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AI Tracking Systems: A Pioneering Leap Forward in UK Wildlife Conservation


In a groundbreaking partnership between Microsoft and the UK wildlife charity Fera Science, an innovative artificial intelligence system is reshaping the landscape of wildlife conservation in the United Kingdom. Heralded as the "biggest leap forward in a century" by scientists, this AI-tracking technology is playing a pivotal role in safeguarding endangered British species. In this comprehensive exploration, we delve into the challenges faced by conservationists, the development of this pioneering AI system, and its transformative impact on wildlife monitoring and conservation efforts across the UK.


The Challenge of Monitoring Elusive Species:


Conservationists have long grappled with the complexities of tracking rare and elusive animal species across vast natural habitats. Traditional manual survey methods have proven to be time-consuming, expensive, and limited in scope. Tags and collars equipped with GPS and radio transmitters offer a way to track individual animals, but they fall short when it comes to monitoring entire populations. Even remote camera traps, while useful, can miss infrequent species and generate an overwhelming volume of images for analysts to sift through.


This predicament has significantly hindered efforts to study at-risk native wildlife such as Scottish wildcats, red squirrels, mountain hares, and water voles. The remote habitats, nocturnal behaviours, and scarcity of these species make it nearly impossible to monitor population trends over time consistently. Without accurate data, conservationists struggle to identify threats, measure progress, or tailor interventions to save these vulnerable British species. Enter AI tracking technology, offering a solution to these persistent challenges.


The Pioneering AI System:

In response to the monitoring challenges faced by conservationists, scientists at Microsoft joined forces with the UK wildlife charity Fera Science to develop a revolutionary AI system. This system integrates motion-sensor cameras with an advanced AI image analysis platform. Placed strategically across habitats of target species, these cameras capture animal movements. Rather than storing full images, the motion sensors transmit only pixel change data to the cloud.


The AI platform filters out noise and irrelevant motion, identifies potential animal activity, and compares these pixel changes against encoded outlines of various species. Upon a match, the AI system flags the event for expert review, enabling reliable species detection and monitoring without the need to store or review vast numbers of images. After successful field testing in 2020, the technology has been deployed at over 500 sites across the UK.


Transforming Wildlife Tracking Capabilities:

This AI tracking program generates substantial data on population sizes, behaviours, movements, and trends across both time and geography. The analysis of this wealth of intelligence provides conservationists with capabilities that were previously unimaginable. The system detects even the most rare and elusive species, surpassing the limitations of traditional methods. Machine learning algorithms continually enhance detection accuracy for different animals under varying conditions.


The implementation of remote monitoring significantly reduces costs and fieldwork compared to manual surveys. By covering more habitats, AI tracking identifies previously unknown populations and offers geospatial data to focus conservation efforts effectively. The technology enables earlier intervention against declining species by detecting negative trends. In essence, AI tracking delivers a powerful new tool in the fight to preserve Britain's threatened wildlife.


Saving the Scottish Wildcat from Extinction:


One notable success story of this AI tracking technology lies in its contribution to collecting vital data on Scottish wildcats, the rarest and most threatened mammal in Britain. With estimates suggesting as few as 35 individuals remaining in the wild, the Scottish wildcat faces extinction due to habitat loss, interbreeding with domestic cats, and disease. However, their nocturnal and solitary forest-dwelling lifestyle makes them almost impossible to monitor through direct observation.


By deploying motion-activated cameras across remote Highland glens, the AI system captures and processes enough data to reliably track this elusive species. The tracking insights verify wildcat behaviours, identify critical habitats and location ranges, and reveal population trends in greater detail than ever before. This intelligence will enable conservationists to reverse the wildcat's decline through tailored interventions, such as protecting habitat corridors, building road underpasses, and implementing breeding programs.


Optimising Red Squirrel Conservation:

Another native species benefiting from AI tracking is the red squirrel, which is threatened by habitat loss and competition with invasive grey squirrels. Red squirrels are challenging to distinguish from grey squirrels in camera trap images, limiting conservation data. However, the AI system's sophisticated image recognition algorithms reliably differentiate between the two species. This allows for large-scale monitoring of red squirrel populations, providing early warnings of declines that require swift conservation action.


Additionally, the tracking identifies areas where the two species overlap, leading to the local extinction of red squirrels. Armed with this intelligence, conservationists can focus on grey squirrel control efforts in these regions to protect vulnerable red squirrel populations. The AI program is playing a pivotal role in preventing the disappearance of red squirrels in the UK.


What Does The Future Hold?

Conservationists are just beginning to tap into the vast potential of AI to revolutionise wildlife monitoring and protection in Britain. Looking ahead, the integration of tracking data with other sources such as GPS collar readings, genetic sampling, and drone imagery promises an unprecedented understanding of at-risk species. The expansion of the AI system to improve detection for a broader range of wildlife, including birds and insects, will reveal hidden population trends.


Scientists envision machine learning algorithms that dynamically optimize camera trap locations and analyze monitoring gaps. AI could even identify poaching activities threatening endangered animals. More ambitiously, algorithms may one day reconstruct 3D animal movements and behaviours from motion sensor data. The future of AI-powered conservation appears bright for preserving Britain's natural heritage.


Transforming Wildlife Conservation with AI:


This groundbreaking AI system developed by Microsoft and Fera Science signifies a new era in British wildlife conservation. Motion-detecting remote cameras and machine-learning image analysis unlocks robust, widescale monitoring of even the rarest and most elusive species. The resulting intelligence empowers conservationists to make informed interventions that can reverse species declines and prevent extinctions. What once seemed impossible is now achievable thanks to artificial intelligence.


With the ongoing conservation work happening across the globe and the efforts of the volunteers at SAVSIM, we are excited to see how far the use of AI will go and the exciting change that it is likely to bring.

To find out more about our mission and how you can help, please visit us on our website www.savsim.org or follow us on Instagram @savsim_official.


On behalf of the animals, we protect and the veterans we support.

Thanks


Joe

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