From facial recognition technology that monitors brown bear populations to intelligent robots sorting recycling, these initiatives are having a positive impact on the environment

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SwissCognitive, AI, Artificial Intelligence, Bots, CDO, CIO, CI, Cognitive Computing, Deep Learning, IoT, Machine Learning, NLP, Robot, Virtual reality, learning1. Conserving species

The Living Planet Index produced by WWF estimates that wildlife population sizes have dropped by 68 per cent since 1970. The charity advocates the use of artificial intelligence (AI) as a tool of conservation technology to monitor and curb this alarming rate of decline.

One of the most useful applications is in acoustic monitoring, recording the sounds of wildlife ecosystems on weatherproof sensors. Many animals, from birds and bats to mammals and even invertebrates, use sound for communication, navigation and territorial defence, providing reams of rich data on how a species population is doing. AI provides a fast and cost-effective way to analyse hours of recordings for patterns of behaviour.

Conservation Metrics, a California-based company, has used acoustic listening and machine-learning to monitor endangered populations of both red-legged frogs in Santa Cruz, diverting water to help them mate successfully, and the forest elephants of the Central African Republic, helping to protect them from poachers.

Facial recognition technology is another application of AI that could help track wildlife populations, when combined with camera traps in the wild. BearID, an open-source application, which was trained on brown bears in Canada and the United States, is a recent AI triumph as, unlike primates, zebras or giraffes, bears don’t have distinguishing features, so the deep-learning algorithm had to find patterns in their facial make-up instead. The researchers hope this AI will be used to monitor other species in the future.

2. Improving recycling

More than 2.1 billion tonnes of rubbish is generated in the world each year, yet only 16 per cent of it is recycled, according to research by Maplecroft. To make matters worse, a quarter of waste put into the recycling is not actually recyclable at all, hindering the whole process.

Several startups are now looking at how AI and sustainability goals can be combined to make recycling more efficient, even when dealing with mixed materials. Colorado-based AMP Robotics uses an AI-powered robot with optical sensors to quickly identify rubbish as it passes on a conveyor belt. It then sorts it with its robotic arms, using the company’s AMP Neuron AI platform, which can recognise different textures, colours, shapes, sizes and even brand labels.

The AI constantly updates itself and is designed to run 24/7. It has already been rolled out in the United States, Canada and Japan, and will soon be coming to Europe.

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In Bali, Gringgo Tech has designed an image recognition tool to help informal waste collectors identify the different monetary values of various recyclable materials. In a pilot study, it improved recycling rates by 35 per cent. They’re now working with Google to build AI into the platform to help improve how quickly and efficiently the system can categorise waste.

3. Protecting forests

Forests are home to 80 per cent of the world’s terrestrial biodiversity, and they absorb and store a third of current carbon emissions. Halting the loss and degradation of forest ecosystems is essential to meeting the objectives of the Paris Agreement on climate change, according to the International Union for Conservation of Nature.

Rainforest Connection seeks to combat illegal logging using acoustic monitoring in forests on hidden solar-powered smartphones, which have been recycled from consumer use. The charity then uses AI to analyse this sound data in real time. If the AI detects the sounds of chainsaws, logging trucks or gunshots, an alert is sent to rangers. According to Rainforest Connection, research shows that if illegal loggers are interrupted once or twice, they leave and don’t return until the next logging season. […] 

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