As a society develops, unfortunately, so does the sophistication of crime. Delinquency is constantly evolving, and delinquents use modern technology to escape the law. In such a scenario, a smart community policing system is essential to reduce crime and bring a sense of safety in residential areas.
A team of scientists at Dongguk University led by Joong-Yeon Lim decided to tackle this problem, and by integrating three main areas of their research, has developed an innovative policing system that they have named "Googi."
Of the research areas, the first focuses on virtual reality used for police training and crime education and involves reconstruction of crime scenes through simulations.
The second investigates how robotic devices can detect and respond to crimes when they happen, boosting surveillance. This technology uses forensic dentistry to identify victims and suspects. The form and pathology of teeth of Korean people, as well as bite marks, all contribute to personal identification.
The third pertains to big data, where offline and online information is analyzed for crime prediction and prevention. Virtual reality data, information provided by citizens, and forensic data gathered by robots are analyzed for crime prediction, with results handed over to local authorities.
Combining these three modes together, the team has built a crime prediction algorithm using information extracted from crime scenes, local communities, and forensics. The researchers are hopeful that this can help the police identify crime hotspots in real time and thus help them prepare for and respond to crimes in vulnerable areas.
"This technology can greatly contribute to the prevention of gender violence, domestic violence, and child abuse," said Lim.
The proposed Googi system encourages citizen participation by gathering their feedback and providing results to the community, while boosting crime prevention education. The ability to detect individuals at crime scenes is also enhanced by using robotic technology to analyze Korean teeth.
"As a result, crimes can be better predicted and responded to, resulting in a safer community environment," said Lin.
After having successfully built a prototype on the local scale, the research team now looks to bring the technology to a global level in 2022.