THANK YOU FOR SUBSCRIBING
Government CIO Outlook | Wednesday, June 23, 2021
By combining IoT with artificial intelligence and machine learning, powerful tools have been developed which help to dramatically improve surveillance footage analysis.
FREMONT, CA: Artificial Intelligence (AI) and the Internet of Things (IoT) are slowly but steadily becoming a capable tool for catching offenders and monitoring illegal activity. It is no longer merely a possible technology to be considered. Many law enforcement agencies throughout the world are preventing crime with the most up-to-date solutions.
Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.
One such approach is 'facial recognition,' which is widely used in industries other than law enforcement to ensure security. In policing, artificial intelligence is a framework that is analyzed using computers. It can also be used to think critically about the final decisions in legal matters. It is the technology that has the most potential in terms of criminal detection in the future.
[vendor_logo_first]Law enforcement agencies are now using artificial intelligence to improve the efficiency of their officers. It is quickly becoming a vital aspect of law enforcement or the police, as it may assist them in various ways.
Artificial intelligence and the internet of things (IoT) continue to change the way people live worldwide. Here are few ways through which technology may help security forces worldwide improve their capabilities and keep people safer.
Connected Cameras
For decades, police forces globally have relied on innovative connected camera systems to monitor high-crime areas, prevent crimes, and trace criminals. As a direct result, crime rates have decreased all around the world. Surveillance has become more dependable, sophisticated, and effective over time.
Many local governments started a project in several countries to reduce violent crime in the city. Zones with the highest criminal exposure were isolated for accomplishing this. The isolation was conducted by evaluating data on crime rates in different city zones and communities.
Machine Learning for footage analysis
Without the tools to properly analyze the footage collected, connected camera systems are useless. Officers would usually spend several hours a day going through numerous hours of footage in pursuit of a specific profile or incident.
In recent years, police departments have begun to use Machine Learning algorithms to filter through video data to boost efficiency and maximize officer time.
Predictive Policing
Forces can now forecast the location of future crimes with a fair degree of accuracy because to Artificial Intelligence and Big Data.
The method relies on historical data for three primary factors: the type of crime, the time it was committed, and the location of the incident. Using this information, the algorithm can forecast the next steps of the gangs and well-known criminals in real-time.
More in News