Air Quality Nodes & Dashboard
A consortium of AI, hardware, and public health experts have collaborated to develop a groundbreaking solution to air quality monitoring in the Global South. The Air Quality Nodes & Dashboard project utilizes low-cost air quality sensors, IoT-based technologies, and machine learning to provide real-time air quality measurements, as well as predictions based on trends.
The project, in collaboration with CERN Green Village and the University of Witwatersrand, will combine hardware components with an online web service application to process and display the data in a graphical format. This allows machine learning methods to be used on the data, developing models to predict air quality in the future. The project has already developed and deployed ten prototypes, which have been shown to be accurate and functioning ideally. The next stage is the deployment of these sensors in areas of low air quality in South Africa.
The project's expected outcome is the mass-production and deployment of these nodes throughout the Global South, particularly in areas that have been neglected in studies on air quality. The project will help inform decisions about public health, mining, real estate, and numerous other industries in the private and public sectors. The project is expected to last for two years.
With the Air Quality Nodes & Dashboard project, the consortium aims to bridge the gap in air quality monitoring and benefit the Global South through innovative technologies and scientific research.
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