The crime rate is spiking by leaps and bounds across the globe. Be it the Syria war or the massive ISIS terrorist attacks, the crime world is frequently flourishing.
Let’s glance over the terrorist attacks in Australia. This continent is an evidence of five terrorist attacks since 2014. The Australian Institution of Criminology has some valid figures in support of the crime statistics. It shows the cases of 31 percent of homicides, 11 percent of kidnapping & abduction and 22 percent of robberies in 2016. In all, 15.9 percent cases involved firearms. Why is big data policing required for the law enforcement agencies? The aforesaid figures have a substantial reason to incline towards the big data policing. All those crime stats have the inclusion of the weapon. It doesn’t matter whether or not that arm is a knife or the gun. The bone of contention is the usage of the arm. Evoke the scenario wherein a domestic violence ended in a death. It’s no big deal if you would find that the shot person would be a policeman. A Queensland Officer Brett Forte (37) was shot dead by the 40-year old Maddison. The police officer ambushed the offender. Its counter-effect swiftly appeared in the massacre of the officer. The offender took out a military-styled weapon to counterattack the police. A study of police deaths in this continent sifted through the crime records for the period of 1981 and 2007. The gist unearthed the fact that the 22 out of 35 killings involved a gun. Isn’t it a reason to seriously sleep on this matter (for sure, it is)? Now, it’s the time to go back to the drawing board to hamper the scrolling up of the crime rate. The big data policing acts as a big data tool to control offences. Big Data Policing is a Handy Tools for Law Enforcement Agencies: 1. Policing Software: It is an online program to identify the crime and criminals. Thereby, social harmony, peace and prosperity can be achieved. The law enforcement agencies employ data-matching technologies to tap any suspicious activity before the crime reaches the height. Enticed with the Internet-of-Things (IoTs), the surveillance cameras monitor and drill out real-time data. This is how the big-data policing of the Los Angeles Police Department’s Real-Time Analysis Critical Response Division (RACR) controls the crime rate. Thanks to Palantir-a social network software! It bedecked the American police with the proactive control. 2. Out-and-Out Filtration: How is it if the sergeant gets an easy access of the criminals’ profile as well the social profiles of the suspects? The law enforcement officers require clutching the offender with evidences. The enforcement officer needs to input the first name and the description in the software. Palantir’s software system blurs the thin line between the suspect and the criminal. On the basis of age, description, address, tattoos, gangs’ affiliation and vehicle ownership, the real culprit is detained. The matched profiles narrow down the searches to just a few. Thereby, the police win the battle. 3. Identification signs: The surveillance software would require no sweat to spotlight the suspects. Then, the automated technology comes in the role, for example, the automated Licence Plate Reader. Let’s consider a bank robbery. The robbers ran away in a vehicle. The foretold reader technology, that does managed IT services of capturing the surrounding happenings, would be extracted later. The law enforcement authority would scour the entire city for tapping the location of the vehicle. 4. Tracking-Specific Technology: This kind of policing is rocking just because of its outstanding tracking features. The digital maps alert the patrol officer with the crime forecasts every day. Meanwhile, the powerful software crunches the accumulated crime data sets to feed its algorithm. On that basis, the crime alert forecasts are launched with specific locations. This is what the predictive policing analysis cites. The IoT connected surveillance cameras avail the evidence. If the crime involves a vehicle, the Licence Plate Reader is hired. It runs on the technology called the automatic number plate recognition. The managed IT service-oriented technology captures and configures it with the driver. Likewise, there are facial recognition software, data matching technologies and many more monitoring tools that can be gelled up to keep the crime under a watch. 5. Narrow Down Public Records for Data to Arrest: The data- driven predictive technology pitches and predicts the risk of future. It’s the root cause of all evils. Therefore, the big-data policing technology hits at the risk to determine its pan architecture. With the prescriptive analysis, uprooting the risk of riots, offence, murders, extortions and many more anti-social crimes is a piece of the meal. The comprehensive charts, graphs and maps enable the analysis. Later on, the decision ends in the arrest of the culprit. The data policing is in a nascent phase. Its future would be pretty refined & comprehensively segregated structure of crime data, personal data, gang data, associational data, location data, environmental data, IoT data, telecom data and fusion center’s data. Subsequently, machine learning-based algorithm figures out similar patterns that point towards the crime or its propensity. These all would become a source to perform a wholesome research about the crime, location and suspects. However, having a full-fledge software to root out the crime are yet to come out. It’s just a phase of infancy. The work is under process. In the meantime, whatever sources and analysis tools are prevalent they, to a certain extent, capable of tracing the crime and criminal. For drawing the criminal psychology, the technology is under-construction. No sooner it would be developed, the crime would reach to its extinction.
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