Can AI Detect Water Hazards? Detecting RipCurrents and other Water-Related Hazards via a Convolutional Neural Network (CNN)
Applied Technology- Grade:
- 7
- Teacher:
- Nicholas Young
This project involves building and testing an AI to detect water-induced hazards like rip currents, strong waves, and flash floods in advance. It can analyze any kind of media, including photos and videos. It uses a convolutional neural network, a type of deep learning model used for visual analysis. It uses a variety of different layers and features like matrix multipliers, dilations, convolutions, MaxPooling, a ReLU Activation Feature, and many more to do this. It scored a top accuracy of 99.5%, and I currently have a web application where it can be accessed (https://nereos-ai.onrender.com). This project will help multiple first-responder professions and assist with their duties, and it even provides a simple, easy-to-use interface for casual users to detect hazards with.
I love your enthusiasm for solving the problem of water hazards. It shows that you care and love providing solutions to problems. This is extreme great. Also, you show a great understanding of water hazard, and how it ca be tested and detected, I enjoyed reading your plan on how to solve this problem, you did a fantastic job!