solutions to people's problems by taking the biological and characteristic features of many living things.
Biomimicry is a new problem-solving science that studies the models, systems, formation processes and elements of nature and uses the information obtained by imitation or creative inspiration. Its basic principle is not how we can solve our problems better, but how we can do better. In order to solve our problems or meet a need, we can examine and observe living things in nature, and then transform them into designs.
While biomimicry first focused on the design of products, it later found application in organization and team management. Herd intelligence and tree fungus symbiosis are examples of this. The collective decision-making process of insects, which display swarm intelligence and social behavior patterns such as ants and bees, shows that we have a lot to learn from these creatures. In order for businesses to continue their lives for a long time, they need to focus on innovation. In this context, biomimicry offers businesses a strategic advantage in product design and research and development. Seeing the characteristics of living things in nature as a source of innovation provides businesses with a profit, risk reduction, cost-effective and sustainable opportunity.
Herd intelligence organization structure
Swarm intelligence is a collection of simple agents from natural biological models that act with each other and with their environment. Social insects act within the framework of simple rules. Ant colonies, bird flocks, bacterial growth, animal herds are examples of social insects. Insects with swarm intelligence can plan in balance. Each social insect has its own individual goals, but as a community they serve the same global goal.
Swarm intelligence can solve difficult problems by choosing the shortest possible way, as a result of social insects' teamwork, self-organizing, strong communication and coordinated work. Here is the emerging collective behavior of a group of social insects. Social insects are thought to be successful because of three characteristics. These:
- Flexibility of the colony to adapt to a changing environment,
- the strength of the group members in performing their duties, even if one or more of the group fails,
- It is self-organization due to the fact that the activities are not controlled by a central authority and that there is no control mechanism.
Swarm intelligence, which is developed by different algorithms from the combination of deterministic principles and randomness inspired by the behavior of social insects in our ecosystem, consists of the basic components of division of labor and self-organization.
Honeybee organization structure
Honey bees are very intelligent creatures. Honey bees display certain social behaviors while foraging. Honey bees are examined in three different groups. Workers, scouts and spectators. Bee swarms have the ability to exchange information among themselves, memorize their surroundings, collect and share information, and make decisions. In addition, the herd updates themselves according to the changes in the ecosystem and perform their duties through dynamic and social learning. The job of the worker bees is to search for food and share the information of their food sources with the bees that monitor them. The job of the onlooker bees is to select the good food sources available. They choose high quality food sources. On the other hand, scout bees are bees that leave their food sources and seek new ones.
Bees base their decisions on local clues and information. Honey bees, which have the ability to make quick and high-quality decisions, reduce the risk that may occur in this way. They use a technique similar to the Delphi technique when making big decisions with high probability of risk.
The genetic differences of bees, which are different from each other, are effective in determining the options. Because the more different their DNA structure, the more sensitive they become under different conditions and the more options they have.
Dr. Ayşe Meriç Yazıcı
References
Bansal, P. (2005). Evolving Sustainably: A Longitudinal Study of Corporate Sustainable Development, Strategic Management Journal, 26: 197-218.
Benyus, J. M. (2002). Biomimicry: innovation inspired by nature, New York: Perennial.
Bonabeau, E., & Meyer, C. (2001). Swarm intelligence: A whole new way to think about business, Harvard Business Review, 79(5). https://www.antoptima.ch/pdf/pr_harvardbusiness_0105.pdf
Brezočk, L., Fister, I., & Podgorelec, Jr. V. (2018). Swarm Intelligence Algorithms for Feature Selection: A Review, Appl. Sci., 8, 1521; doi:10.3390/app8091521
Cuevas, E., Cienfuegos, M., Zaldivar, D., & Pérez Cisneros, M. A. (2013). A Swarm optimization algorithm inspired in the behavior of the social-spider, Expert Systems with Applications, 40(16): 6374-6384. DOI:10.1016/j.eswa.2013.05.041.
Dargent, E. (2011). Biomimicry for Business, University of Exeter Business School.
Karaboğa, D. (2011). Yapay Zekâ Optimizasyon Algoritmaları, Ankara: Nobel Yayın Dağıtım.
List, C., & Vermeule, A. (2010, October 16). Independence and interdependence: Lessons from the Hive. Harvard Public Law Working Paper. Retrieved from https://papers. ssrn.com/sol3/papers.cfm?abstract_id=1693908
Maglic, M. J. (2012). Biomimicry: Using Nature as a Model for Design, (Unpublished Master Thesis), University of Massachusetts Amherst, Architecture+Design Program.
Nakrani, S., & Tovey, C. (2007). From honeybees to Internet servers: biomimicry for distributed management of Internet hosting centers, Bioinsp. Biomim., 2: 182-197.
Nayyar, A., Le, O. N., & Nguyen, N. G. (2019). Advances in swarm intelligence for optimizing problems in computer science. Boca Raton, FL: CRS Pr
O’Malley, M. (2012, June 20). A beekeeper’s perspective on risk. Retrieved from https:// hbr.org/2012/06/a-beekeepers-perspective-onri.
Passino, K. M. (2005). Biomimicry for optimization, control, and automation. Berlin: Springer Science & Business Media.
Primlani, R. V. (2013). Biomimicry: On the frontiers of design. XIMB Journal, 10(2), 139–148.
Volstad, N. L., & Boks, C. (2012). On the Use of Biomimicry as a Useful Tool for the Industrial Designer, Sustainable Development, Vol:20.
