Bomb Suspect Images And Big Data Tech Combined Would Be A Better Search

The bomb suspect images from the Boston Marathon bombing and Big Data technology and/or crowdsourcing would be the perfect match for finding the terrorists who perpetuated this heinous crime.

As previously reported by The Inquisitr, Police reportedly believe the Boston Marathon bombs, which were made out of pressure cookers and metal shards, were most likely brought to the scene in a large, black duffel bag. Authorities have been scanning photos from the marathon looking for suspicious characters carrying large black bags.

Current search efforts focus on pushing the bomb suspect images and videos from the Boston Marathon out to the world in hopes that someone might know the suspects and report them. But so far these methods have only resulted in chaos.

Salah Barhoun was the target for one of these purported bomb suspect images, and fortunately he went to the FBI before things could get ugly. There were even reports that one of the bomb suspect images led to an arrest, but CNN quickly apologized for its false reports.

So what is Big Data and how could it help find the terrorists using the bomb suspect images? Big Data is the idea that it is possible to analytically process massive amounts of data in order to derive insights into problems facing the world. For example, one Big Data project called the Integrated Marine Observing System (IMOS) collects, integrates, and shares terabytes of data about animal migration, ocean salinity, temperature, currents, and carbon storage from a variety of sources. Before the 2012 Presidential election, a Big Data project from Avast correctly identified Obama as the winner through crowd sourcing.

One crowdsourcing method that is currently being employed is an attempt to gather as many Boston Marathon 2013 photos as possible onto a single area on Reddit. People who took videos or photos at the Boston Marathon are asked to post them at the r/findbostonbombers Reddit Boston Marathon section. But crowdsourcing the bomb suspect images may be relatively slow and lead to some false positives as already seen.

The FBI is currently manually combing through all the data with the help of object/facial recognition companies. A Big Data bomb suspect images project would essentially automate the function of crowdsourcing. Using object recognition and other methods, it should be possible to build a database of images based upon position and direction of sight. The result might be similar to how Google maps allows you to “look around” from omni-directional photos taken from the Google car cameras.

An automated program could cross-reference photo timestamps, derived positional data, and video images to build a quasi-three dimensional progression of the events leading up to the Boston Marathon bombing. Hopefully, such an effort might accurately identify when the bomb carrying bags were placed and then backtrack to a bomb suspect image that portrays the facial features of the terrorist(s).

Do you think this Big Data bomb suspect images project should be undertaken?