Search and rescue (SAR) operations operations are being made more effective by the use of computer vision based AI models. Every year millions worldwide have first hand experience of large natural disasters. And every day hikers, climbers, and other outdoor adventurers get lost, injured, or stranded. In order to protect lives, emergency services and NGOs have developed search and rescue operations, incorporating the best practices and the latest technology. This is continuing today as AI is beginning to be incorporated into search and rescue efforts. By supporting SAR teams this technology has the capacity to save lives across the globe.
The development of search and rescue AI applications is reliant on access to quality image and video data, data that reflects the complexity of disaster and wilderness contexts. This blog will assess some of the exciting developments in this field and suggest ways in which annotation providers, like Keymakr, can facilitate further progress.
Mapping disaster landscapes
In the event of a natural disaster it is essential that SAR teams know where the most badly affected areas are so that they can target their search. Image recognition and classification technology can rapidly analyse thousands of images, from satellites or aerial photography, and identify the areas most in need of a SAR response. AI models are extremely efficient and accurate when observing and categorising features such as damaged buildings, flooding, and blocked roads. By processing large amounts of image data quickly AI applications can save valuable time for SAR. These models can also run analytics to suggest areas of significant damage to governments and organisations.
Annotated image data is vital for the smooth functioning of this technology. Semantic segmentation annotation splits images of disaster zones into relevant classes, pixel-by-pixel. This allows AI models to distinguish between flooded areas and normal bodies of water, or between collapsed buildings and safe structures.
Locating missing persons with drone AI
When someone goes missing in wild areas it can be incredibly difficult to find them. Large wilderness spaces can take months to adequately cover, a search that may require hundreds of individuals to accomplish. Thankfully drones have shown the potential to speed up the hunt for missing persons through the use of computer vision AI. Drones, and drone swarms are being developed with the aim of surveying large areas and identifying the presence of any missing persons, all completely autonomously.
Aerial image and video annotation are essential for the success of drone based SAR. Bounding box annotation can be applied to a variety of images to locate humans and allow AI models to distinguish them from their surroundings. Quality data is also of crucial importance when lives are on the line. Keymakr ensures that errors and bad labeling do not make it to final training datasets by employing multiple layers of quality control.
Search and rescue robotics
The final frontier for SAR AI is having robots and autonomous vehicles find survivors and pull them out of dangerous situations without direct human control. To achieve this multiple researchers and AI companies have been refining precision automated movement, and object detection and avoidance. One example is RoboSimian from NASA, a robot with multiple sensors in its limbs, capable of interpreting and navigating complex environments. It is hoped that this technology will allow robots and tracked vehicles to successfully navigate disaster areas and wild places, in order to find and extract individuals in danger.
Diverse data is extremely valuable for the continued flourishing of this exciting SAR technology. It is often difficult for companies and research groups to find the variety of specialised training images that their models need to be fully successful. Providers, like Keymakr, are experts at data collection, and can remove this time consuming burden from innovators.
Data Annotation Supports Search and Rescue R&D
Keymakr leverages an in-house team of experienced annotators overseen by quality focused managers to meet the demands of today’s SAR AI leaders. Contact a team member to book your personalized demo today.