article / 14 November 2016

5 Smart Technologies That Will Crack Down On Wildlife Trafficking

Technology by itself will not save pangolins or elephants, but it can help make major progress.

An electronic nose to sniff out contraband sea turtles and sharks. Sensor systems to track animal poachers in remote places. Machine learning to find trafficked wildlife in online marketplaces. These are just 3 of the 300 ideas submitted to this year's Wildlife Crime Tech Challenge, a global innovation contest organized by USAID, the National Geographic Society, the Smithsonian Institution, and Traffic, a wildlife trade monitoring network.

"We have government policies and laws, but we wanted to focus on technology and try and identify good ideas from anywhere in the world," says Sara Carlson, part of USAID's forestry and biodiversity team.

The ideas cover four areas: detecting transit routes, strengthening forensic evidence, reducing consumer demand, and tackling corruption. In all, 16 entries became winners, receiving $10,000 each, and 4 became grand prize winners, with as much as $500,000 on offer for development (not to mention technical assistance). Below are a few ideas that Carlson picked out for their originality, scalability, or cuteness (they come from the wider short list).

Hotspots for Pangolin Poaching

Pangolins are adorable, head-to-toe scaly, ant-eating creatures that happen to be one of the most trafficked species in the world. In Asia, their skins are used for traditional medicine and their meat is eaten as a "delicacy" (so-called). This project from the University of Washington’s Center for Conservation Biology is creating a reference database to help with DNA analysis. In time, such data could help identify hotspots of illegal trading and aid law enforcement.

An electronic nose

Developed by the University of Technology Sydney Center for Forensic Science in Sydney, this gun-like "electronic nose" picks up "unique odor signatures of different wildlife species to rapidly determine the identity and geographic origin of trafficked samples." Carlson says it could complement or replace sniffer dogs, which are effective but expensive and non-straightforward to train and maintain.

Sensors for remote rangers

The Zoological Society of London has developed a sensor-alert system called Instant Detect. Designed for small teams of rangers in remote protected areas, it consists of camera traps and motion sensors for vehicles and humans who may want to do harm to endangered species. It aims to increase the capacity of rangers who can't be everywhere at once and is equally adaptable for rhino sanctuaries and turtle beaches. Carlson says it also has a deterrent effect and increases transparency.

Citizen scientists for endangered songbirds

Colorful songbirds are part of the culture in Indonesia. A lot of people keep them, and lots of markets sell them. Unfortunately, the trade is leading some species to extinction. So, conservation nonprofit Planet Indonesia is developing an app encouraging concerned users to go to markets and record what they see. "We will use user data to trace supply chains, report illegal shipments, and advocate for stricter protection of species within Indonesia," says the group's submission.

Smart Invoicing

Finally, the New England Aquarium is developing "smart invoice" technology to aid port inspectors. Called Automated Shipment Forensics, it converts paper invoices into digital form, then runs that version through a background server of recorded illegal activity. The aim is to weed out illegal trade that's often laundered with legitimate trade.

"Technology by itself will not solve the problem," says Carlson. "It needs to be embedded in a more comprehensive approach. But hopefully these technologies can accelerate the work that's being done on the ground."

See more here.

About the Author

Ben Schiller is a New York staff writer for Co.Exist. He edited a European management magazine and was a reporter in San Francisco, Prague and Brussels. 

This article first appeared on Co.Exist and was republished with permission. 

The header image is credited to David Brossard and used under a CC BY_SA 2.0 license

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