Automated Systems for Applying Reagents for Oil Spill Elimination

Abstract

The article discusses the development and application of an automated oil spill response system using drones and autonomous underwater vehicles (AUVs). The system is based on mathematical models for optimizing drone trajectories and reagent dosage, as well as machine learning algorithms for adapting the system's actions in real time depending on sensor data and the spread of the oil slick. This allows for increased spill response efficiency, reduced reagent consumption, and minimized impact on the ecosystem. The article highlights the technological features of the system, including the use of GPS and infrared sensors, as well as machine learning methods for predicting the spread of pollution and dynamically adjusting the system's actions.