Poster Title

Improving Ecosystem Quality Through Data Mining Application

Grade Level at Time of Presentation

Senior

Institution

Western Kentucky University

KY House District #

Susanne Miles

KY Senate District #

Joe Bowen

Department

Dept. of Information Systems

Abstract

The main objective of this research is to develop an automated predictive water quality control system for Kentucky’s natural water ways. The health and sustainability of our ecosystem is paramount to the wellbeing our state. Keeping our waterways healthy ensures that the agriculture and aquaculture sectors remain a strong industry for current and future Kentuckians. Using data sets from the Green River Preserve and other Kentucky organization of field station sites, we are implementing data mining algorithms to predict instances of harmful levels of pollution. These algorithms will uncover where and when our attention should lie to effectively improve our state’s waterways while simultaneously creating a very detailed image of how Kentucky’s ecosystem changes over time. When implemented this system will collect data for vital to biological research and send alerts when certain factors such as oxygen saturation, E. coli levels, and certain herbicide and fertilizer chemicals exceed healthy or acceptable levels necessary for local wildlife populations. Once this system is fully integrated in Kentucky, the platform can be expanded to the other states, not only improving scientific research and understanding through mass data collection and sharing, but also by improving the health of the United States’ ecosystems by use of automated monitoring for efficient management.

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Improving Ecosystem Quality Through Data Mining Application

The main objective of this research is to develop an automated predictive water quality control system for Kentucky’s natural water ways. The health and sustainability of our ecosystem is paramount to the wellbeing our state. Keeping our waterways healthy ensures that the agriculture and aquaculture sectors remain a strong industry for current and future Kentuckians. Using data sets from the Green River Preserve and other Kentucky organization of field station sites, we are implementing data mining algorithms to predict instances of harmful levels of pollution. These algorithms will uncover where and when our attention should lie to effectively improve our state’s waterways while simultaneously creating a very detailed image of how Kentucky’s ecosystem changes over time. When implemented this system will collect data for vital to biological research and send alerts when certain factors such as oxygen saturation, E. coli levels, and certain herbicide and fertilizer chemicals exceed healthy or acceptable levels necessary for local wildlife populations. Once this system is fully integrated in Kentucky, the platform can be expanded to the other states, not only improving scientific research and understanding through mass data collection and sharing, but also by improving the health of the United States’ ecosystems by use of automated monitoring for efficient management.