AI transforms humanitarian aid with space tech and predictive maps

Artificial intelligence is revolutionizing humanitarian aid, enabling safer delivery of supplies and earlier detection of food crises. Technologies originally developed for space exploration are being adapted to navigate conflict zones, minefields, and flooded areas.

AHEAD Project: Rovers for dangerous deliveries

The AHEAD project, a collaboration between the World Food Programme (WFP), the German Aerospace Center (DLR), the Red Cross, and technology partners, is developing remotely-operated vehicles to transport aid in hazardous environments. Based on DLR's experience building planetary rovers like the MMX rover for Mars moon Phobos, the SHERP all-terrain vehicle can traverse open water and rugged terrain while controlled from a safe distance Source: euronewses. This keeps humanitarians out of harm's way.

HungerMap Live: Predicting food insecurity

WFP's HungerMap Live platform uses machine learning to monitor food security in over 95 countries. It combines data on conflict, weather, climate risks, and economic conditions to identify emerging hunger crises. "Everybody can access it, HungerMap Live, on the internet. You can get real-time data and now we even analyze how to forecast food security 90 days in the future," said Bernhard Kowatsch, director of WFP's Global Accelerator and Ventures division Source: euronewses.

Disaster mapping with AI

After earthquakes struck northern Venezuela in June, Humanitarian OpenStreetMap used machine learning to extract building information from satellite images. Volunteers then reviewed the images via the MapSwipe app, marking damaged areas. "Within four days after the earthquake, we mobilized over 600 volunteers... swiping left and right on the mobile app, indicating if 'yes, this building area is damaged' or 'no,'" said Leen D'hondt, director of technology and data at Humanitarian OpenStreetMap Source: infobae. This rapid assessment helped prioritize aid distribution.

While AI speeds up response, D'hondt noted that the technology still cannot match the precision of detailed manual work.