A 17-year-old creates an ultra-efficient and inexpensive anti-poaching device to protect elephants

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jeune fille 17 ans dispositif anti braconnage protéger elephants

⇧ [VIDÉO] You may also like this partner content (after the ad) An iPhone, a drone and a modest thermal imaging camera… 17-year-old Anika Puri needed more than enough to create a system against the poaching four times more effective than those currently used to protect elephants. The idea came to the young woman four years ago, she explains to Smithsonian magazine. Visiting with his family in India, he was surprised to see so many ivory items still for sale in the markets, even though the ban on hunting elephants had been in place for many years. In fact, elephant populations continue to decline worldwide. Between 2002 and 2011, the population of African forest elephants, for example, declined by 62%. In 2013 it represented only 10% of its potential, despite protection supposedly in place since the 1990s. Monitoring systems are already in place. However, as she finds, these are often surveillance systems based on visual recognition. They are too ineffective, as well as being extremely expensive. Indeed, the type of thermal cameras used can cost close to 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, it uses machine learning. It is a technology that allows a program to “learn” by feeding on data, so that it can then, for example, analyze situations by itself. He managed to create a system that uses fairly simple tools: an iPhone and a relatively inexpensive thermal imaging camera, all connected to a drone. According to her, the system could cost around €300. Therefore, the whole interest of the project lies not in the physical structure itself, but much more in the software that he has carefully developed. Instead of relying on a visual analysis of the species filmed, he 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 of detecting potential poachers,” he told Smithsonian magazine. Analyzing the movements of elephants and humans During a conference on artificial intelligence, he meets Elizabeth Bondi-Kelly, a computer scientist at Harvard. 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 “BIRDSAI” (BIRDSAI). Using a machine learning algorithm, he created a model that can determine whether the movements are made by elephants or humans, based on speed, group size and many other things. He used 372 datasets, including 300 elephant movements and 72 human movements. The remaining 144 were used to test their model on data they had never seen before. Their software then showed 90% accuracy in detecting humans. A method that is, therefore, four times more effective, he says, than those that already exist. His invention, called ElSa, for Elephant Savior, won him an award, especially for his clear explanation of the project: the Peggy Scripps Award for Science Communication. It also won a prestigious award in the earth and environmental sciences category of the competition. The young woman has no intention of stopping on such a good path. In the future, he wants to continue testing the effectiveness of his project and deploy it on the ground, in Africa. It also aims to extend it to other endangered species, such as rhinos. Also on the agenda: optimizing the flight paths of drones, which have limited autonomy.
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