WAVE WAKE SIGNAL CLASSIFICATION USING K – NEAREST NEIGHBOR

Abstract

This project is about the wave wake signal classification using K-Nearest Neighbor which is induced by two selected boats 6.4 meter and 8.53 meter lengths higher and lower than 10 knots speed at Jetty Kampung Baharu, Lumut, Perak. The characteristic of wave induce by boats is different based on the specifications of the boat itself. When the boats navigate, wave wakes will generated by the impact of hull geometry, boat’s speed and propeller. The wave characteristics analyzed from the data collected. Some number of equipment used to measure wave wake’s parameters. Wave height is collected instantaneously with water temperature using water level logger. Besides that, the writer also records the video during boat crossing for verification purpose. The K- Nearest Neighbor algorithms is applied for classification. Analyzing the wave wake data using KNN algorithms is more better because it give distinguish result to evaluate parameter of wave wake. Based on the result, type of boat recognize from analyzing wave height using K d-tree. It will classify based on the tabulate data of wave wake generate by boats which is boat size 8.53 meter will give higher wave height compare to boat 6.4 meter. Lastly, develop monitoring system for user interface by using Guide User Interface function in MATLAB. The concept of xi this monitoring system is to ease user import wave data to analyze time and type of boat crossing. Type of boat and time boat crossing display for user information. Development of wave wakes monitoring system is hopefully give some benefits in order to reduce severe erosion on river bank due to boats activities.