Artificial Intelligence (AI) and its Role in Wildlife Conservation

What is AI?

AI is a branch of science in which computers are made to think and act like a human being. Even making decisions like humans. It is a technological invention that has seen tremendous growth in the past year. There are few basic fields in AI. Let us briefly look at them.

Machine Learning (ML)

Machine Learning (ML) is a branch of AI that focuses on the use of data and algorithms to imitate the way humans learn, gradually improving its efficiency. That is, ML is focused on building computer systems that learn from data. ML simulates human learning patterns to learn, grow, update, and develop itself by continually accessing data and identifying patterns based on past outcomes. Facial Recognition system is an example of ML.

Deep Learning (DL)

Deep Learning is a subset of ML that trains computers to process information in a way that simulates human neural processes. Human beings learn from examples and past experiences. In DL, the computers are taught to function in a similar way. An example is a driverless car or train that will stop automatically when it comes to a stop sign or distinguish between a pedestrian and a lamppost.

Did You Know?

• Data in computer systems is information that can be interpreted and used by computers.

• Algorithm is a set of instructions to perform a particular task. But an algorithm is not a computer code. It is written in plain English and usually created in the form of a flowchart with shapes and arrows, a numbered list, or pseudocode (a semi-programming language). Pseudocode is a detailed, readable instruction of what a computer program or algorithm should do.

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AI’s impact on wildlife study and conservation

Wildlife conservationists use AI technology to gather information from different habitats such as on land, air and water. The inputs to the AI equipment could be in the form of audio, video or wireless signals received from various transmitting gadgets such as drones, cameras, binoculars and wireless transmitters. The raw data once received is then processed using different AI techniques to yield information that is easy to analyze.

Some examples of where AI has been used are as follows:

• Preventing biodiversity loss by analyzing large amounts of data, monitoring intricate aspects of ecosystems, and reviewing trends over time.

Camera traps are AI-based devices that help track, monitor, and better understand the ecosystem’s health and biodiversity of wildlife in remote areas. Usually these traps are set up and left for weeks on end where they flash a picture whenever an animal walks by. Subsequently, AI is used to classify these animals in real time, identify individual animals, and detect illegal poachers. Photo Credit: https://www.smartparks.org

• Monitoring the health of endangered species on land, air and in water to prevent their further decline.

• Analyzing migration patterns of birds, animals, and sea dwelling creatures like dolphins and whales to help conserve habitats on land, air and sea. For example, the Sound Surveillance System (SOSUS) monitors the health of marine animals.

An AI-powered bird migration tracker called BirdCast is helping birders, scientists and even farmers map imminent bird migrations in striking visuals. Developed by Cornell University. Photo Credit: https://www.smithsonianmag.com

• Predicting when and where birds, reptiles, amphibians, and water-based animals are most vulnerable by processing vast datasets of animal behavior and habitat conditions.

• Putting a stop to poaching by tracking poachers using AI enabled drones.

South African conservationists scan live video from a thermal-imaging camera attached to a drone, looking for heat signatures of poachers stalking through the bush to kill rhinos. Photo Credit: https://phys.org. Original Photo taken by Denis Farrell

• Preventing the possibility of the extinction of a species by learning traits related to species interactions.

• Using AI to detect ambient noise as well as sounds of animals in ecosystems so that corrective actions can be deployed if needed.

Sounds of African Elephants. Cornell University researcher Peter Wrege and his team used neural networks, a subset of artificial intelligence, to collect and categorize data on savannah elephants in Central Africa. Audio recorders captured jungle sounds and subsequently used to build neural networks in collaboration with Conservation Metrics, a California-based company, to separate jungle noises and locate elephants and poachers. Photo Credit: https://aiworldschool.com

Did You Know?

• Neural networks are a subset of AI, representing a specific architecture inspired by the human brain, while artificial intelligence is a broader field focused on creating intelligent systems that can perform tasks requiring human-like intelligence.

• A convolutional neural network (CNN) is a type of artificial neural network used primarily for image recognition and processing, due to its ability to recognize patterns in images. A CNN is a powerful tool but requires millions of labelled data points for training.

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