Conveners
AI and air quality data analytics: S7
- Rafael Borge (Universidad Politécnica de Madrid (UPM))
Effective air quality monitoring is essential because it alerts communities when pollution levels are high, allowing people to take necessary precautions. Traditionally, reliable monitoring requires reference-grade stations, but these are expensive and limited—especially in low-resource settings. The South African Consortium for Air Quality Monitoring (SACAQM) developed the AI_R system, which...
Gaining insight into the response of surface ozone (O3) formation to its precursors, primarily nitrogen oxides (NOx) and volatile organic compounds (VOC), is still challenging due to the complex formation mechanisms involved.
The subject of this study concerns a methodology for analysing O3 sensitivity to NOx and VOC precursors. The approach is based on the Machine Learning (ML) techniques to...
Large building and campus WiFi networks generate a huge amount of data from user activity and device counts. Working with data at this scale creates major challenges, as it becomes computationally expensive and slow to train models. To solve this, we propose using intra-domain transfer learning. Our method involves first training a model on one large, resource-rich WiFi dataset. We then adapt...
