Harnessing Artificial Intelligence for Environmental Sustainability: A Comprehensive Review of Its Applications in Biodiversity, Energy, Transportation, and Water Management

Artificial intelligence has been applied to address a wide scope of environmental sustainability topics such as biodiversity, energy, transportation, and water management. Actions need to be monitored as soon as feasible in the benefits of environmental sustainability. This study is to find out to what extent AI have made participating in these important avenues by conducting systematic literature review. A systematic review uses predefined inclusion and exclusion criteria to identify all eligible scholarly papers, reports and case studies. An overview of the literature exposes the variety of uses of artificial intelligence (AI) technologies for environmental sustainability. Recent advances in machine learning have made it considerably easier to predict environmental services that the global community benefits from as a result of developments in biodiversity research. Additionally, there is a trend that more and more AI Apps and Machine Learning models are being used, especially for predicting and optimizing the conservation of water resources. Nowadays the energy business has a lot of focuses in neural networks, expert systems, fuzzy logic model, and pattern recognition. Further, this industry has come to acknowledge the need for computer vision applications and decision support systems.