Tsavo, a region in Kenya, contains the world's largest elephant population, and thus, it is a prime target both for poachers and conservationists. Nonetheless, policing the 8,150-square-mile area is a daunting task. With some clever math and the help of drones, though, Penn State University researchers are helping to make that task much easier.
The idea of how to effectively patrol large areas is a very old and well-studied math problem. Because elephants can travel 20 to 40 miles per day, effectively narrowing down search areas is critical to being able to monitor their well-being. In the case of poachers, it comes down to understanding two things: where the elephants are and where poachers are most likely to attack them. Michael Shaffer, a former master's student in geographic information systems, notes that elephants need water, and poachers are likely to look for them in such areas. On the other hand, poachers likely want roads near elephant habitats for fast entrances and escapes. After combining all this information and performing a statistical analysis, researchers found that 85 percent of poaching incidents happened in shrub or savannah areas.
Once these areas were identified, drones could be programmed to fly mathematically efficient paths to monitor the areas. This not only allowed for more effective patrol of the areas, but it also reduced the risk to conservationists by preventing them from having to physically patrol the areas and risk confrontation with poachers. It's also far cheaper than using helicopters. The beauty of the new model is that the math essentially applies independently of the location; in other words, it can be adapted most anywhere by using that region's specific data. With so many stories of mishaps involving drones, it's great to see such a neat and beneficial use of them.
Lead Image by Flickr user Remy Rossi, used under Creative Commons.