INTRODUCTION
Analytics For Crime Prevention: Artificial intelligence and the Internet of Things has brought a change already in the way agencies operate. Smart devices, virtual meeting tools, cloud, newer tracking tools arm agencies with real-time insights to anticipate threats, helps make faster and better decisions, and also coordinate responses.
Research has persuaded leading criminologists to believe that certain types of proactive policing, such as aspects of hot spots policing, can curb crime, especially in targeted areas. Manchester Police Department powered their digital investigations with IBM, to become proactive with predictive policing. This led to a 28% reduction in crime rate even in the midst of reduced personnel and while facing an acute opioid epidemic.
Prime Minister Narendra Modi at the launch of the book ‘Bridgital India’ said the debate should not be on the dangers of artificial intelligence or robots outsmarting humans, it “should be on how to create a bridge between artificial intelligence and human intentions.”
Technology is surely a bridge and not a divider. “Technology builds bridge between aspirations and achievement, demand and delivery, government and governance,” thus embracing technology is meant to serve more efficiently.
There are priorities involved as is seen by extreme vetting of security in China accused of building a digital dictatorship meant to exert control over the 1.4 billion population. Facial recognition and an intricate network of identification rules there. With gait analysis, though more complex than other biometrics, computationally, people can be identified from far, even with their back turned or face covered as it analyses all the features of an entire body. There has been research on gait recognition in Japan, UK and U.S. for over a decade. Police on the streets of Beijing and Shanghai, use it as a new surveillance tool. The push across China to use artificial intelligence and data-driven surveillance is raising concerns on the real reach of the silhouette movement of technology!
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Analytics For Crime Prevention
People are recognised by the way they walk, using footage from surveillance cameras to analyse gait. The technology isn’t new, nor is the logic and background behind it. We have been living in a world under constant surveillance and the big advantage is safety. Countries like the U.S. are making the most of surveillance information to analyze crime patterns and trends, even predicting crime. And why not?
To be a Future-Ready City smart policing is smart security. When every second matters, we know making smarter and more holistic decisions will make Delhi or any other city a better and safer place to be. The technology also needs to be flexible enough to adapt to new ways people commit crimes and report information to the police.
Coming back to the other technology available, the range of Mapping and Analysis tools as part of the U.S. National Institute of Justice (NIJ) Funded Software Tools, Apps and Databases is representative of the tools for police departments to make geographic forecasts of crime risk.
There is a noteworthy ‘precrime’ initiative, led by the Chicago Police Department and Chicago University Urban Labs. It is based on applying machine learning and predictive analytics to police data sets combined with real-time IoT data. It enables pinpointing problem locations and understand the conditions which make crime flourish. Besides Chicago IBM is working with the police department of other cities to combat crime ahead of time. There is reported reduction in robberies, burglaries, and theft from vehicles, based on recommendations for preventive action from statistical analysis. These common crimes get predicted due to large amount of historical data, infrastructure data and even weather data. And that’s the way to go, towards serious crime predictions ultimately. The new systems and dashboards can accommodate that, when the time comes.
HunchLab a web-based proactive patrol management system illustrates predictive policing very well. It is a geographic prediction tool using data modeling to predict risk in the city’s specific locations. The ‘when and where at-risk areas and time is highlighted on-screen, while recommendations for action too like deploying a high visibility patrol car to control the situation and also deter criminals get displayed alongside. This ‘decision support system empowers each police officer on the beat. It also helps keep the policemen and first responders safer by providing alerts for potentially dangerous situations. Problem-Oriented Policing is an analytics method used by law enforcement to develop strategies that prevent and reduce crime by targeting underlying conditions that lead to recurring crime.
Today crimes have taken a unique dimension with the open street crimes being just one side of the coin. On the other side are those that are now being predicted by the tone, the sentiment – harder to anticipate. There are tools to measure and predict social media outcomes too.
Differentiating between the dangerous, and just unpleasant is important for many governments too, thus they take resort to technology to help make the distinction. IBM® Watson Analytics™ and their veteran analysts sift through huge amounts of data and instantly identify potentially dangerous threats within minutes. Monitoring huge Social Media data and narrowing down to real threats, helps Tactical Institute analyze social sentiment and evaluate whether a person really has the criminal intent, or means and the opportunity to carry out a particular threat bragged in the tweets, posts and messages. Harnessing the power of cognitive analysis has deterred intended crimes in many schools.
Oliver Oetterer, Chief Operating Officer of Tactical Institute says “There’s a military term that many of our veterans like to use: Watson Analytics is a force multiplier, a tool that gives each of us the ability to work many times more effectively and productively. With our old methodology, we might find the top 1,000 threats; with Watson Analytics, we’re thinking it will be more like the top 1,000,000. And in this business, the bigger the haystack, the more needles we are likely to find for our customers.”
Several police-led technology ruled initiatives for analysing both open and social media trends, have showed excellent results. Particularly in larger cities, law enforcement is leveraging powerful computer-based algorithms that analyze big data to isolate crime breeding grounds. Algorithms inform law enforcement strategies by sorting and analyzing sometimes massive amounts of crime data to identify the highest risk places and individuals. Predictions of crime rate helps ensure that police has the resources in place to prevent it.
