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Publications

This page presents peer-reviewed research publications produced by SACAQM scientists.

Spatiotemporal Graph Neural Networks for PM2.5 Concentration Forecasting

https://doi.org/10.3390/air4010002

Review of IoT Systems for Air Quality Measurements Based on LTE/4G and LoRa Communications

https://doi.org/10.3390/iot5040032

AI_r: Transforming Air Quality Monitoring through Cost-Effective AI Solutions

https://doi.org/10.1109/IDAP64064.2024.10710650

A Cost-Effective Air Quality Monitoring System for the Global South

https://ieeexplore.ieee.org/document/10855074

Enhanced Underground Communication: A Circularly Polarized Smart Antenna with Beam Steering for Improved Coverage

https://doi.org/10.3390/mining5010014

A Scalable Reinforcement Learning Framework for Wireless Sensor Networks: Spatiotemporal Cluster-Based Multi-Agent Reinforcement Learning

doi:10.1109/ACDSA65407.2025.11166147

WhatsApp Image 2026-01-15 at 15.40_edite

Machine learning for air quality prediction and data analysis: Review on recent advancements, challenges, and outlooks

https://doi.org/10.1016/j.scitotenv.2025.180593

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