This project involves monitoring water and beach conditions using various data sources and machine learning models. We are developing an app that detects whether people are drowning in open water.
We developed a Python script that interacts with tidal and weather APIs, and calculated the level of risk.
- Wind: The strength of the wind determines the risk.
- Temperature: Colder temperatures increase the risk.
- Tide: The difference between the tides determines the level of risk.
- Decrease the zone of clarity
- Insert another method that would update the value
We created a model using YOLOv8n as a base to detect humans and swimmers.
- Enhance the risk calculation functions.
- Improve the accuracy of the swimmer detection model.
- Integrate additional data sources for more comprehensive monitoring.
- Have zone of clarity
- Clone the repository.
- Install the required dependencies.
- Run the Python script for tidal info.
- Use the YOLOv8n model for swimmer detection.
This project is licensed under the MIT License.