Multi-agent system for monitoring and prediction of environmental processes

The paper explores the development of a multi-agent scalable system (SMA) concept for monitoring and predicting environmental processes, addressing the challenges related to the organization of distributed computing processes and the application of knowledge-based models, machine learning and artificial intelligence. SMA offers an innovative solution based on autonomous agents that perceive the environment, collaborate with each other, with the data storage center and implement advanced computing models. The technical and technological development of the system provides for the use of a set of smart sensors and devices, such as the ESP32, which integrate acquisition, data preprocessing and network communication services. The agent functional diagram and the algorithm for collaboration between agents and the data storage center were developed. The process of predicting environmental events is based on the application of neural network models. It was analyzed the carbon dioxide pollution scenario and its evolution to validate the proposed concept. The paper demonstrates that multi-agent systems can provide efficient and scalable solutions for managing environmental problems, to help to prevent crises and to support environmental protection policies.