Artificial intelligence in environmental monitoring: Advancements, challenges, and future directions

• AI-driven pollution detection enhances environmental protection. • Real-time monitoring facilitates prompt interventions for pollution prevention. • Accurate air quality forecasting aids in planning pollution-reducing activities. • AI's role in smart cities fosters sustainable urban development. • AI algorithms integrate diverse data sources for pollution detection. The application of Artificial Intelligence (AI) in environmental monitoring offers accurate disaster forecasts, pollution source detection, and comprehensive air and water quality monitoring. This article provides an overview of the value of environmental monitoring, the challenges of conventional methods, and potential AI-based solutions. Several significant AI applications in environmental monitoring are highlighted, showcasing their contributions to effective environmental management. AI technologies enhance environmental monitoring by enabling better understanding, prediction, and mitigation of environmental risks. However, realizing the full potential of AI faces hurdles such as a shortage of specialized AI experts in the environmental sector and challenges related to data access, control, and privacy. These issues are more pronounced in regions with developing technological infrastructure. The paper advocates for proactive data governance measures by governments to protect sensitive information. Despite these challenges, the future of AI in environmental monitoring remains promising, with advancements in AI algorithms, data collection techniques, and computing power expected to further improve accuracy and efficiency in pollution monitoring and management.