mlsanityData to 14 Oct 2026

Towards an Open Global Air Quality Monitoring Platform to Assess Children's Exposure to Air Pollutants in the Light of COVID-19 Lockdowns

arXiv 2103.12505 ↗First posted 17 Mar 2021cs.HC cs.LGcited by 0

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Abstract (arXiv)

This ongoing work attempts to understand and address the requirements of UNICEF, a leading organization working in children's welfare, where they aim to tackle the problem of air quality for children at a global level. We are motivated by the lack of a proper model to account for heavily fluctuating air quality levels across the world in the wake of the COVID-19 pandemic, leading to uncertainty among public health professionals on the exact levels of children's exposure to air pollutants. We create an initial model as per the agency's requirement to generate insights through a combination of virtual meetups and online presentations. Our research team comprised of UNICEF's researchers and a group of volunteer data scientists. The presentations were delivered to a number of scientists and domain experts from UNICEF and community champions working with open data. We highlight their feedback and possible avenues to develop this research further.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 29 references that are in the map. First posted on arXiv 17 Mar 2021.

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References · 1

  1. 2019Interpretable machine learning: definitions, methods, and applicationscited by 305

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