Poor air quality is especially prevalent in developing countries like those in lower delta Mekong. They have inefficient modes of transport and inefficient combustion of household fuels for cooking. Coupled with limited access to healthcare, health conditions of Mekong citizens exacerbate.

Our aim

  • Create a visualisation and prediction model to monitor air quality in Mekong countries.
  • Allow stakeholders to contribute suggestions to lower emission levels.
  • Communication channel for fast roll out of measures whenever necessary

How it works

  • Using past carbon emission data, predictions are generated. When countries are exceeding their emission thresholds, they receive a warning.
  • The current prediction algo uses a double exponential smoothing model. Algo can be improved by using neural networks to weigh different factors contributing to high air pollution level.
  • Target audience: Leaders of various sectors
  • When a certain solution is selected, a pre-written mail is then sent to relevant authorities informing them on the immediate measures implemented allowing them to take action
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