Missing person cases have been on the rise in the United States for the past twenty years. Currently, approximately 4,000 people go missing every day. Of those 4,000 cases, over 500 missing person cases go unsolved per day. Furthermore, many of these missing person cases are associated with human trafficking. By utilizing software tools, resources can be maximized as searching for missing persons becomes more efficient. Artificial intelligence concepts, such as geospatial abduction problem (GAP), can enable better and more efficient searches for missing persons. However, current technologies and approaches must be modified to maximize the impact for applications related to missing persons.
Researchers at Arizona State University have recently introduced the Missing Person Intelligence Synthesis Toolkit (MIST), which leverages a data-driven variant of the geospatial abduction problem (GAP). MIST aggregates various pieces of information to identify geographic areas in which the missing person is likely to be located. Then, MIST assigns a probability for each geographic location of interest – thereby allowing the prioritization of search teams. This approach has been tested with real-world data, and found it reduced the search areas of 24 cases by 31 square miles. This technology is also a vital step toward an all-encompassing methodology for locating missing persons who are victims of human trafficking.
Potential Applications
Benefits and Advantages
For more information about the inventor(s) and their research, please see
Dr. Paulo Shakarian's directory webpage