Wednesday, February 14

How could Sensors, Social Media, Call data, Intellegence Data & Big Data help prevent terror attacks on Indian Borders?

As we hear the news of another terror attack in Jammu & Kashmir in India, I wonder what kind of software driven intelligence is used by Indian Army to predict and prevent terror attacks. I was in discussion with an army officer from intelligence department and we discussed how these technologies are being used by telecom, bank & insurance companies to prevent frauds, by power and oil companies to predict and prevent power outages and the army gentleman was amazed at the use of big data, sensor, predictive analytics, artificial intelligence technologies by industry verticals.

Software architects are trained to identify scope for innovation by using existing infrastructure coupled with latest technologies. We can sit with a bottle of beer or a cup of coffee and tell you a incredible story that may seems fantastic and surreal but quite easy to implement. The army men promised me that he would discuss the case studies with his boss and hopefully set a meeting with him! What could be better than being invited to share ideas with the guys from army intelligence and do my bit for the country. I am going to post some usecases that can be used to build a Border Security solution using Sensors, Predictive Intelligence & historical data. I am not familiar with the technologies in use by border security forces so I am going to assume certain facts.


What I think can be achieved in a short time is a Multi Dimensional Intelligence Dashboard (we love buzz words!) that can give various insights into potential security breaches on border and real time alerts.

Intelligence Dashboard can give intelligent insights for example :


1) What are the locations around the border where enemy may try to sneak in on a particular time on a particular day?

2) What is probability of an intrusion at various locations on border based on human movements on both sides of the border

3) What is probability of intrusion based on weather condition and day/time of the year

4) What kind of intrusion strategy can be expected on next D-day

5) What are the support groups that could be working within the border to support the enemy  intrusion and how to track their movement

6) What is the synergy between social media, telecommunication and messaging application and enemy activity

7) How to auto detect events that indicate potential enemy activity in near future

The following sample illustration shows different data sets being collected, processed in real time and predictive analytics being performed on data at rest. Data sets are collated and analysed to derive insight into potential incidents and displayed on user friendly dashboard






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