Wildlife Protection Enhanced with AI Technology in Africa

Wildlife poachers can now be located and arrested across the central African forests thanks to state-of-the-art AI listening technology. A network of microphones has been deployed across the rainforests in Gabon, Congo, and Cameroon, to detect gunshots associated with the illegal poaching of elephants and other wildlife.

American scientists, led by Naveen Dhar from the Center for Conservation Bioacoustics at Cornell University, are utilizing AI to differentiate gunshot sounds from the multitude of natural noises in the jungle environment.

The deployment of acoustic sensors enables real-time alerts to gunfire, but the dense rainforest presents challenges as the constant influx of sound data complicates the process. The AI system can distinguish loud bangs from the sounds of birds and insects, but struggles with identifying sounds like branches cracking or trees falling, leading to false positives.

To combat this, Dhar and his team are developing a lightweight gunshot detection neural network that will process signals in real-time to minimize these inaccuracies. The system relies on autonomous recording units, or ARUs, which are power-efficient microphones designed for continuous sound recording.

Each ARU performs real-time detection and communicates with a central hub that handles more complex data processing. The ARUs initially filter audio for potential gunshot sounds, sending these to their microprocessors, where the lightweight detection model resides.

If confirmed as a gunshot, the ARU relays information to the central hub, which then cross-references input from other sensors to confirm the event as a true gunshot or a false positive. Upon validation, the system compiles audio files to pinpoint the gunshot's location, providing rangers on the ground with precise coordinates for immediate intervention against poaching activities.

In the future, Dhar hopes to expand the model to detect various types of firearms and other human activities, such as the use of chainsaws or trucks. This innovative approach aims to create an open-source framework for real-time detection that could be utilized globally.

Dhar is set to present his findings at a joint meeting of the Acoustical Society of America and the Acoustical Society of Japan in Honolulu, Hawaii. This initiative represents a significant step forward in wildlife conservation efforts and illustrates the positive impact of technology in environmental protection.

According to the report, the integration of advanced AI technology into anti-poaching strategies could inspire similar initiatives worldwide, showcasing the importance of innovation in preserving wildlife.