FruitPunch AI for Wildlife: Development of an autonomous aerial vehicle for detection of wildlife poachers

To aid in the protection and conservation of the environment and its wildlife, the FruitPunch AI community aims to develop an autonomous UAV based solution to revolutionize the way monitoring and inspection of wildlife reserves is conducted.

Athina Ilioudi - AI for Wildlife project lead Tweet

The challenge

Most of you will know about the poaching crisis in Africa. More ambiguous is, why is it especially important now? With the middle class of many Asian countries growing, the demand for the luxury erection enhancing, cancer curing powder of rhino horn, ivory and pangolin scales is growing. Of course it doesn’t actually have any of these properties, rhino horn is made from keratin, the same stuff your nails and hair is made from. But that doesn’t stop the international black market from craving the product. Driving up the price of the endangered animals’ body parts higher than the price of gold. Motivating the poorest or most corrupt people to kill these beautiful animals by the ten-thousands.

The real solution here is to stop the demand by educating the masses that eating or keeping these body parts doesn’t do anything but make you an asshat. But unless we can stop this disease within the next 10 years, which is highly unlikely, many species will die out. Thus we also need to stop the bleeding. This means applying our best selves and our best tools to stop poaching in the wildlife reserves. And that is what we set out to do, using humanity’s most powerful tool, artificial intelligence.

Help us tackle the following challenges:

🍉   Flying time and range are limited with RC plane 
🥝   Specialized and skilled pilots for RC landing plane are required 
🍍   
Watching the black and white video stream for poachers through the night is prone to human error

🍒   Most drones can’t navigate where GPS is inaccurate or unavailable 
🍎   The application environment is characterized by strong dynamic external disturbances such as air force
🍊   
There is limited flying time due to battery capacity

Our first objective is to develop a robust control scheme for autonomous UAVs to compensate for model uncertainties, gravity forces, external disturbances like wind gust, sensor errors and even attacks. We will focus on two main topics:

  1. Human detection on the thermal camera live-feed
  2. Autonomous navigation and landing in complex and possibly GPS-denied environments

Quick facts

🥥  More than a thousand rhinos are slaughtered per year for their horns.

🍊  More than 100,000 african elephants were killed between 2014 and 2017 for ivory. And there are less than 4000 tigers in the world.

🍉   In Africa, almost 600 rangers charged with protecting wildlife were gunned down by poachers between 2009 and 2016 while working.

🥝   In the Democratic Republic of the Congo’s Virunga National Park, at least 170 rangers have been killed during the past two decades.

Source: National Geographic

Source: Wildlife justice

Partners

SPOTS
Strategic Protection of Threatened Species
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SyFly
TU/e student team developing a fixed-wing drone
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