According to Save The Rhino statistics, over 1000 rhinos are killed annually in South Africa. These harrowing poaching statistics display a gloomy future for survival of this beautiful species.
While many attempts have been undertaken over the past ten years to combat the devastating results of poaching, the country has not yet seen a steady decline in numbers year-on-year.
AxxonSoft’s global marketing director, Colleen Glaeser, who is based in South Africa, decided to create a strategical and proactive anti-poaching approach, utilising the tools at her disposal, assisting a country in dire need of assistance.
While deep learning, using artificial intelligence (AI) and neural network analytics in its algorithm, is not new to the security and surveillance industry, Glaeser and the team at AxxonSoft global took the technology a step further, developing and implementing the software to help differentiate between humans and animals.
The implementation of this technology in game reserves and parks across South Africa has been a game-changer in the war against poaching. For two reasons namely; this neural network solution can identify actual poaching threats (distinguishing poachers from their prey) while providing a proactive surveillance solution as opposed to a reactive one.
Predominately utilised for face and license plate recognition, deep learning technology has never been adapted to tell the difference between humans and animals.
Prior to the incorporation of deep learning in anti-poaching surveillance, software often failed control rooms and response units in that false alarms were on many occasions, set off by animals, insects and weather.
Control rooms were not able to tell the difference between an actual threat and a false alarm, which often resulted in exhausting resources as teams were dispatched for animals who had touched the fence while grazing in their natural habitat.
AxxonSoft’s surveillance software, which leverages AI and deep learning technology now alerts the operators in the control room to an immediate poaching threat as poachers try and breach the fence perimeter to enter the reserve or park.
Glaeser comments: “Our deep learning technology has been extremely successful thus far in telling the difference between animals and humans as the neural network algorithm can identify, through certain indicators, whether a human or animal has set off the alarm. If the software detects a human, the operations team is immediately notified and a dispatch team is sent to the scene in question.”
In addition, AxxonSoft’s deep learning technology provides a proactive solution to surveillance whereas previous systems were somewhat archaic and reactive in their response to real threats.
Due to expansive terrain and limited resources, rangers and antipoaching units often get to the scene of the crime too late. With the AxxonSoft technology, as soon as the breach occurs, cameras will identify if the breach has been caused by an animal or human, and the control room is immediately notified as to where the occurrence has taken place in the reserve or park.
The dispatch team is given the necessary information and they head to the site where the occurrence has taken place.
The beauty of deep learning and neural network analysis is in its ability to learn and understand the conditions which lead up to an event, and that ultimately allows us to prepare for threats or potential breaches when the known conditions are met.
“AxxonSoft’s technology has proved very successful in preventing killings as the team is able to get to the scene of the crime quickly. By utilising this technology, we have been able to take a proactive approach, identifying the threat in a real time situation. The AxxonSoft team and I really believe this anti-poaching solution can aid in the war against poaching and drastically bring down the upsetting statistics. I can attest to the fact that we have seen great success in curbing poaching,” concludes Glaeser.