Air Quality Monitoring and Forecasting
This cluster of papers focuses on the advances in low-cost air quality monitoring systems, utilizing technologies such as neural networks, forecasting models, and IoT-based sensor networks to monitor particulate matter and pollutants in urban environments. The research explores the application of machine learning and environmental monitoring techniques to improve the accuracy and accessibility of air quality data.
Papers listed on taxonomy pages are the top few works per node from the OpenAlex snapshot. That list is not exhaustive and is not an endorsement. The topic map and the journal registry remain separate: there is still no authoritative topic-to-venue or topic-to-organization edge. Search is a lexical lookup, not a claim that a venue publishes a topic.