RADR: Rapid Amber Detection Response wins Rep. Frank Pallone Jr.’s 2024 Congressional App Challenge in New Jersey’s Sixth District

When asked what inspired the creation of RADR: Rapid Amber Detection Response, the students said, “Recently, there has been a noticeable rise in crime in our community. Neighbors’ homes were robbed while they were away on vacation, and it was evidence that methods of investigating these crimes were not always very effective. For instance, a police officer once came to my door asking for our doorbell camera footage hoping to spot a suspect vehicle. He repeatedly did so, asking many in our neighborhood one-by-one. Sadly, no progress was made, and the culprit wasn’t caught. Amber alerts are similar: public broadcasts that depend upon humans to spot and report suspects, or kidnapped children, but there may not always be a human present.

Naturally, we questioned the human-dependency in this entire search process. Why should humans be the only ones to spot suspect vehicles, when cameras can do so down to the pixel? Why should humans have to report sightings when automated systems, especially in the age of Artificial Intelligence can do so through a more streamlined process? These questions begged answers, and we realized that live footage from sources like car dash cams could be used to revolutionize this process. We completely eliminated the human-factor of a search by designing artificially intelligent cameras that can communicate with one another, scouring for the location of a culprit vehicle. Currently, so much footage is simply wasted, whether that be from a doorbell or a dashcam. RADR repurposes these sources of data, so that no officer has to ever knock door-to-door in order to find criminals. With RADR, this end-to-end system to search for criminals is automatic, accurate, and efficient.”