Big Data Applications, How Far Will They Take Us?

– Big Data and Crime Prevention –

You may have already heard from the LG CNS blog site or other press outlets that LG CNS has constructed and are managing a public transportation network system in Bogota, Colombia that has significantly increased the convenience of using mass transit for the citizens of Bogota. The Bogota bus lines were designed using the bus traffic records and boarding and transfer records. The optimization of this mass transit system was made possible through big data.

But big data has the capability to do more than just constructing mass transit systems. The LG CNS mass transit system in Bogota has also contributed to a reduction in crime rate even though it seems that there would be no relation between mass transit and crime rate reduction. Since people in Bogota typically would wait in the street for buses at all times because they did not know the bus schedule, they were more susceptible to being victims of crime. However, since the implementation of the LG CNS mass transit system, people have access to concerning bus stop locations and bus times and there was a decrease in dangerous situations for passengers.

I found this information to be very interesting. These days, big data can not only be used for mass transit systems but it can also be used to made social systems more efficient and even help reduce crime. Let’s take a look at some actual application of how big data is being used to prevent crime (pre-crime).

How Big Data was Used after the Boston Marathon Terror Attack

On April 15, 2013, 2 bombs were set off near the finish line of the Boston Marathon killing 3 people and injuring 260 people. The Boston Marathon has been run every year since 1896. The terror attack on this monumental event in American culture sent a shock across the country. However, the Boston Marathon opened this year with 3,600 participants and a tribute to the victims of the attack last year. But what happened to the perpetrators of the terror attack in 2013? I thought that considering the size of the location of the attack that it would take a long time to capture the suspects but the culprits were detained within 4 days.

Big Data Background

Big data was at the center of the system used to capture the suspects. Big data receiving so much attention by being used during the criminal investigation in this case really shone light on its importance. The Boston Criminal Investigation Bureau was able to collect clues from the large amount of data available immediately after the attack. That data included CCTV footage taken from cameras in the streets and buildings, SNS messages sent by people on the scene and videos and pictures taken by people on site. There was 10TB of data all-together. In order to analyze all of this data, the data was organized through the assignment of identification codes. Using this process allowed the authorities to capture the culprits. Through this data, the authorities were able to quickly get a description of the suspects. It is safe to say that using big data in an investigation has revolutionized the investigation process when compared to traditional investigatory methods.

Big Data ‘Geographic Profiling System’

There are lively discussions taking place in Korea and other countries about how to implement systems to improve security in ways similar to the way big data was used during the Boston Marathon terror attacks. This January, the Korean National Security Council reported on big data and made large increases to the budget for the implementation of big data. As a result of these efforts there are now 38 big data related companies with a combined budget of over USD 55M.

Big data companies are instrumental in the implementation of geological profiling systems in pre-crime and investigations. Geographic profiling systems are made up of diverse spatial statistics techniques, police crime investigation data, high-crime area prediction strategies and make it possible to carry out investigations with serial criminal location information. Geographic profiling systems are implemented using big data to protect the lives of citizens and prevent crime with Government 3.0.


A real life example of how geographic profiling can be seen in the image below. First, a map is generated using geographic profiling to assign colors to regions on a map according to the level of crime that occurs in the regions. Regions in red are areas with a high concentration of crime. Geographic profiling is carried out by assigning police patrols to according to the level of crime in a region. Experts anticipate profiling data to have a big effect on CPTED (Crime Prevention Through Environmental Design) as well.


Geographic Profiling Application Process
(Source: Information 3.0 Official Blog

Big Data and CPTED(Crime Prevention Through Environmental Design)

CPTED is a term that is not very familiar to most people. CPTED stands for Crime Prevention Through Environmental Design and is a method of preventing crime using surveillance through architectural design. CPTED is used widely in Europe and North America. CPTED is now being introduced and has started to be recognized in Korea as well.

modern town houses

We can also see the importance of big data when we look into the process of designing a city with CPTED. CPTED is made up of a collection of data that includes the time and location of crimes that occur, the time of crimes that are committed at specific times and locations, road conditions, official closures at specific locations, and other geographic factors. Using this set of data, actions are taken such as installing CCTV at locations where crime frequently occur and limiting the number of times and locations where criminals can congregate.


CPTED: Crime Prevention Through Environmental DesignProcess
(Source: Official Gyeonggido Blog)

In 2013, the Gyeonggido Design Council announced the release of a manual for a public design service to prevent crime through CPTED data. Let’s take a look at the data analysis that goes into this type of design. The potential for crime increases between the hours of 8PM and 4AM in poorly lit streets and areas with isolated houses. Once this type of data is collected, detailed plans can be made for a CPTED system to be put in place. Closed in spaces can then be opened up and CCTV equipment can be installed in dark or narrow streets where crime is likely to occur.

The Gyeonggido Design Council stated that the construction and support of a comprehensive database that reflects the detailed characteristics of each neighborhood in order to install an effective CPTED system would be very expensive.

The first demo CPTED system deployed in Korea was installed in Bucheon, Gyeonggido and resulted in a 20% decrease in the crime rate in that region. Busan, in the South of the Korean peninsula, has also announced plans to implement a CPTED system.

Social Safety Structure and Big Data

Big data has played a big role in crime prevention and criminal investigations in both the Boston Marathon terror attack and in geographic profiling in Korea. Big data is instrumental in this type of social safety structure and is being implemented in countries around the world.


Big Data in Social Safety Systems
(Source: Gyeonggi Development Institute)

Big data cannot be left out of talks concerning these trends and Government 3.0 discussions. Korea’s long-term future development depends on the scientific analysis of big data. Currently, big data is limited to safety, economics and disaster relief. However, as we are seeing in big data applications overseas, planning for further applications such as tax evasion prevention, governance of special interest groups, NGOs and government as well as other social affairs is necessary.

We’ve now taken a brief look at how big data is implemented in improving the sense of social safety. Big data has not suddenly arrived on the scene but the scope of applications for big data is continuing to become more and more diverse. Therefore, there is a need for trained specialists and efforts made to increase the applications of big data.


LG CNS has organized a support program that enables university students interested in IT to write news articles related to the field. This article is one that was written under the program.

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