AI-enhanced sensor networks strengthen pollution mapping and public health action
Published on: Oct. 1, 2025, 10:47 p.m. | Source: Devdiscourse
Machine learning has become the critical enabler for addressing these challenges. Traditional ML models, including random forest, gradient boosting, and support vector regression, have improved sensor calibration when sufficient co-location data with high-quality reference monitors is available. These models can adjust for sensor biases, correct systematic errors, and improve the comparability of data across networks.
