In our rapidly changing world, massive amounts of information are being stored every second around the world. This data keeps a record of human behavior, events, conditions, and other factors that can inform law enforcement agencies and predict future behaviors with more accuracy than a human analysis.
However, with such massive amounts of data, it becomes much more difficult to comb through it. Big data is large in size, yet it grows exponentially over time. Because this data can be so large and complex, traditional data management tools are often unable to process it efficiently. Law enforcement agencies and other stakeholders can employ AI and other methods to reveal the secrets behind this big data.
Combating High Crime Rates in the US
Crime rates in the United States are higher than rates in many other industrialized countries. According to the Federal Bureau of Investigation, annual crime statistics for 2019 include:
- There were approximately 1.2 million violent crimes
- There were nearly 7 million property crimes
- Victims of property crimes suffered lost about $15.8 billion
- Law enforcement agencies around the country collectively made 10.1 million arrests
- The arrest rate for violent crime was 156.3 per 100,000 inhabitants
- The arrest rate for property crime was 343.3 per 100,000 inhabitants
- The arrest rate or murder and nonnegligent manslaughter was 3.4 per 100,000 inhabitants
- The arrest rate for rape was 7.4 per 100,000 inhabitants
- The arrest rate for robbery was 24.7 per 100,000 inhabitants
- The arrest rate for aggravated assault was 120.8 per 100,000 inhabitants
Despite these high numbers, it is believed that the number of crimes is actually quite higher. According to the Pew Research Center, only 40.9% of violent crimes and 32.5% of household property crimes were reported to the police in 2019.
These statistics demonstrate the importance of law enforcement being able to combat – and even prevent – crime.
How Police Can Analyze Crime Patterns and Trends Through IoT and Big Data
The Internet of Things refers to non-standard computing devices that connect wirelessly to a shared network. All devices connected to the network can transmit data. Smartphones, tablets, watches, and even appliances can be part of this network and interact with others. Anything connect can potentially be monitored and controlled.
The IoT creates the opportunity for law enforcement agencies to analyze patterns and trends that are collected through these various devices. Some examples of how the IoT and big data can capture data to help inform these trends include:
- Review of surveillance camera footage for the commission of crimes and to identify criminals
- Track crime patterns and trends across various geographic areas, communities, and demographics
- Provide opportunities to notice and report crimes through mobile apps
- Monitor communications on connected devices regarding the planning of crimes
- Review communication on social media platforms
- Create a mechanism to track criminal activity and the events leading up to it
- Apply predictive analytics and machine learning to big data
Using Public Records in Crime Prevention
Law enforcement and individual citizens alike can use public records to help prevent crime. Public records include information about a person or community’s:
- Arrest rates
- Demographic data
- Socioeconomic levels
- Property ownership rates
- Court records
By being aware of areas where crime is more prevalent, police can increase their presence and communities can launch their own initiatives to prevent crime.
How Police Are Using IT Worldwide to Predict Crimes
With the advent of crime-solving and new technologies, police forces throughout the world are getting more accurate about predicting crimes.
Efficient law enforcement agencies are able to apply predictive analytics and machine learning that teaches a computer the types of behaviors and data points that often arise before a crime is committed. This helps the system to more easily forecast when and where a crime is more likely to occur. Often, these systems rely on a combination of information, including information from public records like previous arrests with real-time data from the IoT.
Police forces may rely on a variety of different data points to help predict the commission of crimes, such as crime incident rates, arrests, and even weather data. Identifying factors that affect crime can help law enforcement agencies better predict when crime will occur. Other predictive tools take data sets from mugshots, location data, arrest records, and known gang affiliations into a dashboard that allows law enforcement to view and share the information while on the job.
Geographic prediction tools can further isolate specific locations that are predicted to have higher or more serious risks of crime commissions. Geographic factors can also be a data point that these systems consider, such as which areas are close to a major roadway for criminals to make a quick getaway.
Some police forces across the globe have incorporated big data to create predictive crime mapping. This technology create hotspots based on historical data regarding crime type, date, time, and location. The U.K. has adopted these crime-solving and new technologies more quickly than the U.S. since it has accumulated big data for more time but had not previously found a meaningful way to use the data. These maps are estimated to be 10-25% more accurate in predicting crime than the police.
Additionally, some predictive software has allowed some cities to reduce their instances of property crimes. The software uses analyzes various statistics to recommend actions to prevent crime.
How to Prevent Crime from Happening
Even better than being able to catch criminals is to prevent crime from happening in the first place. Some effective crime prevention methods include:
- Increase police presence – People are less likely to commit crimes if they see noticeable police vehicles in the area who are regularly patrolling.
- Educate – People can advocate for themselves by understanding common risk factors associated with the commission of crimes.
- Deter – Locking doors, installing alarm systems, and alerting criminals to their presence can help deter crime to your property.
- Be conscious of your surroundings – People can be taught to take notice of their surroundings and avoid target-rich environments like dark alleys,
- Increase privacy – With the IoT, you may be more connected to the outside world than ever before. However, constant updates, location tags, and other tracking metrics can give criminals inside information about when a crime can successfully be carried out.
- Increase your devices’ privacy settings and avoid posting private information on an online platform.
Conclusion
Big data, public records, and new technologies can continue to be used for new purposes, including making the world a safer place. By embracing these new methods, police forces can gain access to the data they need to better analyze and predict crime patterns. However, it should be mentioned that with big data comes big responsibility. Collecting and storing big data could attract hackers and scammers from all over the world, so we should be careful of data breaches, especially now that it is on exponential rise.