1. Proceedings
  2. I3M
  3. 2022
  4. SESDE
  5. 10.46354/i3m.2022.sesde.002

A Social Media-driven Digital Twin of an Invasive Species

  • a Jim Scheibmeir , 
  • b Yashwant Malaiya
  • a,Colorado State University Department of Systems Engineering Fort Collins, CO. 80523 U.S.
  • b Colorado State University Department of Computer Science Fort Collins, CO. 80523 U.S.
Cite as
Scheibmeir J., and Malaiya Y. (2022).,A Social Media-driven Digital Twin of an Invasive Species. Proceedings of the 10th International Workshop on Simulation for Energy, Sustainable Development & Environment (SESDE 2022). , 002 . DOI: https://doi.org/10.46354/i3m.2022.sesde.002

Abstract

The digital twin concept and technology is helping improve life and business in many ways. Manufacturing, health, and supply chain systems benefit from digital twins’ predictive capacity to better plan and utilize costly and recently scarce resources. This research utilizes social media to drive a digital twin and model the propagation of an invasive species in the United States. 11,723 social media conversations considering the Spotted Lanternfly, an invasive species of insect that poises significant risk to crops and forests within the U.S., were utilized in the natural language processing and modeling. Converging the theory of sociomaterial assemblage and the emerging technology of digital twins, we have created machine learning models and an initial digital twin that predict the paths of these pests. This research advances modeling and simulation by applying the digital twin concept to the application of protecting industry against further natural disasters of crop destruction, resource and food shortage, and forest damage due to invasive species.

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