Africa is home to most of the world’s diverse and unique ecosystems. It hosts a rich array of wildlife contributing to the planet’s biodiversity. However, the continent faces numerous challenges, including habitat loss, climate change, and poaching, which threaten the existence of many species.
In the face of these persistent challenges, integrating emerging technologies, such as AI, in wildlife conservation across Africa has yielded positive results. From monitoring endangered species to doing away with poaching activities, AI technologies are valuable tools in protecting the continent’s diverse biodiversity daily. This article will explore real-world use cases of AI in wildlife, highlighting their transformative power in safeguarding Africa’s wildlife.
AI is being applied a lot in monitoring wildlife animals in Africa. Wildlife monitoring is critical since it helps us understand the dynamics of the populations, their seasonal distribution, range, and movement requirements(i). Moreover, wildlife monitoring is also critical since it helps us protect animals from risks such as poachers, pests, and diseases, among others. Protecting our animals from such dangers is vital since it promotes wildlife growth and nourishment.
AI applications in wildlife conservation
AI plays a crucial role in biodiversity conservation through various applications. In species identification, AI-powered image recognition and computer vision technologies are employed to identify species from photographs and videos. This not only aids researchers in their efforts to track and study wildlife populations but also provides valuable insights into the diversity and distribution of species in specific regions.
Furthermore, AI is instrumental in habitat monitoring, where sensors and camera traps utilize computer vision to monitor habitats in real time. This technology collects data on species movement, behavior, and environmental changes, offering conservationists a comprehensive understanding of the ecosystems they strive to protect. Additionally, machine learning algorithms analyze the collected data for population estimation, providing vital information about the sizes and trends of various populations. This knowledge is particularly crucial for assessing the health and status of endangered species, allowing for targeted conservation efforts.
In anti-poaching measures, AI systems detect unusual activities, such as poaching or illegal logging. This capability enables a rapid response and intervention to protect wildlife from immediate threats. Moreover, AI assists in disease monitoring by detecting diseases among wildlife populations. This early detection facilitates timely responses and preventive measures, contributing to ecosystems’ overall health and resilience. Lastly, in planning conservation strategies, AI-driven models predict the impact of human activities on wildlife and suggest mitigation measures. This proactive approach enhances the effectiveness of conservation efforts by addressing potential threats before they escalate.
Real-world AI use cases
Strategic Protection Of Threatened Species (SPOTS)
SPOTS is a team of wildlife conservationists working hard to curb illegal poaching. However, the vast tracts of land to be monitored compared to the limited number of rangers pose a heavy challenge for their monitoring efforts. To deal with this, SPOTS partnered with FruitPunch AI to source a team of skilled AI engineers to develop a poacher detection system and put it onto an autonomous drone.
The progress results show that the team has developed a system that can spot the poachers more accurately, faster, and more automated. Due to its high efficiency, more poachers can be spotted and ceased quickly. The team further shares that they will keep working to protect endangered species, including rhinos since these animals are important to different communities.
SMART (Spatial Monitoring and Reporting Tool)
SMART in Niassa Reserve, Mozambique, is a system used to combat poaching and monitor wildlife populations. The system processes data from camera traps, allowing rangers to identify and track animals, assess population trends, and respond to potential threats in real time. Through the system, authorities can carry out Law enforcement monitoring, Biodiversity monitoring, and intelligent data collection.
Wildbook
Wildbook is a system being used in Kenya for the conservation of Zebras. The system uses AI to examine thousands of photos of zebras. Every zebra has its unique pattern of stripes, just as we humans have distinctive fingerprints. Wildbook’s AI program takes the photos uploaded through social media by safari travelers, researchers, wildlife enthusiasts, and residents (including school children) and identifies each animal. The application of AI in the field has conservation efforts to ensure the survival of this critically endangered species.
PAWS (Protection Assistant for Wildlife Security)
PAWS has been deployed in various protected areas, including Southeast Asia and South Africa, to combat poaching and protect wildlife. In South Africa, the system is heavily used to address the persistent threat against the rhino species. The system uses predictive analytics to analyze historical poaching data, weather patterns, and other variables to identify potential hotspots. This proactive approach has significantly improved the efficiency of anti-poaching efforts, reducing rhino mortality rates.
Rainforest Connection
This AI-powered monitoring system has been instrumental in combating illegal logging. The technology detects chainsaw sounds in real-time and alerts authorities, enabling rapid response to such illegal activities. This has helped preserve the habitat of endangered species and maintain the ecological balance of the rainforest.
In conclusion, these real-world use cases demonstrate that AI is not just a theoretical concept but a practical and transformative force in Africa’s wildlife conservation efforts. From digital identification to predictive analytics, AI technologies are reshaping the conservation landscape, offering hope for the continued protection and thriving of Africa’s unique biodiversity.