Artemis is a geospatial software tool that allows users -such as victims of human trafficking, citizen scientists, social justice activists- to locate, discover and label's the 'hot spots of human trafficking" in near-real-time satellite images with the help of deep learning machine vision techniques.
Recent advancements in technology allow A.I to identify hot spots through satellite imagery which provide actionable intelligence in regards to where men and women are being kept against their will.
Tony Schiena recently gave a talk at a United Nations conference on the uses and benefits of ARTEMIS. (press play on video)
ARTEMIS seeks to bridge a number of capability gaps to improve geospatial awareness of the dynamic environment at the tactical level, enhancing situational awareness and improving predictive capabilities. Artemis is a geospatial software tool that allows users, such as victims of human trafficking to locate, discover and label “hot spots of human trafficking” in near-real-time satellite images with the help of deep learning machine vision techniques.
A former slave in Libya can use the application to locate, through an intuitive and easy-to use interface, the detention centre where you they were held hostage. By allowing users to detect patterns of human-trafficking in satellite images, it exposes the covert activities of human traffickers, enabling more effective collaboration between victims and the criminal justice system. It thus provides incident reporting even in remote and unsafe locations. Artemis was born with the aim of turning “victims” into “researchers” by giving them a safe platform to identify patterns of human trafficking activities in satellite images, tapping into the victim’s intimate local knowledge. Marking a fundamental shift in the way we treat “victims” by giving them the means to be part of the solution to end human trafficking. The identification of the militia run detention centres would be a key factor in tackling the slave trade in Libya and ARTEMIS provides the tool to do this.