Teenager invents low-cost device to detect elephant poachers in real time

A 17-year-old has invented a low-cost way to track elephant poachers in real time.

High school student Anika Puri has created a machine-learning-driven model observing the movement patterns of humans and elephants, according to BusinessNews.

And to think, when I was 17, I thought ludicrous was spelt like the rapper, but it's good to know the future is in the hands of some tech-savvy teens.

While drones are mostly used to detect elephant poachers, Anika says these devices can be inaccurate, which is what prompted her to invent ElSa (short for elephant saviour).

According to Anika, ElSa is four times more effective than drones as the technology can analyse movement patterns in thermal infrared videos of humans and elephants.

“I realised that we could use this disparity between these two movement patterns in order to actually increase the detection accuracy of potential poachers,” the New York native said.

But not only does it do the job, but the machinery eliminates the need for expensive high-resolution thermal cameras.

ElSa uses a $250 (AUD $365 or £146) FLIR ONE Pro thermal camera that can be plugged into an iPhone 6. 

The camera and iPhone, while attached to a drone, flies over parks detecting if movement is coming from either an elephant or a human.

EyeEm / Alamy Stock Photo

Anika was inspired to invent this innovative piece of technology while visiting India four years ago when she came across a market in Bombay selling large quantities of ivory jewellery.

She said: “I was quite taken aback. Because I always thought, ‘well, poaching is illegal, how come it really is still such a big issue?’”

After conducting a little research of her own and finding out that Africa’s forest elephant population had declined by about 62 per cent between 2002 and 2011, the animal lover felt obliged to do something.

Equipment ecologist at Wageningen University in the Netherlands Jasper Eikelbloom noted that the low-budget equipment was ‘remarkable’ as it could be used for broader conservation research as well.

“In ecology in general, we like to track animals and see what they're doing and how it impacts the ecosystem,” he said.

“And if we look, for example, on the satellite data, we can find a lot of moving patterns, but we don't know what species they are. I think it's a very smart move to look at these movement patterns themselves instead of only at the image—at the pixels—to determine what kind of species it is.”