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High‑school students pitch AI tool to detect Japanese knotweed to Mill Creek public works
Summary
Two Henry M. Jackson High School students described an AI detection system that combines satellite and aerial imagery with drone verification to locate Japanese knotweed monocultures; public works staff agreed to schedule a full presentation.
At the March 3 council meeting two students from Henry M. Jackson High School described an AI‑based method to detect and monitor invasive Japanese knotweed and asked to give a full presentation to city public‑works staff.
The students — who identified themselves as S. Shvasville and Aiden Kim — said they had located a previously undocumented knotweed monoculture near East Side Church adjacent to a North Creek corridor and described an approach that combines government aerial imagery, Sentinel‑2 multispectral satellite data, vegetation indices (NDVI), and machine learning. They said their winter detection accuracy ranged from about 70% to more than 95% after applying a new parameter the students developed and that they plan to verify detections with drone‑based ground truthing.
“We hope we can work with Mill Creek to help detect invasive species before they become a problem,” the students said, and asked for a presentation slot; council and staff encouraged them to coordinate with public works for a full demonstration.
Public‑works staff present confirmed prior conversations and said a full presentation would help staff evaluate feasibility, integration with existing inventories and any cost implications for city monitoring programs.
