AI News, Artificial intelligence helps wildlife rangers combat poaching artificial intelligence
From AI to Drones, Smart Technology is Firing Up Wildlife Conservation Globally
By 2017, rhino poaching in the sanctuary was reduced by a whopping 96% – a resounding success that has resulted in the expansion of this programme to Kenya, Zambia and Mozambique this year.
In June in Cambodia, for instance, the conservation outfit Global Park Defence System set up by Wildlife Alliance, a global conservation network, saved a critically endangered pangolin from being poached when the rangers got alerted of suspicious movement by a hidden camera.
Over the last six years, Wildlife Alliance has removed 109,217 snares (traps that can injure or kill anything from elephants to mice) from a single park in Cambodia: an alarming number that only highlights the need for the protection of wildlife in this region.
Drones can help with aerial review of animals without disturbing them, too, but some animals are shy and are not easy to spot, which is when thermal imaging steps into the fray, providing a more accurate picture of animal movement, especially in the dark when poachers are most likely to strike.
Artificial Intelligence has also come to the aid of the wild, with bots and algorithms combing the internet for data such as animal sightings and other useful information that can help protect threatened species.
(This is a double bonus as the wind turbines also provide clean energy!) All sorts of exciting possibilities exist today – including the use of technology and science to fake elephant tusks to reduce the poaching, as well as using acoustics to protect marine wildlife—and surely more will come in the future with the advancement of technology.
Perhaps we can be a little optimistic of the future after all – perhaps, in the future, we won’t ever have to debate again if we humans have indeed wiped out 60% of the world’s animal species.
The Technology That Will Finally Stop Poachers
Just outside this 62,000-hectare reserve—which is tiny compared to Kruger’s one million hectares—poachers lurk, desperate to hack the horns off of some the park’s most magnificent animals.
Considering that a rhino horn fetches $60,000 or more per kilogram on the black market, many thought it was worth the risk.
Just last year, one ranger, who wishes to remain anonymous for his own safety, noticed that one employee couldn’t look him in the eye.
In 2016, the first 18 months that new tactics were deployed, poaching fell by 96 per cent.
And while poaching remains an extraordinary problem throughout the country, this year, at this park, not a single rhino has been slaughtered—a figure tracked daily on a board at the park’s headquarters.
And the reserve’s tactics—a wise mix of new technology, old-fashioned sleuthing, and social enterprise—have been so effective, other countries want to know how it’s done.
In the least intrusive way possible: by creating a virtual net around the reserve, a point-to-multipoint router network and using the Internet of Things to track people rather than wildlife.
says Watson.) 'While better tags and more sophisticated sensors are being developed, by the time the alarm is raised, it’s usually too late,”
That basic hut is still standing, but what goes on inside it has been transformed, as security information from around the park is transmitted back and analyzed.
Day and night, two rangers sit inside the building, glued to several monitors displaying live feeds from CCTV and thermal cameras along the perimeter that are rugged enough to withstand poachers’
Each of the park’s four gates have been supplied with a local-area network and long-range technology within the reserve, providing Wi-Fi and allowing staff to communicate and see live data while on patrol.
Stout, seasoned, and with a thick Afrikaans accent, the head of security plots the progress of his patrols on a map in his “war room.”
A wall map marks sightings of rhinos, progress of patrols, and potential hot spots, where poachers will try to break in.
After 22 years in the military, the head of security now enjoys watching the big game from his veranda and has come to appreciate his country’s heritage.
Acoustic fiber has been fitted along the electrified fence and sounds an alarm if wires are cut, and thermal cameras capture movements.
These could sound the alarm if someone passes above them with anything metallic, such as a gun, allowing security heads to keep tabs on what all sensors are revealing, wherever they are.
The head of security will touch base with communities and police forces outside the park, trying to keep tabs on whereabouts of illegal weapons.
In the past year, an estimated 1,000 poaching syndicates existed on the park’s borders, says the park’s security chief.
Each horn, which weighs up to seven kilograms, will earn a poacher anything from a five-kilogram bag of cornmeal to roughly 150,000 rand—nearly five years’
Mostly American tourists enjoy safari drives punctuated by sundowner cocktails, breakfasts on the veranda, plunge pools, and bathrooms larger than a small apartment.
A similar project is about to be rolled out in a private Kenyan reserve, funded by the same alliance, but each location demands a bespoke solution.
Although technology companies have bankrolled these projects to date, Watson is keen to urge philanthropists and the private sector to put up cash for the future.
The project aims to develop platforms for machine-learning algorithms that will be able to identify single species amid thousands of images.
This could allow conservationists to count and monitor wildlife without disturbing it, but also throws up large amounts of data which requires handling.
But a new project between ZSL and the Arribada Initiative has produced cheaper, less obtrusive tagging that allows conservationists to follow turtles in the ocean and assess threats faced by turtles off the beaches of Principe Island in West Africa and understand how issues such as plastic pollution affect their behavior.
Tags take video clips at timed intervals and are attached to turtles via a base plate with a quick-release mechanism, minimizing stress for the turtles.
Machine Learning vs Poachers
The preservation of wildlife costs us millions of dollars, while there are many other problems of humankind that require immediate support such as fighting hunger or poverty.
The global tiger population has dropped over 95% from the start of the 1900s and has resulted in three out of nine species extinctions.
Poaching also provides significant profits to terrorist organizations, “which are which are attracted to wildlife trafficking because of its low risk of detection, high profits, and weak penalties”.
In 2013 researchers from the University of South California (USC) in collaboration with Uganda Wildlife Authority (UWA) developed PAWS (Protection Assistant for Wildlife Security), an AI algorithm which analyses historical information on previous poaching activities and designs the most effective routes for patrolling by trying to predict where the next poaching activity will happen.
After an initial launch in Uganda, in 2014 PAWS was rolled out in Malaysia to further increase the amount of data available for analysis and test adaptability of PAWS in other geographical zones.
Currently, the project team is working on: Larger PAWS needed In my opinion short-term the project team needs to focus on improving the predictability of the model, which can be done by deriving larger sets of data.
To speed up the roll out the PAWS project team should learn how to quickly optimize the algorithm for different terrain conditions, as well as design easy-to-understand interface to make transferring PAWS management to local patrol teams as smooth as possible.
The success of the PAWS project should be highly publicized and, as a result, motivate tech companies and research labs engage in other wildlife conservation initiatives.
- On 5. marts 2021
Catching poachers with high-tech cameras
At the Mara Conservancy in Kenya, thermal-imaging cameras with artificial intelligence are helping rangers stop poachers in their tracks.
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