In some communities in Indonesia, real-time air quality information is not available, which is crucial for improving response efforts in regions affected by air pollution.
Pulse Lab Jakarta developed a model that leverages real-time sensing and integrates social media images. The model produced at best, 87.24 per cent forecast accuracy — an improvement of 18.11 per cent compared to the baseline model (that uses only satellite and air quality information) based on 2014 data from Pekanbaru, Riau.
Pulse Lab Jakarta has been working closely with the National Information Resources Service in the Ministry of Interior Safety of the Republic of Korea to provide technical assistance for a similar model that the Ministry is developing to monitor the prevalence of fine dust particles in South Korea.
Read more: Nowcasting Air Quality Using Social Media