Early Makers Explorations

Project carriers:joint initiative of the IUCN CEESP/SSC Sustainable Use and Livelihoods Specialist Group (SULi) and the International Institute for Environment and Development (IIED) with support from TRAFFIC, the wildlife trade monitoring network.
Beneficiaries:Wildlife
Users: community representatives
Need:build awareness and knowledge-sharing about community approaches to reducing IWT.
Principle:Supporting and engaging communities as the first line of defence
Main technologies involved: online learning plateform
Sources: https://www.peoplenotpoaching.org/

Project carriers:World Wildlife Fund & Google.org
Beneficiaries:Wildlife
Users: Conservationists, technologists, engineers, data scientists, entrepreneurs and change makers
Need:Resolve some of the biggest conservation challenges facing our planet
Principle:Sharing information, ideas, tools and resources to discover and implement technology-enabled solutions
Main technologies involved: plateform
Sources:https://www.worldwildlife.org/projects/wildlabs-net-connectivity-and-collaboration-to-save-the-planet

Project carriers: WWF, TRAFFIC, and IFAW & the world’s biggest e-commerce, technology, and social media companies
Beneficiaries:Wildlife
Users: the world’s biggest e-commerce, technology, and social media companies, cyberspotter volunteers
Need:shut down online marketplaces for wildlife traffickers
Principle:share key search words to enhance AI, block or remove posts for illegal wildlife, train voluntary cyberspotter to report suspicious wildlife listings, raise public's awareness on social media
Main technologies involved: AI and plateform
Sources:https://www.endwildlifetraffickingonline.org/

Project carriers:Microsoft,AI for Good research project
Beneficiaries:Wildlife, animal ecosystem
Users: enforcement agencies and officials at airport
Need:To detect illegal wildlife trafficking facing our planet
Principle:Identifying ivory items such as tusks and horns at airports;Identify animals or products such as bears, polar bears, leopards, lions, and illegal products used in medicines.
Main technologies involved:Azure-based technology,AI, machine learning.Developers have trained Project SEEKER by uploading images of animal parts and manually labelling them, so the AI model can spot them automatically in the future
Sources:https://news.microsoft.com/en-gb/2021/11/18/first-of-its-kind-multispecies-ai-model-to-detect-illegal-wildlife-trafficking-is-ready-to-roll-out-to-airports/

Carriers and actors of the project: joint initiative of the IUCN CEESP/SSC Sustainable Use and Livelihoods Specialist Group (SULi) and the International Institute for Environment and Development (IIED) with support from TRAFFIC, the wildlife trade monitoring network.
Research question:How to tackle animal trafficking based on the ressources and tools owned by each different community?
The reason I selected this project: We should raise social awareness and share knowledge within communities, to fight against animal trafficking.

General principle: Training through webinars, share training materials on the website with the community.
Technical overview - AI version: Based on supervised learning, the animals and the poachers' images(pattern identification and labelling them) could be identified through camera, and the real time alert could be sent to the local community even before the intruders arrive.
Added value thanks to AI: alert the local community of the poachers in real time

A. Exploratory research