ASAQ Seminar Series

Session

AI and air quality data analytics

4 Dec 2025, 10:40

Online

Conveners

AI and air quality data analytics: S7

• Rafael Borge (Universidad Politécnica de Madrid (UPM))

31. Cost-effective, High impact : the AI_r system for Air Quality Monitoring

Manal Karmoude (University of the Witwatersrand (ZA))

04/12/2025, 10:40

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...

16. Applicability of the explainable machine learning techniques in surface Ozone simulation and formation sensitivity analysis

Roberta Valentina gagliardi (istituto superiore di sanità)

04/12/2025, 10:55

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...

32. A Scalable Framework for Sensor Data: Intra-Domain Transfer Learning in Wi-Fi Networks and Air Quality Monitoring

Mr Raghav Chandna (University of the Witwatersrand and iThemba Labs), Prof. Bruce Mellado Garcia (University of the Witwatersrand and iThemba Labs)

04/12/2025, 11:10

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...

28. "LIVESTAQSENS": AI-Calibrated Network of CH₄ and NH₃ Sensors for Monitoring Air Quality in Livestock Farming

Ambra Fioravanti

04/12/2025, 11:25

Intensive livestock farming, with high animal density, is widely used to meet the growing demand for meat but negatively impacts air, water, soil, climate, and biodiversity. Ammonia (NH₃) and methane (CH₄) are the main air pollutants, and farmers are adopting strategies to reduce their emissions. This requires continuous, widespread monitoring using reliable, low-cost devices. However,...