Deep Data Analytics can be a key for Public Safety in India

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Given the complicated evolving landscape in India, the security situation today is more unstable than ever before. Deep data analytics could be a key asset to any agency which deals in public safety and emergency management

By Anand Navani

Given the complicated evolving landscape in India, the security situation today is more unstable than ever. In such conditions, the weapon of choice is deep analytics technology. Public Safety today needs to be revolutionary to fit into the rapidly changing day to day working environment and big data analytics or better known today as deep data analytics is a key asset to any agency that provides emergency management or response.

Apart from external threats that disrupt law and order, public security officers in India also face challenges within the organisations, such as lack of interoperability and trade of information which in turn leads to a weaker response time and fewer positive outcomes. Similarly, dwindling budgets also pose constraints that lead to reduced resource capacity, which in turn cast a shadow on the trust and promise of maintaining highest levels in protecting the community and conserving order.

Law enforcement agencies in India also lack a robust IT infrastructure; implementation of state of the art facilities can help them deal with threats to public security and safety proficiently. The ability to collect and process a huge quantity of data from various sources actually in turn leads to the success of big data projects.

Currently, India has just about 259 million Internet users and over 943 million mobile users. The quantity of digital information accessible to the law enforcement agencies can be overpowering. In the past, finding information was the problem, but now the quandary is filtering and processing huge and disparate data sets so that members of intelligence and law enforcement agencies can fully exploit the information and make it actionable. In fact, the problem is getting worse with the explosive growth of data.

The issue is further exacerbated by need-to-know access to the right data across multiple jurisdictions. In this circumstance deep data is definitely going to find a bigger grip as the government of India embarks on a journey to modernise its IT infrastructure across agencies and jurisdictions.

With the commencement of deep data analysis in today’s competitive world, be it businesses, administration, medicine etc. – They all are gradually accepting the concept of ‘Measurement is managing’. Big data and analytic procedure can help map India’s landscape by interpreting large sets of data from numerous sources and determine composite patterns of associations between society, places and measures.

The result of all this increased information from various sources flowing into Public-safety answering points (PSAPs) is the potential to gather actionable information to better protect people of this country. The solution will be making sense of this “big or deep data” and allocating it to work. Today’s software analytics can single out the related bits of information—in the form of videos, photos, records and more—out of huge quantity of data, without the laborious task of manual searching and culling out core data. With modern deep data analytics competence, PSAPs, homeland security, police and other entities can mine these data sources and gain much greater background when responding to investigate crimes and other occurrence. Intelligence, law enforcement and other public security agencies amass a large amount of data and utilise specialised analysts to make sense of raw intelligence gathered from disparate sources.

They are custodians of an unprecedented volume of raw data acquired from sources including data from internet interception systems, analytics on the civilian movement in transport system, vehicular traffic and on foot, spatial alertness of suspects, and inputs from observation devices such as CCTV, IDS etc. Analyzing traffic activities for violation purposes proves effectiveness and prevents security vulnerabilities in a complex environment.

Using Deep Data, intelligence agencies can consume, analyze and make sense of this hyper volume of structured and unstructured data, in real-time speed.  An expert system based on semantic technologies and domain ontologies can facilitate agencies to classify relationships and unite the dots in this huge intelligence familiarity base to help wisdom, avert & resolves crimes.

Within a couple of years, deep data of this nature will be available to emergency service operators which along with information from sources such as video surveillance in public/commercial spaces, medical emergency alerts and detention lists, will help create a proactive—rather than reactive—security environment. With deep data analytics technology, these operators can analyse the varied data collected, make it actionable so as to become intuitive for the safety and welfare of the citizens by interpreting the possible patterns that might occur. Predictive analysis can become an integral crime – prevention tool as various police departments are in need for analytic tools to parse large volumes of data to forecast patterns and prevent crimes.

Earlier in the day, sourcing the data was the problem however with technological advancements; the issue is now analyzing the information which is not only enormous but also disparate and making that actionable so that members of intelligence agencies and police can fully exploit the available information. The problem is heightened since it is essential that the right data be channelized to the right agency across a number of channels. As the Government of India embarks on a journey to modernise its IT infrastructure across agencies and sectors, data analytics is the key to both preventive and responsive action with regard to safekeeping of the public. With data analytics technology, PSAPs will be able to not only analyze data but also predict future security threats so as to prevent harm to the citizens of the country.

The author is Country Manager, Video Intelligence Solutions, Verint Systems. Views are personal.

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