Application of AI in Crime Detection and Prevention

Application of AI in Crime Detection and Prevention

Companies and cities all over the world are experimenting with using artificial intelligence to reduce and prevent crime and to more quickly respond to crimes in progress. The ideas behind many of these projects are that crimes are relatively predictable; it just requires being able to sort through a massive volume of data to find patterns that are useful to law enforcement. This kind of data analysis was technologically impossible a few decades ago, but the hope is that recent developments in machine learning are up to the task.

Algorithm used: Data Analysis and Machine Learning algorithms.

AI for Crime Detection

Gunfire Detection – ShotSpotter

• ShotSpotter is an intelligent system to detect gun fires.
• It can alert authorities in effectively real-time with information about the type of gunfire and a location that can be as accurate as 10 feet.
• Multiple sensors pick up the sound of a gunshot and their machine learning algorithm triangulates where the shot happened.
• The location where shot takes place appears to be a red-color dot on the map.
• The algorithm works by comparing data such as when each sensor heard the sound, the noise level.
• It provides real-time alerts to law enforcement agencies.
• Algorithm used: Machine Learning algorithms

AI Security Cameras – Hikvision

• Hikvision, a Chinese company, create cameras able to run deep neural networks right on board.
• AI technology is embedded in the camera itself.
• These cameras can better scan for license plates on cars, run facial recognition to search for potential criminals or missing people.
• They automatically detect suspicious anomalies like unattended bags in crowded venues.
• The algorithm used: Vision processing, Deep neural networks 

AI for Crime Prevention

Predicting Future Crime Spots – Predpol

• Predpol is a company using big data and machine learning to try to predict when and where crime will take place.
• Their algorithm is based on the observation that certain crime types tend to cluster in time and space. By using historical data and observing where recent crimes took place, they can predict where future crimes will likely happen. 
• Their system highlights possible hotspots on a map the police should consider patrolling more heavily.
• Algorithm used: Big Data Analysis

Predicting Who Will Commit a Crime – Cloud Walk

• The Cloud Walk Technology is trying to actually predict if an individual will commit a crime before it happens.
• The system will detect if there are any suspicious changes in their behavior or unusual movements. For example, if an individual seems to be walking back and forth in a certain area over and over indicating they might be a pickpocket or casing the area for a future crime.
• It will also track the individual over time.
• Algorithm used: Facial recognition and gait analysis technology