Discover Network Cameras and Their Metadata

In 2014, there were an estimated 245 million video surveillance cameras installed globally (HIS Markit). Real-time visual data have many applications. As researchers gain the ability to collect large amounts of visual data about the world, the true potential of data-driven research is recognized. Despite the large amount of publicly available real-time data, there are challenges that inhibit the true potential of analyzing real-time data from these cameras including identifying the cameras either statically or dynamically and identifying camera metadata once identification of individual cameras occurs.

Researchers at Purdue University have developed a method for identifying cameras on the internet; particularly, identifying public and closed circuit television cameras and the metadata associated with each in a static or dynamic manner. Examples of uses include monitoring traffic flow, viewing wildlife, detecting intruders or anomalies, and monitoring weather conditions and emergencies.

Advantages:

-Allows access to existing network of cameras

-Collects metadata

-Numerous applications

Potential Applications:

-Security

-Weather information

-Traffic information

-Emergencies

-Machine learning algorithm development

TRL: 7

Intellectual Property:

Keywords: video surveillance, real-time visual data, camera identification, camera metadata, public safety, traffic monitoring, closed circuit television, machine learning algorithm development, data-driven research, internet connected cameras, Big Data, Cameras, Computer Security, Computer Technology, Data, Metadata, Networks, Security, Software