Designing an Intelligent Environmental Monitoring System for Vietnam Green Seaports

Air pollution is a complex problem for the world, particularly Vietnam. With the excessive number of ships operating and transporting goods, the air quality in these areas has become polluted and dangerous to human health. This paper presents the design and real-time application of an efficient adaptive neuro-fuzzy (ANFIS) inference system to monitor air quality at Vietnamese Ports. The system collects parameters such as PM2.5, CO, S02, and N02 in real time, and then the system calculates the AQI<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</inf> index to warn the operator about the pollution level. In addition, applying the ant colony optimization (ACO) algorithm helps increase the ability to transmit and receive data between stations. The training datasets of the adaptive N euro- Fuzzy inference system were extracted from the fuzzy logic controller model developed in MATLAB Simulink, and its robustness was verified experimentally. The research results increase the ability to monitor the quality of clean, green port environments today in Vietnam.