Air pollution is a major global public health challenge responsible for numerous health issues in children. It is responsible for deteriorating environmental conditions with adverse outcomes on people’s health (Sofia, Gioiella, Lotrecchiano, & Giuliano, 2020). Public health experts agree that air pollution aggravates morbidity associated with respiratory and cardiovascular diseases (Katsouyanni et al., 2001; Künzli et al., 2000), and leads to premature mortality (Arden Pope III & Dockery, 2012; Vlachokostas, Achillas, Moussiopoulos, & Banias, 2011). The World Health Organization (WHO) assesses that more than 80% of people living in the urban context are subject to air quality levels above the emission limits (Sofia et al., 2020). The primary pollutants are carbon monoxide (CO), particulate matter (PM), nitrogen oxides (NO x), volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), ozone (O3), and sulphur dioxide (SO2). The levels of these pollutants continue to increase due to the rapid global industrialization and urbanization, especially in developing countries (Fu & Chen, 2017).
The adverse health outcomes due to air pollution exposures are wide-ranging. Epidemiological studies have demonstrated that air pollution exposures are associated with various respiratory diseases such as pneumonia, which is responsible for the deaths of 920,000 children under five years of age across the world annually (Adaji, Ekezie, Clifford, & Phalkey, 2019). Further debilitating effects of air pollution in children include bronchitis (Guarnieri & Balmes, 2014), asthma (Hooper et al., 2018), and long-term cognitive damage (Zhang, Chen, & Zhang, 2018). In expecting mothers, continuous exposure to air pollution results in lower birth weight, preterm birth, and stillbirth (DeFranco et al., 2015; Gehring et al., 2011; Liu, Xu, Chen, Sun, & Ma, 2019; Yang et al., 2018). This is especially true in Mongolia, which experiences severe air pollution during the winter seasons. In a recently published report by the World Health Organization (WHO), it was reported that about 80% of the air pollution in Mongolia in the winter months is caused by low-pressure boilers and burning raw coal (World Health Organization, 2019). In 2018, citizens in the Ulaanbaatar (UB) district breathed toxic air, as defined by environmental agencies, in 322 out of 365 days. Low-income families are disproportionately affected, and the homes and schools lack air filtration systems.
Current surveillance and data ecosystems only provide limited insights on individual exposure to air pollution due to a limited number of sensory stations, outdated and complex data ecosystems, and lack of user-friendly portals and dashboards for accessing and exploring these data. Hence, the application of artificial intelligence (AI) on such data is often limited due to the low volume of data produced. Furthermore, population-level studies can take years to be completed due to challenges associated with knowledge access and mobilization, and the general public and public health officials rarely have access to real-time information. Big data infrastructure often available for big corporations and research institutions in developed countries is rarely available for supporting underserved populations in low and middle-income countries (LMICs) (Knight et al., 2019).
The purpose of this project is to create a real-time, crowdsourced, IoT-based air quality monitoring ecosystem using IoT sensors. In doing so, these data can then be used by the national public health agency to expedite the necessary steps to mitigate the adverse impacts of air pollution. Therefore, the specific research question that we are looking to address for this project is if real-time data monitoring combined with AI allows public health officials to monitor the harms of air pollution. The specific outcomes we are looking to address is a reduction of hospitalizations to mothers and children in the UB district.