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The Smart Wildlife Movement Prediction and Tracking System utilizes historical animal location data and machine learning techniques, specifically K-Nearest Neighbors regression, to predict animal movements for wildlife conservation. It features a user-friendly web interface that visualizes animal paths and predicted zones on a map, enhancing monitoring efficiency. The system demonstrates improved prediction accuracy over traditional methods and has potential for future enhancements like real-time GPS integr

Author

nchipole11

Language

EN