DHS posts crowd analysis tech RFI
On August 20, the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) released a request for information (RFI) on technology solutions that analyze crowds and their size. The technologies will be considered for inclusion in a market survey conducted by S&T’s National Urban Security Technology Laboratory (NUSTL) for law enforcement and emergency response agencies. Interested industry partners have until 5:00 p.m. Eastern on September 17 to submit their products.
These systems improve the situational awareness of first responders in order to enhance their ability to manage large crowds during planned and unplanned events. “When it comes to events with large gatherings of people, responders may need to rely on anecdotal information pertaining to the crowd’s size and movement,” said NUSTL engineer Tyler Mackanin. “Utilizing real-time crowd analysis technology could allow for more accurate and efficient response operations to ensure the safety of everyone involved.”
The benefits of crowd count and analysis technology may begin before and continue long after a large gathering. The information these systems provide can help prevent delayed, inadequate or misplaced responses to crowds, as well as enhanced awareness on the scene. These tools also gather data that allow more effective planning for future events.
The market survey report—produced by NUSTL’s System Assessment and Validation for Emergency Responders (SAVER) program—will be posted to the SAVER Document Library on the S&T website, where the findings can be accessed by federal, state, local, tribal, and territorial response agencies making procurement decisions about this type of technology. The solutions of interest should perform crowd count and analysis, including video analysis, and other technologies. They should also provide for post-event analysis. Software and hardware tools should be commercial-off-the-shelf products that are available to the first responder community. NUSTL is seeking technology solutions that don’t rely on facial recognition capabilities.