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Case Study Resolve NGO: AI for good.
We worked with Resolve NGO to put their data science capabilities into high gear: deploying over 20 smart camera applications in 6 months across Asia and Africa. By creating AI using only synthetic data, we were able to improve their operational efficiency by 2000%, increase product battery life by 42x, and develop object detection algorithms for animals that are rarely photographed in the wild.
The pain points.
RESOLVE is an international environmental NGO based in Washington DC that has created TrailguardAI, an intelligent camera system aimed at addressing global environmental concerns. The system is specifically designed to monitor endangered species and detect illegal activities, such as poaching and wildlife trafficking, by capturing images of the species and intruders. Wildlife trafficking is a major issue, with an annual value of $175 billion. However, traditional data collection methods are limited by the scarcity of photos and videos of endangered species, making it difficult to develop accurate detection models. The current cameras also require frequent maintenance due to limitations in AI power and battery life. As a result, RESOLVE was struggling to find a solution that would enable their cameras to effectively track endangered species and detect illegal activities. To overcome these challenges, RESOLVE turned to CVEDIA to create a better solution with the goal of preventing false positives and reducing maintenance burdens.
"Now typically we want cameras to last a year, even two years. You don’t want to have to go change the battery every two months, but in fact, that’s what we had to do. So the experiment we just did in South Africa, a typical rate of intruders (at a given trail) is maybe between one to ten transgressions a month. If we do the math, that should be the equivalent of 7 years of use in the field."
Eric Dinerstein
Director of Biodiversity
RESOLVE NGO
RESOLVE NGO
Our solution.
RESOLVE is an international environmental NGO based in Washington DC that has developed TrailguardAI, an intelligent camera system designed to address global environmental issues. Their goal was to create a solution that tracks endangered species in the wild and alerts authorities of poachers and illegal traders. TrailguardAI is an edge device that sits overhead in trees, camouflaged to capture images of species and intruders. Wildlife trafficking is an annual $175 billion illegal industry, and many countries in Asia and Africa are searching for ways to combat it. However, traditional data collection methods are limited by the scarcity of photos and videos of endangered species, making it nearly impossible to create effective detection models. In addition, current cameras require frequent replacement due to AI power restraints. RESOLVE turned to CVEDIA to develop effective algorithms and improve battery life, as they knew that their cameras would send false positives to authorities too often and be a burden to maintain without these improvements.
Resolve NGO achieved a remarkable feat with CVEDIA technology, deploying their first intelligent camera within three weeks of conception. Within a month, they had deployed an intelligent camera running a CVEDIA algorithm in Asia, capturing photos of wild elephants for research purposes in collaboration with geologists, conservationists, and local communities. The NGO plans to deploy their cameras in 200 parks within a year to combat illegal wildlife poaching effectively. This innovative use of technology has allowed them to expand their donor list and fundraise with an active, in-the-field solution. Over 20 AI systems have since been built by CVEDIA for Resolve NGO, including those for endangered species such as snow leopards, rhinos, and tigers. The NGO aims to monitor every square mile of wildlife on the planet with their solutions, effectively eliminating environmental crime. Check out the video to hear Eric Dinerstein, Director of Biodiversity and Wildlife Solutions at Resolve NGO, share his experience with CVEDIA.