This project’s research objective is to generate ideas for how sensing and modeling technologies can be used to estimate the extent of labor trafficking in the agricultural industry of Florida. Advancements in technology have transformed mechanisms used by human traffickers to operate. At the same time, technology provides an unprecedented opportunity for law enforcement to uncover these illicit activities. The primary methodologies presented in this talk are 1) a literature review and 2) cross-sectional survey. First, the literature review investigates two forms of technology to support policing: sensing and modeling. Sensing technologies include the use of drones, satellites, imaging, and other advanced equipment for the observation and detection of an event or activity (Klemas, 2015). Modeling technologies refer to computational and mathematical models (e.g. data analytics, pattern mining, optimization, and simulation) for the recognition and response to an event or activity. Some technologies, including remote sensing, pattern mining of flight datasets, bank records, and cash withdrawals have been used to combat sex trafficking (Watson et al., 2015 and QC et al., 2016) and to maintain border security (Coulter, 2009). Florida ranks 3rd in number of human trafficking reports (Florida Strategic Plan for Human Trafficking). While sex trafficking is a major challenge, labor trafficking, particularly in agriculture and tourism and hospitality industries, are the dominating forms of trafficking within the state of Florida (Florida Strategic Plan for Human Trafficking). The presenters will share preliminary mixed-method results from a cross-sectional stakeholder survey on the use of technologies to estimate agricultural labor trafficking. The survey’s objective is to understand the challenges and technological needs of labor-trafficking stakeholders (e.g. police, non-profits, policy-makers, researchers, etc.).
Dr. Michelle Alvarado is an assistant professor in the Department of Industrial and Systems Engineering at the University of Florida. The aim of her research is to develop theory, models, algorithms, and practical tools to improve the operation of complex systems under uncertainty using integrated simulation and optimization methods.
Dr. Mostafa Reisi is an assistant professor in the department of Industrial and Systems Engineering at the University of Florida. His research focuses on analysis of Big data for pattern discovery and information extraction in complex environments for the purpose of systems improvement and decision-making support.
Meserret Karaca is a PhD student in Industrial and Systems Engineering at University of Florida. Her research focuses on pattern mining and machine learning applications in healthcare systems.