How artificial intelligence and analytics helps in crime prevention

How Artificial Intelligence Helps Crime Prevention

According to a study released by FBI, there is an annual increase of 4.1% in violent crimes and 7.4% in motor-vehicle thefts in the United States in 2016. Despite having stringent laws and intense monitoring, the crime rates seem to be only increasing. Therefore, the best approach to prevent crime is a proactive approach rather than post-crime investigation and action. One of the powerful tools that can help the security department with prevention of crimes is Artificial Intelligence (AI) enabled “crime prediction” methodology. It not only saves millions of citizens from violence and crime but also aids in the better utilization of the limited law enforcement resources.

What makes crimes predictable?

As per a study conducted by the University of California, it is observed that crime in any area follows the same pattern as that of earthquake aftershocks. It is difficult to predict an earthquake but once it happens, the aftershocks that follow are quite easy to predict using patterns and past data. Same can be applied for crimes happening in a particular geography.

Experts believe that a criminal tends to use a method, time and location that has proven successful to them over time. They tend to be in their comfort zone and operate under similar conditions again and again due to their prior experience and minimize the risk involved. This makes them predictable.

As per the Chief of the Los Angeles Police Department, “The predictive vision moves law enforcement from focusing on what happened to focus on what will happen and how to effectively deploy resources in front of crime, thereby changing outcomes.

Rule-based engines vs. Machine Learning

With the traditional rule-based engine solutions, rules have to be updated frequently which increases manual intervention and are error-prone. Also, with increasing data, rule engine becomes heavy and maintenance becomes tedious.

Machine Learning (ML) builds intelligence from various sources of data. ML algorithms then try to mimic human intelligence and draw patterns and behaviours from the data without any manual intervention. This intelligence gets upgraded over time as new or additional data is being generated from the sources. As new data is added to the system, the ML algorithm automatically adjusts the parameters to check for possible changes in patterns.

Applying analytics to crime data

In simple terms, crime prediction using analytics and machine learning involves integrating data from disparate sources to analyze them and find patterns and behaviors that are repetitive in nature. This enables the police department to draw conclusions about the crimes committed by seasoned criminals, in various locations, and during different periods of time. A huge amount of data is being used for analysis such as historical data, data from CCTV, social media conversations, weather reports, population data, public events data, economic growth-related data, etc. This data is then analyzed through the right set of mathematical models, predictive analytics technique and machine learning algorithms to identify patterns of crime that otherwise can’t be obtained.

The collected data is pre-processed and analyzed to identify the hidden patterns and derive correlation between crime type and locations. Predictive models are built using machine learning algorithms to predict the future crime occurrences.

How Artificial Intelligence Helps Crime Prevention

Techniques used in AI-enabled crime prediction

It is crucial to identify the type, location and method of crime in order to prevent it. The below matrix would help the security experts to choose the right ML algorithm for the required function. For e.g., Random Forrest is used to analyze/predict the “when” and “where” of the crime. To predict the next possible crime scene, the hot spot analysis would be the most suitable choice.

Artificial Intelligence Helps Crime Prevention

Analytics and ML in crime prediction

Below is a scenario that depicts how an agency can predict crime in advance and alter the outcome. A US city leveraged the benefits of Analytics and ML to reduce burglaries by 30%.

Benefits of using artificial intelligence and machine learning in crime prediction

  • Accuracy of 60-74% can be achieved in predicting category of crime by multi-label classification techniques like Gradient Boosting Machine and Random Forest.

  • Crime prediction accuracy of 65-72% can be achieved by analyzing just 4-5 years of crime data.

  • Including feeds coming from social media, the accuracy of prediction can be increased by up to 15%

By Sarvagya Nayak

Sarvagya is an experienced business manager at Prodapt’s Telebots RPA division with a demonstrated history of building & delivering actionable insights on Analytics, Robotic Process Automation, O/BSS and IoT. His areas of interest are analytics, process improvement, and business model innovation.

Gary Bernstein
Managing Your Internal IT Your company's internal IT team is responsible for keeping things running smoothly, and they deserve all the support you can give them. Here are ten ways to make their lives easier ...
Episode 16: Bigger is not always better: the benefits of working with smaller cloud providers
The benefits of working with smaller cloud providers A conversation with Ryan Pollock, VP Product Marketing and Developer Relationships for Vultr.com - Everyone knows who the big players are in the cloud business. But sometimes, ...
JK Chelladurai
Maintain telecom tax compliance The Telecommunications industry is one of the most heavily taxed service industries. In countries such as the United States, providers have to keep on top of Federal, State, and District taxes, ...
MIT
Smart Manufacturing Startups AI and machine learning's potential to drive greater visibility, control, and insight across shop floors while monitoring machines and processes in real-time continue to attract venture capital. $62 billion is now invested ...
Rakesh Soni
Customer Experience: Living In A Connected World and Winning the IoT Race IoT and smart interconnected systems have already created an invisible aura of convenience, usability, and a rich user experience around us. However, when ...

SECURITY TRAINING

  • Isc2

    ISC2

    (ISC)² provides IT training, certifications, and exams that run online, on your premises, or in classrooms. Self-study resources are available. You can also train groups of 10 or more of your employees. If you want a job in cybersecurity, this is the route to take.

  • App Academy

    App Academy

    Immersive software engineering programs. No experience required. Pay $0 until you're hired. Join an online info session to learn more

  • Cybrary

    Cybrary

    CYBRARY Open source Cyber Security learning. Free for everyone, forever. The world's largest cyber security community. Cybrary provides free IT training and paid IT certificates. Courses for beginners, intermediates, and advanced users are available.

  • Plural Site

    Pluralsite

    Pluralsight provides online courses on popular programming languages and developer tools. Other courses cover fields such as IT security best practices, server infrastructure, and virtualization.