Similie Timor, is developing an Early Warning System using ML and low-cost sensors to assess risk levels and mitigate the effects of natural disasters.

Results to date: The company has been working in the development of the solution with the government of Timor-Leste and the support of Mercy-Corps. In the last year of testing, the Early Warning System alerted the authorities of three flood events one hour prior to the event. The total population alerted and protected is 300,000 individuals in the island. 

Workplan: During the investment period, the machine learning (ML) algorithm will be trained to enhance the risk assessment tool to identify flooding in coastal regions more than one hour before the event happens. Leveraging the data collected and post-processing it through ML and other modelling solutions will generate improved predictions and will be possible to scale the solution in at-risk islands beyond Timor-Leste. 

Investment rationale: The team has a robust AI approach and model, and the resulting Open Source IP could have the potential to scale in the same region and other regions prone to weather hazards.