Categories: Big DataGoogle Glass

Google Glass & Big Data – Boon for Crime Control

A class of bloggers & writers have been writing about the google glass hurting the privacy. Thus, this may pose barrier to widespread acceptance of google glass device. However, google glass shall surely act as a boon to crime control and sooner than later, government will get on board for acceptance for glass device for police personnel.

Google Glass & Big Data for Crime Control

 

Google Glass for Capturing Pictures from Crime Spot

However, to think of one of the out-of-box benefits provided by google glass, which is “take a picture”, this may prove to be a boon to police department across the globe. Imagine police personnel start wearing a cool glass device. They could easily capture multiple pictures from the crime spot.

In the normal scenarios, police personnel are unable to take the pictures due to complexity involved with handling cameras (even mobile ones), taking pictures and sharing to the investigation team. With google glass, this would be as simple as “ok glass, take a picture” and that’s it. The pictures will be uploaded to google cloud, and may be posted to glasswares if programmed that way.

In addition to above, citizen journalist could as well contribute to quick pictures on the crime spot.

Big Data to enable detailed investigation along with historical data analysis for crime control

Once pictures are captured with glass device, the pictures along with location & other details could be uploaded to service provider server using Google Mirror API and Glasswares. You would agree that glass devices with thousands of police personnel would lead to upload of several hundred GBs of pics from different regions within a particular country. Thus, this would lead to multiple issue:

  • Storage of Image & related data
  • Processing of information
  • Analytics for investigation

The above problems related to data sounds like a big data problem and could be handled using Hadoop technology stack. Some of the hadoop technologies that could be used are following:

  • HDFS for data storage
  • MapReduce for data processing
  • Hive/Pig for analytics
Nidhi Rai

Nidhi has been been actively blogging in different technologies such as AI / machine learning and internet technologies. Her field of interest includes AI / ML, Java, mobile technologies, UI programming such as HTML, CSS, Javascript (Angular/ReactJS etc), open-source and other related technologies.

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