IoT-enabled hybrid intelligent environmental management

The combination of rapid urbanization alongside industrialization causes environmental management to confront sophisticated challenges whose root is climate change. The current strategic tools show limited capability in dealing with the unpredictable conditions, as well as extensive information combined with changing operational environments. A powerful method for supporting sustainable environmental decisions involves integrating the intelligent hybrid systems, which include machine learning (ML) with fuzzy logic and neural networks, and evolutionary algorithms. The research evaluates hybrid models consisting of neuro-fuzzy and evolutionary-fuzzy systems to judge their practicality and relevance. The innovation of this study consists of addressing the complete treatment of hybrid intelligent systems (HIS) through environmental management applications while promoting practical implementation and teamwork between different fields of expertise. The report contains examples with performance comparisons that show how hybrid systems outperform traditional methods. The study reveals that combining multiple systems enables better environmental application results, which leads to more effective intelligent environmental policy solutions.