With six decades of innovation under its belt, the World Food Programme (WFP) has an eye for spotting emerging technologies that can have a profound impact on emergency response. So, it has been quick to home in on the power of machine learning to boost the speed and accuracy of post-disaster assessments and mapping and get more targeted assistance to the people who need it most.
In a watershed moment, WFP flew its first drones in post disaster assessment following cyclone Idai in Mozambique (2019). But, while the kit itself offers huge benefits for easy, affordable humanitarian operations, that’s only half the story. Perhaps less evident, is the second layer of technology that extracts the real value from the veritable goldmine of data buried in the high-quality images the drones collect. For this, WFP developed a Digital Engine for Emergency Photo-analysis (DEEP), which uses machine learning to turn that bird’s eye view into actionable information for response teams.