Artificial Intelligence in Biodiversity: How AI can help in Animal Conservation?

December 13, 2020 6 min read By Cogito Tech. 1199 views

As per the latest reports, by the end of 2020, the population of wild animals living on the Earth is expected to fall by two-thirds. Few folks don’t care about animals and don’t know how their natural habitats are affecting the lives of other living beings on this planet.

This process in continuation is bound to disturb the biodiversity of the Earth. Conservation of natural biodiversity of the planet is vital for the smooth functioning of our natural ecosystems. Every animal, even a single plant or a small fungus is a part of a bigger system, and if they disappear, it will affect the parts of the ecosystem resulting in instability and eventually the collapse of the entire system.

Hence, saving the biodiversity of the Earth is important to maintain the balance in the entire eco-system. But existing wildlife monitoring system is either incapable of scaling globally or does not have the right resolutions or you can even say, the fine-scale data is often not within the reach of the authorities.

As a conventional practice, researchers work tediously to complete manual tasks like identifying specific animals from photoshoots of demographical studies. Later on, after spending more time and effort, these camera photos were classified manually.

But now, thanks to the advanced level of technologies like Artificial Intelligence (AI) and Machine Learning (ML), such tasks can be performed more efficiently with better results. Yes, the fully-integrated AI & ML-based solutions in wildlife conservation can help us to save the entire biodiversity of the Earth.

Also Read: What are the Common Myths about Machine Learning?

How AI can Help in Saving the Biodiversity?

Animal conservation is becoming one of the key issues in saving biodiversity on the Earth. AI can play a vital role in detecting, recognizing, and keeping track of wild animals wandering in their natural environment or conserved within the wildlife sanctuaries.

Most importantly, AI can help in preventing the extinction of endangered plants and animals. If such animals are kept under observation or tracked by the forest rangers, they can be protected from natural disasters such as fires in the forests, floods, and all illegal activities like poaching.

To conserve wild animals, AI-enabled devices, applications, & analysis/monitoring system is used to keep their track records and understand the behavior of animals for right predictions of such models. Let’s find out how AI-enabled applications can be used for conserving animals.

AI in Animal Detection & Counting

Endangered species at the brink of extinction are kept in special conservation. AI-enabled machines like robots or autonomous flying drones can keep an eye on such animals helping the wildlife conservation authorities by keeping their population under observation.

annotation for animal counting

Similarly, computer vision technology in AI-enabled drones can detect the types and species of animals, and then inform researchers about their activities. The machine learning algorithms are developed with a wide-ranging huge quantity of training datasets to equip AI and to recognize the different species of animals.

Also Read: How to Improve Computer Vision in AI Drones Using Image Annotation Services?

Large animals like elephants and whales can be spotted by satellites. Using the set of satellite imagery, researchers can gather data and keep an eye on such animals. Animal detection and their count is important to ensure whether their population is increasing or decreasing in a region.

Detecting Poachers to Save Animals

Intensely killing the animals is another illicit activity which reduces the population of endangered species. Poachers kill animals like elephants for their precious tusks and Rhinoceros for their horns that are sold at very high rates in the International Market. But now, AI can help in controlling such unlawful actions through a human-less monitoring system.

AI-enabled drones and night vision cameras can detect such poachers on the ground and report the forest rangers to take action against them before they kill any animal. Humans with weapons and other unusual activities can be easily spotted by AI-enabled cameras with quick alert systems.

The combination of machines and humans working together with forest rangers can accomplish more of such actions. With intelligent visibility from the sky, there is a great opportunity to safeguard the wild animals. To make the drones detect varied animals, a relevant amount of high-quality training datasets is required for training the Machine Learning algorithms.

Also Read: How Much Training Data is Required for Machine Learning Algorithms?

Identifying the Waste Materials in the Ocean

People enjoy beaches but litter waste material near the banks of an ocean, which is another risk for various underwater species or other that are completely dependent on marine life. But now thanks to AI algorithms, models can easily identify and remove plastics from natural environments before they harm the wildlife.

identifying the waste materials in the ocean

Drones are trained to identify the waste materials floating or drowning in the sea and inform the marine wildlife conservation department to collect and remove such materials. Marine litter mostly contains plastic articles. This has become a universal practice of the tourists and people enjoying their life around the ocean.

Plastic has harmful effects on living beings and carries invasive species posing a risk to biodiversity and ecosystems. Hence, an improved understanding of littering sources, the distribution, and the degradation of plastic in oceans is necessary to reckon the risk related to plastic pollution.

Identifying and classifying the littered plastic waste in the ocean is a challenging task. But using improved AI-enabled cameras equipped with drones, gathering marine litter information has become easier. The AI model is well-trained to recognize the varied types of waste materials littered into the ocean.

Image Annotation for AI in Animal Conservation

Annotation for Animal Counting

Reckoning wild animals is another challenging task, especially when they are living in their natural environment. But thanks to AI, such animals can be easily counted without any human encounter to keep their population under observation.

Cogito provides bounding box annotation service to make such animals identifiable by machines like drones. All types of animals are annotated here with the best level of accuracy for appropriate detection.

Annotation for Animal Detection

Apart from counting, detecting the different types of species of animals is also a part of animal conservation. Here again, image annotation services can make such animals recognizable to machines (drones) and provide information to forest rangers. Cogito uses the right image annotation techniques for animal detection with the highest accuracy.

Also Read: What Are The Applications of Image Annotation in Machine Learning and AI

Annotation for Animal Recognition

Again, semantic segmentation is the image annotation technique that helps to recognize the animals in a single class. AI Drones can recognize such animals captured in a single frame, thereby helping the forest animals’ conservation department to recognize animals. Cogito can produce high-quality training data sets for Machine Learning to train the AI models developed for animal recognition.

Also Read: What is the Importance of Image Annotation in AI And Machine Learning?

Annotation for Species Identification

Identifying the different animal species is another challenging factor for wildlife conservation. But AI can easily detect the different species living on Earth or under water. Cogito provides image annotation to annotate the animals with metadata like animal names or species. Thus, ensuring that a wide range of animal species may be identified with the AI model if trained with the right training data.

Also Read: What are the various Types of Data Sets used in Machine Learning?

Semantic Segmentation Annotation

The animals in a single class need to be more precisely identified. Semantic segmentation image annotation is the best and one of the most appropriate techniques used that helps to identify such animals from a distant location with extra precision. Cogito uses the best tools and techniques to annotate animals in the images with Semantic Segmentation for deep learning AI models developed for animal conservation.

Annotation for Poachers Detection

Animals on the verge of extinction can be protected if illegal killings can be spotted by the wildlife conservation department using the AI-enabled security surveillance installed at suspicious locations. Yes, poachers, even in the dark or night can be detected with AI security cameras.

Cogito provides image annotation for AI cameras, night vision view, and object detection in the dark and at night. Image Annotation with added metadata is used to train the AI model that can detect poachers and help the animal conservation authorities to save the biodiversity of the earth.


If AI can be fully and efficiently deployed into animal conservation it can help in saving the biodiversity of the earth. It is only possible when the AI models are trained with the right machine learning datasets. To develop such a fully functional model, AI companies need high-quality animal detection dataset for Machine Learning training to identify animals and objects with precision.

Also Read: What is Human-in-the-Loop Machine Learning: Why & How HITL Used in AI

Image annotation is the right data labeling process to generate datasets for Computer Vision-based AI models. As much as such data is fed into the algorithms, the model will be able to learn with a varied scenario and detect the different objects thereby, giving accurate predictions when used in real life.

Also Read: How to Create Training Data for Machine Learning?

If you wish to learn more about Cogito’s data annotation services,
please contact our expert.