MapInsights helps police trainees learn the territory

MapInsights helps police trainees learn the territory Sadie Harley Scientific Editor Andrew Zinin Chief Editor In early 2026, the University of Illinois Division of Public Safety was facing a challenge. It had 11 security guards it planned to convert to community service officers, which meant they would change from being based in one building to working a whole beat. "Their jobs completely changed," said Lt. Ty Ledbetter, administrative lieutenant for the division, who also manages the community service officer program and officer training. Public Safety needed a way to get the officers up to speed, and quickly. Its solution was to call associate professor Yun Huang, who ultimately built the MapInsights program. Huang, whose research focuses on human-AI collaboration and interactions, was already at work on interactive mapping software. She started working with Ledbetter and Jennifer Whiting from the university's Police Training Institute in March, and by May had created MapInsights, a web-based training platform that converts the memorization of a large real-world operating environment into structured, measurable practice. For a public safety officer, knowing every building on a beat is essential. However, memorizing more than 1,000 buildings on the University of Illinois campus, which is divided into three beats on roughly a north-to-south basis, can be tedious and time-consuming. Furthermore, the division's test of campus geography, on which trainees must score 80% or higher before moving to the next training module, was a clunky web form that didn't even save progress. In contrast, MapInsights is highly reactive. MapInsights identifies each building by name but also by the number used by the campus Facilities & Services office. All maps are connected to the university's archaeological services, so if a building number changes in the system, it will change on the map. When the assessment begins, all buildings are outlined in red. Each time a user clicks on a building and identifies it correctly, the red changes to green. Progress is savable, and the interface is reactive. The design turns campus geography into a short practice loop: each round shrinks the map to one beat and either buildings or parking lots, shows a highlighted target, and offers a short list of names, then brings back only the misses until the officer can recognize those places with less help. The system design was informed by cognitive psychology research. For example, it incorporates a sense-of-direction assessment framework to help measure the trainee's sense of direction, map reading, distance judgment, route memory, orientation in novel places and mental map formation. With that information, the training can adapt to each user's abilities and tendencies. "This generation," Ledbetter said as he clicked through a practice exam, "this is exactly what they're used to doing." MapInsights has become part of training for both sworn police officers and community officers in Public Safety. With some additional mapping, Ledbetter envisions possible training for campus SafeWalks escorts and even publicly available maps showing the best-lit or most accessible walking routes across campus. "It's really affected the department as a whole," he said, calling Huang's work "phenomenal." Meanwhile, Huang sees other applications of MapInsights. For example, it could allow new students to upload their course schedules, showing them the best and quickest routes to classes—or whether they even have enough time to get from one class to the next based on their schedule. Huang has worked to design technology for public safety since 2010, including SafeRBot, a large language model that helps dispatch centers respond to nonemergency situations. She potentially sees the two applications working together. "We want to turn this research platform into something really practical that people can use," she said. Huang's experience with MapInsights also reflects how AI is reshaping the role of experienced researchers. "It's exciting to be back in the creator's seat," Huang said. "AI allows me to return to hands-on development while doing intense research and advising, combining the technical skills I've built over the years with a much deeper understanding of real-world problems. I can navigate between research and reality smoothly and see immediate impacts." Provided by University of Illinois at Urbana-Champaign