IdentifAI Tomorrow´s Disasters
Purpose and goal
The IdentifAI Tomorrow ´s Disasters project has developed a cloud-platform where image-data from drones automatically gets analysed by artificial intelligence, through visual image recognition. The project has focused on addressing flooding, the most common natural disaster in the world which causes great damage and cost to local populations, the environment and the economy. Emergency response teams are now able to identify risk areas earlier as well as provide quick, valuable insights once disaster has struck.
Expected results and effects
Disaster relief efforts can now get access to improved site information in natural disaster areas without requiring human analysis to the same extent as before which enables for natural disasters to be dealt with more efficiently and in a safer way. The project result has been tested and verified in the UNICEF humanitarian drone corridor in Malawi and is seen as a valuable tool to get access to automatically generated insights in natural disaster areas in a faster, safer and more efficient way than before. The project result is now being developed further with the goal to scale globally.
Planned approach and implementation
The project has collected large amount of image based drone data and applied different types of CV and ML algoritms to the data. The algoritms have been tested, evaluated, developed and trained to automatically identify, through AI visual image recognition, different objects (roads, houses and water) to more efficiently guide emergency response teams in natural disaster areas. The project result is a cloud-platform enabling for automatic AI analysis of image-data from drones in natural disaster prevention and response.