These sensors capture the soundscape in Nouabalé-Ndoki National Park and adjacent logging areas: chimpanzees, gorillas, forest buffalo, endangered African grey parrots, fruit hitting the ground, blood-sucking insects, chainsaws, engines, human voices, gunshots. But researchers and local land managers who placed them there are listening for one sound in particular — the calls of elusive forest elephants.
Forest elephants are in steep decline; scientists estimate two-thirds of Africa’s population has likely been lost to ivory poaching in recent decades. Africa’s savannah elephants have also declined by 30 percent over a recent seven-year period, primarily because of poaching, according to results released in 2016 from Paul G. Allen’s Great Elephant Census.
But those working to save these species, which are critical to keeping ecosystems in balance and that also draw wildlife tourists, have a powerful new tool at their disposal: artificial intelligence.
Conservation Metrics, a Microsoft AI for Earth grantee based in Santa Cruz, California, uses machine learning to monitor wildlife and evaluate conservation efforts. It is applying its sophisticated algorithms to help the Elephant Listening Project, based at Cornell University’s Lab of Ornithology, distinguish between forest elephant calls and the other sounds in a noisy tropical rainforest. It’s a perfect job for AI — looking for these rare patterns in terabytes of data that would take humans years.
Researchers use the elephant call data to build more accurate and frequent population estimates, track their movements, provide better security and potentially to identify individual animals, which can’t be easily seen from the air.
It is one of many ways biologists, conservation groups and Microsoft data scientists are enlisting artificial intelligence to prevent the illegal killing of elephants across Africa, stop the global trade in their parts and preserve critical habitat. Efforts include using machine learning to detect real-time movement patterns that could alert rangers to poaching and blocking online ads that attempt to sell illegal ivory or elephant parts.
Scientists with the Elephant Listening Project estimate that Africa’s population of forest elephants has dropped from roughly 100,000 animals in 2011 to fewer than 40,000 animals today. But those numbers are largely based on indirect evidence: ivory seizures, signs of poaching and labor-intensive surveys that are too expensive to be done regularly.
The Elephant Listening Project has spent more than three decades researching how elephants use low-frequency rumbling sounds to communicate with one another. More recently, those scientists began to use acoustic sensors at research sites to build population estimates and, ultimately, to track and protect forest elephants across their ranges in Central and West Africa.
If scientists find, for example, that at specific times of year elephants are using clearings in an unprotected logging concession to access scarce minerals or find mates, scientists can work with the loggers to schedule their work to minimize disturbance and reduce conflicts.
But there has been a bottleneck in getting data out of these remote African forests and analyzing information quickly, says Peter Wrege, a senior research associate at Cornell who directs the Elephant Listening Project.
“Right now, when we come out of the field with our data, the managers of these protected areas are asking right away, ‘What have you found? Are there fewer elephants? Is there a crisis we need to address immediately?’ And sometimes it takes me months and months before I can give them an answer,” says Wrege.
Conservation Metrics began collaborating with the Elephant Listening Project in 2017 to help boost that efficiency. Its machine learning algorithms have been able to identify elephant calls more accurately and will hopefully begin to shortcut the need for human review. But the volume of data from the acoustic monitors is taxing the company’s local servers and computational capacity.
Microsoft’s AI for Earth program has given a two-year grant to Conservation Metrics to build a cloud-based workflow in Microsoft Azure for analyzing and processing wildlife metrics. It has also donated Azure computing resources to the Elephant Listening Project to support its data-processing costs for the project. The computational power of Azure will speed processing time dramatically, says Matthew McKown, the CEO of Conservation Metrics. The platform also offers new opportunities for clients to upload and interact with their data directly.
It takes about three weeks for computers to process a few months of sound data from this landscape-scale study, says McKown. Once the Azure migration is complete later this year, that same job may take a single day.
“It’s a huge improvement. We’re really interested in speeding up that loop between having equipment monitoring things out in the field and going through this magic process to convert those signals into information you can send into the field where someone can take action,” says McKown. “Right now, that process can take a really long time.”
‘We’ve only scratched the surface’
Across the continent in East Africa, Jake Wall, a research scientist with Save the Elephants who collaborates with the Mara Elephant Project and other conservation groups, typically has more immediate access to data about the savannah elephants he studies in Kenya and seven other countries. That’s because animals in those populations have been outfitted with GPS tracking collars that transmit location data via satellites and cell networks.
That information is uploaded to the Domain Awareness System (DAS), a real-time data visualization and analysis platform now used in protected areas across Africa. It integrates data from about 15 different sources today, including ranger vehicle and radios, animal trackers, camera traps, drones, weather monitors, field reports, snare locations and satellite imagery. The tool was developed by Paul G. Allen’s Great Elephant Census, another AI for Earth partner that is moving the DAS system and its data onto the Azure cloud, to give managers a real-time dashboard that can inform tactical decisions for interdiction against suspected illegal activity or apparent threats to endangered wildlife.
In some areas, DAS also powers a Save the Elephants tracking app that can alert rangers when an animal has slowed or stopped moving via email or text message. The app can also warn when animals are heading toward human settlements where they might raid a farmer’s crops. Reserve managers or the farmer can then help herd the animals back to safety. From Gabon to Mozambique to the Congo, some 463 animal tracking devices are deployed, of which 358 are on elephants.
In other projects, Microsoft has worked with the Peace Parks Foundation, which combats rhino and other wildlife poaching in South Africa, to create remote sensing systems that can detect and evaluate poaching risks. Microsoft, through a NetHope Azure Showcase grant, is also helping move the open-source SMART (Spatial Monitoring and Reporting Tool) Connect to the Azure cloud. It is used in dozens of conservation sites across Africa to improve the effectiveness of wildlife patrols.
AI for Earth has also provided grants to researchers at the USC Center for AI in Society (CAIS) and Carnegie Mellon University, who have created and are continuing to improve Protection Assistant for Wildlife Security (PAWS). It uses machine learning to create patrol routes based on where poaching activity is most likely to occur. USC CAIS has also created and is continuing to improve the Systematic Poacher Detector, which detects poachers and wildlife in nighttime drone footage, now being used by organizations including Air Shepherd.
Even with advances in radio collar technology, sensors and imagery collection, a lot of additional work is needed to turn that data into scientific insights or actionable intelligence, says Wall.
“I think we’ve only scratched the surface of what’s possible,” says Wall. “We’re really excited because the expertise that Microsoft and AI for Earth can bring to the table includes skillsets that field biologists don’t typically have.”
“Machine learning could be applied to seven or eight immediate things that I would love to know more about, whether it’s recognizing individual elephants or picking up on changes in movement behavior or figuring out what’s happening on a landscape level with human expansion and deforestation,” says Wall.
Wall has been collaborating with Dan Morris, a Microsoft researcher working with AI for Earth, on a half dozen project ideas. One examines how to use machine learning to identify streaking behaviors — when elephants run fast and in an unusually straight line — that can be a sign of poaching or other threats.
Morris has also been working to apply machine learning algorithms to camera traps, which are remote field cameras that are triggered by motion and photograph anything that crosses their path. But finding an animal of interest can be like looking for a needle in a haystack.
“Sometimes no one has time to look through these images and they end up sitting on a grad student’s shelf somewhere,” says Morris. “The potential for machine learning to rapidly accelerate that progress is huge. Right now there is some really solid work being done by computer scientists in this space, and I would guess that we’re less than a year away from having a tool that biologists can actually use.”
Wall and Morris are also beginning to work on using AI to distinguish between elephants and other animals like buffalo or giraffes in aerial photography. Knowing when and where elephants are coming into contact with other wildlife — and particularly domesticated animals like cattle — can help rangers minimize conflicts with humans and help scientists better understand disease vectors.
These insights can also inform land-management decisions, such as where to lobby for protected areas and where to locate human infrastructure like roads and pipelines. That’s one of the most significant yet least understood threats to elephant survival, says Wall. With access to the right imagery data, AI tools could help begin to keep tabs on, and draw useful insights into, human encroachment into their habitat.
“We’re always focused on poaching and these acute problems, but really it’s the expansion of human settlements and the advancements of roads and railways and pipelines that are going to affect African elephant populations going forward,” says Wall.
‘AI is really the key piece’
Saving elephants isn’t just about stopping poachers where they hunt. Disrupting the global marketplace that rewards them economically is equally important.
Microsoft and other tech companies have joined the Global Coalition to End Wildlife Trafficking Online, organized by the World Wildlife Fund (WWF) and partners TRAFFIC and the International Fund for Animal Welfare. After observing that trafficking in wildlife parts like elephant ivory, animal skins and live pets had largely moved from physical marketplaces to the internet, they convened companies from across the online landscape to combine forces to stop it.
Along with targeting the illegal trade in elephant products, the coalition partners target criminal transactions such as the sale of tiger cubs for pets and the trade in pangolin scales and illegal coral.
“Previously cybercriminals were able to operate pretty freely on the internet because there wasn’t much risk,” says Giavanna Grein, a wildlife crime program officer at WWF. “But now we’re creating deterrents and consistency across all the different platforms — if every time a criminal creates a new account and puts up a new post, it’s taken down immediately, that’s going to be really frustrating for that criminal.”
The coalition has since worked with search engines like Bing, e-commerce sites and social media companies to adopt strong and consistent policies about what products are prohibited on their platforms. WWF also provides training to help companies recognize and shut down advertisements and customer accounts that traffic in illegal wildlife.
That involves some mix of human detective work and algorithms that search for keywords associated with wildlife trafficking. In September, Microsoft’s AI for Earth team will host an AI-focused workshop for tech companies and academics working to enhance automation to detect illegal wildlife and their products online. The goal is to advance technologies to identify and root out endangered species posts before anyone has a chance to see and purchase them.
“AI is really the key piece in combating wildlife trafficking online. While it’s not the only solution needed, automating the review of posts containing illegal wildlife and their products would drastically increase the barrier to entry for wildlife cybercriminals,” says Grein.
Opera launches built-in VPN on Android browser
Opera has released a new version of its mobile browser, which features a built-in virtual private network service.
Opera has released a new version of its mobile browser, Opera for Android 51, which features a built-in VPN (virtual private network) service.
A VPN allows users to create a secure connection to a public network, and is particularly useful if users are unsure of the security levels of the public networks that they use often.
The new VPN in Opera for Android 51 is free, unlimited and easy to use. When enabled, it gives users greater control of their online privacy and improves online security, especially when connecting to public Wi-Fi hotspots such as coffee shops, airports and hotels. The VPN will encrypt Internet traffic into and out of their mobile devices, which reduces the risk of malicious third parties collecting sensitive information.
“There are already more than 650 million people using VPN services globally. With Opera, any Android user can now enjoy a free and no-log service that enhances online privacy and improves security,” said Peter Wallman, SVP Opera Browser for Android.
When users enable the VPN included in Opera for Android 51, they create a private and encrypted connection between their mobile device and a remote VPN server, using strong 256-bit encryption algorithms. When enabled, the VPN hides the user’s physical location, making it difficult to track their activities on the internet.
The browser VPN service is also a no-log service, which means that the VPN servers do not log and retain any activity data, all to protect users privacy.
“Users are exposed to so many security risks when they connect to public Wi-Fi hotspots without a VPN,” said Wallman. “Enabling Opera VPN means that users makes it difficult for third parties to steal information, and users can avoid being tracked. Users no longer need to question if or how they can protect their personal information in these situations.”
According to a report by the Global World Index in 2018, the use of VPNs on mobile devices is rising. More than 42 percent of VPN users on mobile devices use VPN on a daily basis, and 35 percent of VPN users on computers use VPN daily.
The report also shows that South African VPN users said that their main reason for using a VPN service is to remain anonymous while they are online.
“Young people in particular are concerned about their online privacy as they increasingly live their lives online,” said Wallman. “Opera for Android 51 makes it easy to benefit from the security and anonymity of VPN , especially for those may not be aware of how to set these up.”
Setting up the Opera VPN is simple. Users just tap on the browser settings, go to VPN and enable the feature according to their preference. They can also select the region of their choice.
The built-in VPN is free, which means that users don’t need to download additional apps on their smartphones or pay additional fees as they would for other private VPN services. With no sign-in process, users don’t need to log in every time they want to use it.
Opera for Android is available for download in Google Play. The rollout of the new version of Opera for Android 51 will be done gradually per region.
Future of the car is here
Three new cars, with vastly different price-tags, reveal the arrival of the future of wheels, writes ARTHUR GOLDSTUCK
Just a few months ago, it was easy to argue that the car of the future was still a long way off, at least in South Africa. But a series of recent car launches have brought the high-tech vehicle to the fore in startling ways.
The Jaguar i-Pace electric vehicle (EV), BMW 330i and the Datsun Go have little in common, aside from representing an almost complete spectrum of car prices on the local market. Their tags start, respectively, at R1.7-million, R650 000 and R150 000.
Such a widely disparate trio of vehicles do not exactly come together to point to the future. Rather, they represent different futures for different segments of the market. But they also reveal what we can expect to become standard in most vehicles produced in the 2020s.
The i-Pace may be out of reach of most South Africans, but it ushers in two advances that will resonate throughout the EV market as it welcomes new and more affordable cars. It is the first electric vehicle in South Africa to beat the bugbear of range anxiety.
Unlike the pioneering “old” Nissan Leaf, which had a range of up to about 150km, and did not lend itself to long distance travel, the i-Pace has a 470km range, bringing it within shouting distance of fuel-powered vehicles. A trip from Johannesburg to Durban, for example, would need just one recharge along the way.
And that brings in the other major advance: the i-Pace is the first EV launched in South Africa together with a rapid public charging network on major routes. It also comes with a home charging kit, which means the end of filling up at petrol stations.
The Jaguar i-Pace dispels one further myth about EVs: that they don’t have much power under the hood. A test drive around Gauteng revealed not only a gutsy engine, but acceleration on a par with anything in its class, and enough horsepower to enhance the safety of almost any overtaking situation.
Specs for the Jaguar i-Pace include:
- All-wheel drive
- Twin motors with a combined 294kW and 696Nm
- 0-100km/h in 4.8s
- 90kWh Lithium-ion battery, delivering up to 470km range
- Eight-year/160 000km battery warranty
- Two-year/34 000km service intervals
Click here to read about BMW’s self-driving technology, and how Datsun makes smart technology affordable.