Rip Current: A Potential Hazard Zones Detection in Saint Martin’s Island using Machine Learning Approach

Abstract

Beach hazards would be any occurrences potentially endanger individuals aswell as their activity. Rip current, or reverse current of the sea, is a typeof wave that pushes against the shore and moves in the opposite direction,that is, towards the deep sea. The management of access to the beach sometimes accidentally push unwary beachgoers forward into rip-prone regions,increasing the probability of a drowning on that beach. The research suggestsan approach for something like the automatic detection of rip currents withwaves crashing based on convolutional neural networks (CNN) and machinelearning algorithms (MLAs) for classification. Several individuals are unableto identify rip currents in order to prevent them. In addition, the absenceof evidence to aid in training and validating hazardous systems hinders attempts to predict rip currents. Security cameras and mobile phones have stillimages of something like the shore pervasive and represent a possible causeof rip current measurements and management to handle this hazards accordingly. This work deals with developing detection systems from still beachimages, bathymetric images, and beach parameters using CNN and MLAs.The detection model based on CNN for the input features of beach imagesand bathymetric images has been implemented. MLAs have been applied todetect rip currents based on beach parameters. When compared to other detection models, bathymetric image-based detection models have significantlyhigher accuracy and precision. The VGG16 model of CNN shows maximumaccuracy of 91.13% (Recall = 0.94, F1-score = 0.87) for beach images. Forthe bathymetric images, the highest performance has been found with anaccuracy of 96.89% (Recall= 0.97, F1-score=0.92) for the DenseNet model of CNN. The MLA-based model shows an accuracy of 86.98% (Recall=0.89,F1-score= 0.90) for random forest classifier. Once we know about the potential zone of rip current continuosly generating rip current, then the coastalregion can be managed accordingly to prevent the accidents occured due tothis coastal hazards.