17-year-old creates ultra-efficient, inexpensive anti-poaching device to protect elephants

jeune fille 17 ans dispositif anti braconnage protéger elephants

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An iPhone, a drone and a modest thermal camera… It took no more than 17-year-old Anika Puri to create an anti-poaching system four times more effective than those currently used to protect elephants.

The idea came to the young woman four years ago, she explains to the Smithsonian Magazine. While visiting his family in India, he was surprised to see so many ivory items still for sale in the markets, even though the ban on elephant hunting had been in place for many years. In fact, elephant populations continue to decline around the world. Between 2002 and 2011, the population of African forest elephants, for example, decreased by 62%. In 2013, it represented only 10% of its potential, despite the supposed protection in place since the 1990s.

Monitoring systems are already in place. However, as he discovers, these are often surveillance systems based on visual recognition. They are too ineffective, as well as being extremely expensive. In fact, the type of thermal cameras used can cost up to almost 10,000 euros, says the site of the foundation that awarded it.

Anuka Puri then decides to roll up her sleeves. Passionate about the possibilities offered by the field of artificial intelligence, she uses her knowledge on the subject. Specifically, she uses machine learning. This is a technology that allows a program to “learn” by feeding on data, so that it can, for example, analyze situations on its own.

He’s managed to create a system using fairly simple tools: an iPhone and a relatively inexpensive thermal imaging camera, all attached to a drone. According to her, the system could cost around €300. All the interest of the project, therefore, does not lie in the physical structure itself, but much more in the software that she has developed with care. Instead of relying on a visual analysis of the species filmed, she focused on the movements of elephants and humans. ” I realized that we could use this disparity between these two movement patterns to increase the accuracy in detecting potential poachers. “, he explains to Smithsonian magazine.

Analyze the movements of elephants and humans.

During a conference on artificial intelligence, he meets Elizabeth Bondi-Kelly, a Harvard computer scientist. The latter is working on a wildlife conservation project using drones and machine learning. She then became his mentor for this project and allowed him to use a database collected in the field: the “Benchmarking IR Data Set for Surveillance with Aerial Intelligence” (BIRDSAI).

Using a machine learning algorithm, he created a model that can determine whether movements are made by elephants or humans, based on speed, group size, and many other things. He used 372 data sets, including 300 elephant movements and 72 human movements. The remaining 144 were used to test his model with data he had never seen before. His software later showed 90% accuracy in detecting humans. A method that is therefore four times more effective, he says, than those that already exist.

His invention, named ElSa, after Elephant Savior, earned him an award, in particular for his clear explanation of the project: the Peggy Scripps Award for Science Communication. She also won a prestigious award in the competition’s earth and environmental science category. The young she does not think to stop in such a good way. In the future, she wants to continue testing the effectiveness of her project and deploy it on the ground, in Africa. She also intends to extend it to other endangered species, such as rhinos. She also on the program: the optimization of the flight paths of drones, which have limited autonomy.


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