BRIAN KENNY: Artificial intelligence or AI for short is certainly creating a lot of buzz these days. And although it may seem like this amorphous thing that's somewhere off in our future, it's already very much in our midst. Navigation apps have turned printed maps into relics. Alexa, knows what you need from the grocery store before you do. Google Nest has the house at just the right temperature before you roll out from under the covers. And this is all great, but now you have to wonder if this intro is written by me or chat GPT. Which raises an important question.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The National Park Service (NPS) said Wednesday that a body had been recovered near Lake Mead's Boulder Islands. An adult woman had gone missing in Nevada's Lake Mead National Recreation Area on June 30, 2022. Park rangers located and recovered the body with the use of a remotely operated vehicle (ROV).

Images of elephants roaming the African plains are imprinted on all of our minds and something easily recognized as a symbol of Africa. But the future of elephants today is uncertain. An elephant is currently being killed by poachers every 15 minutes, and humans, who love watching them so much, have declared war on their species. Most people are not poachers, ivory collectors or intentionally harming wildlife, but silence or indifference to the battle at hand is as deadly. You can choose to read this article, feel bad for a moment and then move on to your next email and start your day.

In the wildlife reserves of East Africa, elephants, rhinos, gorillas, and other large mammals are hunted by poachers. All that stands between these animals and harm's way are small teams of park rangers and conservationists. The danger is very real for these species on the brink: A staggering 35,000 African elephants are killed each year, putting them just a decade away from extinction, according to the non-profit RESOLVE. Technology is an increasingly critical tool for protecting elephants and other large animals, given their necessarily expansive habitats: A group of just 50 rangers in Kenya, for example, covers a reserve of 3,000 square miles. Park rangers and conservationists have used motion-activated camera traps to catch poachers in action, but the animals are tragically already lost by the time rangers can respond.

Illegal wildlife poaching threatens ecosystems and drives endangered species toward extinction. However, efforts for wildlife monitoring and protection in conservation areas are constrained by the limited resources of law enforcement agencies. To aid in wildlife protection, PAWS is an ML pipeline that has been developed as an end-to-end, data-driven approach to combat illegal poaching. PAWS assists park managers by identifying areas at high risk of poaching throughout protected areas based on real-world data and generating optimal patrol routes for deployment in the field. In this paper, we address significant challenges including extreme class imbalance (up to 1:200), bias, and uncertainty in wildlife poaching data to enhance PAWS and apply its methodology to several national parks with diverse characteristics. (i) We use Gaussian processes to quantify predictive uncertainty, which we exploit to increase the robustness of our prescribed patrols. We evaluate our approach on real-world historic poaching data from Murchison Falls and Queen Elizabeth National Parks in Uganda and, for the first time, Srepok Wildlife Sanctuary in Cambodia. (ii) We present the results of large-scale field tests conducted in Murchison Falls and Srepok Wildlife Sanctuary which confirm that the predictive power of PAWS extends promisingly to multiple parks. This paper is part of an effort to expand PAWS to 600 parks around the world through integration with SMART conservation software.

What's New: Non-profit RESOLVE's* new TrailGuard AI* camera uses Intel-powered artificial intelligence (AI) technology to detect poachers entering Africa's wildlife reserves and alert park rangers in near real-time so poachers can be stopped before killing endangered animals. TrailGuard AI builds on anti-poaching prototypes funded by Leonardo DiCaprio Foundation and National Geographic Society. "By pairing AI technology with human decision-makers, we can solve some of our greatest challenges, including illegal poaching of endangered animals. With TrailGuard AI, Intel's Movidius technology enables the camera to capture suspected poacher images and alerts park rangers, who will ultimately decide the most appropriate response." How It Works: TrailGuard AI uses Intel Movidius Vision Processing Units (VPUs) for image processing, running deep neural network algorithms for object detection and image classification inside the camera.

Artificial intelligence created by Intel is to be used in cameras to detect poachers entering wildlife reserves and alert park rangers before they can kill endangered animals. The technology firm has announced its software is to be used in TrailGuard AI cameras that are capable of object detection and image classification remotely, and which can alert rangers should a person or vehicle be detected. The cameras are to be distributed around wildlife reserves by non-profit organisation Resolve, and have been built in partnership with the National Geographic Society and the Leonardo DiCaprio Foundation. They will be deployed in African wildlife reserves and throughout Southeast Asia in early 2019, the technology firm said. The pencil-sized devices contain a long-life battery, which can last up to a year and a half without needing to be charged.

Elephants are proverbially hard to miss, but even these huge beasts can be swallowed up in the vast plains of Africa. This is a big problem for park rangers whose job is to protect the animals from poachers. In Serengeti National Park in Tanzania, for example, there are just 150 rangers responsible for safeguarding an area of land roughly the size of Belgium. A new solution to this proposed by conservation nonprofit Resolve is to use AI-equipped cameras to act as remote lookouts. Today, Resolve announced a new custom-made device called TrailGuard AI, which uses Intel-made vision chips to identify animals and humans that wander into view.

The unrelenting threat of poaching has led to increased development of new technologies to combat it. One such example is the use of long wave thermal infrared cameras mounted on unmanned aerial vehicles (UAVs or drones) to spot poachers at night and report them to park rangers before they are able to harm animals. However, monitoring the live video stream from these conservation UAVs all night is an arduous task. Therefore, we build SPOT (Systematic POacher deTector), a novel application that augments conservation drones with the ability to automatically detect poachers and animals in near real time. SPOT illustrates the feasibility of building upon state-of-the-art AI techniques, such as Faster RCNN, to address the challenges of automatically detecting animals and poachers in infrared images. This paper reports (i) the design and architecture of SPOT, (ii) a series of efforts towards more robust and faster processing to make SPOT usable in the field and provide detections in near real time, and (iii) evaluation of SPOT based on both historical videos and a real-world test run by the end users in the field. The promising results from the test in the field have led to a plan for larger-scale deployment in a national park in Botswana. While SPOT is developed for conservation drones, its design and novel techniques have wider application for automated detection from UAV videos.

Poaching takes a brutal toll on the world's wildlife every year. By the thousands, rhinos are for their horns, elephants for their ivory, and tigers for their bones and exotic pelts. To protect these animals, rangers and conservationists must monitor enormous swaths of land, day and night, looking for poachers who trade on a black market estimated to total $40 billion. It's impossible to stop every poacher. New technology could bolster the efforts of conservationists, though, by putting a set of eyes in the sky.