As per statistics, the population of wild animals living on the earth will drop by two-thirds by the end of 2020. The ignorance about biodiversity is going to cost us dearly. This neglect and ignorance disturb the earth’s biodiversity, and conservation of the planet’s natural biodiversity is crucial for our natural ecosystems. Every animal, small or big, or a small plant or a tiny fungus, is a part of a more extensive system. If they vanish, it will ruin the ecosystem affecting the equilibrium, and, ultimately, collapse the entire system.
Hence, saving the earth’s biodiversity is extremely important to preserve the balance in the ecosystem. We need a robust wildlife monitoring system with suitable resolutions, and fine-scale data usually needs to be available to the authorities. Researchers manually identify the threatened animals from the captures for population studies, and much time is spent manually classifying the findings.
This research has become easy because of advanced-level technologies like Artificial Intelligence (AI) and Machine Learning (ML). An integrated AI & ML-based solution in wildlife protection can help us save biodiversity.
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How can Artificial Intelligence Help Saving Biodiversity?
AI plays a crucial role in wildlife conservation and prevents the extinction of endangered plants and animals. It keeps track of wild animals roaming in their natural environment or conserved into wildlife sanctuaries. With AI-aided tools, forest rangers keep animals under observation by tracking—natural disasters like forest fires in the forest, floods, and poaching.
And to conserve wild animals, AI-enabled devices, applications, and analysis or monitoring system is extremely useful in tracking record and comprehending the behavior of animals for the correct projections.
The Unique features of AI-enabled applications used for animal conservation are as follows:
Detection & Counting Using AI and Machine Learning
Endangered species at the brink of extinction need unique conservation. AI-enabled machines like Machine Learning in Robotics or Drone Image Datasets help monitor such animals, helping the forest department keep their population under observation.
Similarly, AI-enabled drones can locate the species of animals and collect information about their activities. The machine learning algorithms designed with a wide-ranging quantity of training datasets provide AI to identify different species of animals.
Satellites can spot large animals like elephants and whales, and using satellite images; researchers can gather data to monitor the animals. Animal detection and counting are essential to determine if their population is increasing or decreasing.
Catching Poachers to Save Animals
Poaching and killing animals have made some animals endangered species. Poachers kill animals like elephants for their expensive tusks and Rhinoceros for their horns, which are in demand in the international markets. AI can control such illicit activities through a human-less monitoring system.
AI-enabled drones and night vision cameras catch images of such poachers, and forest rangers can take action against and catch them. The AI-enabled cameras can easily spot humans with weapons and other unusual activities and ring alarms with quick alert systems.
Combining the machine with humans in the forest department can perform more actions with a sharp vision from the sky. The drones detect animals using high-quality training datasets for training the machine learning algorithms, thereby equipping the forest personnel to protect animals and plants.
Stopping Dumping of Waste Materials in the Ocean
People enjoy beach sides but litter waste material near the ocean banks. Garbage and plastics are a perpetual threat to the species living or dependent on marine life. But now, AI-aided tools can quickly find and help remove plastics from natural environments before they harm marine life. Drones help to locate waste materials floating or drowning into the sea and inform the marine wildlife conservation department to collect and remove such waste materials. Marine litter mainly has plastic materials that tourists throw around the ocean while enjoying beaches.
Plastic harms the environment and is threatful to species while posing a risk to biodiversity and ecosystems. An improved understanding of littering sources, the distribution, and the dumping of plastic in oceans is crucial to addressing plastic pollution.
Controlling littered plastic waste in the ocean is extremely difficult, and AI-enabled cameras equipped with drones identify, classify, and gather marine litter information. The AI model is well-trained to locate the waste materials littered in the ocean and ring alarms to conservationists.
Use of Annotation for Animal Counting
Reckoning the behavior of wild animals is another tough job, mainly when they live in their natural environment. With AI, we can count these animals without any human intervention.
Cogito furnishes Image Bounding Box Annotation to identify such animals using machines like drones. All types of animals are annotated here with accuracy for the correct detection.
Use of Annotation for Animal Detection
Besides counting, noticing different types or species of animals is also part of animal conservation. Annotate Image Online makes animals identifiable to machines (drones) and provides information to the forest department. Cogito uses the proper image annotation technique for animal detection with the best level of accuracy.
Use of Annotation for Animal Recognition
The image annotation technique uses semantic segmentation that helps to categorize the animals in a single class. AI Drones identify such animals caught in a single frame that allows the forest department to classify animals.
Use of Annotation for Species Identification
Identifying the different animal species is another arduous task for wild animal conversation, and AI can easily detect the species living on the earth or in water. Cogitotech supplies image annotation to organize the animals with an animal name or species metadata, and AI can identify a wide range of animal species.
The animals in the single class need to be more specifically identified. Semantic segmentation image annotation is the best technique to identify such animals from a remote location with extra accuracy. Cogito uses the best software and approaches to annotate the animals. Cogito uses the images with semantic segmentation for deep learning AI models designed for animal conservation.
Use of Annotation for Poachers Detection
We can save animals from extinction if the wildlife conservation department spots and stops illegal killings. Installing AI-enabled security surveillance cameras at suspicious locations can detect poachers, even in the dark or at night.
AI security cameras with night vision detect objects in the dark and at night can help save the earth’s biodiversity.
Summing-up
AI can uniquely help animal conservation and preserve the earth’s biodiversity with suitable machine-learning datasets. To develop such a fully functional model, AI companies require a high-quality Animal Detection Dataset for Machine Learning training to identify animals and objects correctly.
Image annotation is the proper data labeling process to generate datasets for computer vision-based AI models.
All said and done, unless and until humans become sensitive to animals and plants and respect their fellow species on the earth, nothing can stop the degeneration of this planet.
