With the advent of the Internet of Things (IoT), more and more of our devices are connected to the network, making it possible to amass data and analyze it for patterns and trends. In this way big data is becoming more of a resource for virtually every industry including security, where video captured by cameras can now be more easily stored and analyzed by software. However, this new technology has taken hold so quickly that some organizations are now sitting with immense quantities of raw data without the knowledge of how to best use it. Since big data is only going to get bigger, security professionals need to understand the best ways that they can put it to use.
The amount of video generated by surveillance cameras is massive, and with compression and storage technology improving along with camera technology, much of the video generated is of a high enough quality to present a variety of opportunities. Technologies such as facial recognition and people tracking integrated with surveillance systems can rapidly mine and analyze video data. With software in place to analyze the hundreds of hours of video data generated by a surveillance system’s tens, hundreds, or even thousands of cameras, it is now possible to identify patterns and make connections that would otherwise be impossible to make without a tremendous investment of manpower.
Big data minimizes the margin of human error significantly. Before the era of big data, if a department store wanted to use video surveillance to help them change traffic patterns to direct more customers to a certain department, they would need to devote a team of personnel to watch the video from every area of the sales floor every moment the store was open, notate the traffic patterns individually, and make a recommendation based on their aggregate observations – a tremendous project to undertake. With big data and analytics, this is no longer necessary. High quality video images enable integrated analytics to evaluate hours and hours of video, determine patterns, and count every single person that enters designated areas. With this data, the department store can more easily determine where their choke points are and where they need to make a change.
With the IoT, the opportunities presented by big data are even greater. Diverse networked devices sharing data can present a much bigger picture than surveillance video alone. For example, in a safe city deployment, software that tracks social media data can be correlated with video surveillance data to detect issues – riots that may develop, traffic incidents that might form – and risks as they happen, or even before they happen. In a university setting, surveillance data can be correlated with access control and student information during an investigation into possible misconduct. With coordination across the various departments within an organization, it is becoming easier to mitigate risk, anticipate customer needs, and increase return on investment.
As we generate more and more data, the potential of that data grows. Software capability has increased to accurately and efficiently process more data than could feasibly be processed by any human user. The video your surveillance system captures, with best-in-breed integrations, can provide you with a variety of opportunities to optimize and escalate your business. With the insights you gather from big data, you can discover existing problems, mitigate future ones, and manage incidents as – or even before – they occur.