Harnessing Big Data in the Physical Security Industry

The physical security industry is rich with contextual data. Here’s how harnessing that data can help the industry in a multitude of ways.

Harnessing Big Data in the Physical Security Industry

This article originally appeared in CS sister publication, Security Sales & Integration.


Today, the success of an organization in any industry is defined by how far the organization is in its “digital journey” as compared to its peers, simply because this digital journey enables significant benefits which are otherwise very difficult to capture.

This journey is fueled by big data and the organization’s ability to harvest and harness that data. The physical security industry is rich with contextual data. Every sensor installed at a customer site is a source of information — from badge swipes in access control systems to video streams in intrusion systems, the control room has access to this data.

The collection of data is easier in some instances than others, but harnessing those sources can help the industry in a multitude of ways, including improvements in operational efficiencies, commercial growth opportunities and improved customer satisfaction.

Understanding Big Data & Its Importance

Let’s get a few definitions out of the way: The large and complex data pool becomes what is commonly referred to as Big Data, and the aggregation of this data into an accessible location(s) is the Data Lake. The analysis of this data is referred to as data mining, which can be enabled through advanced statistics, machine learning and artificial intelligence (AI).

These advanced algorithms allow security providers to gain insight into customer systems and help identify any anomalies which could have otherwise gone unnoticed. Large companies like Facebook and Google are harnessing the disparate data they get from consumers and leveraging it to sell them new products and services through ads.

What Big Data Means to the Security Industry

Within the security industry, the back-end management systems have become increasingly sophisticated and the use of sensor data and other physical security data is now feasible. This has enabled our industry to analyze information at hand in numerous ways — such that we can enhance our forensic operations and use the power of machine learning and AI to help us make predictions.

This, in turn, helps us become more proactive for our customers. For example, through the use of sensor data coming from various devices on-site, we can predict why certain devices are failing faster than other similar devices, thus ensuring that our customers are secured at all times.

Similarly, with the use of point-of-sale (POS) data and associated camera analytics, we can predict if there will be employee-related theft in the stores of our retail customers. We can also aggregate access control and camera feed data with the building power company data to drive efficiencies for the customer in reducing energy costs.

Challenges With Big Data Management

There are numerous challenges to put together the Data Lake. The biggest challenge lies in bringing together all the myriad data sources that could be understood and processed by computer systems. In many cases, data can be unstructured (for example, free textual data), while in other cases the integrity of the data is questionable (for example, different regions of the country enter similar customer information in disparate fields.)

Large Big Data companies like Amazon, Google and Microsoft are foundationally built to solve these problems and are thus leaders in disrupting various industries, including physical security. These organizations can harness data sources from outside the industry and combine them to drive even better insights.

Another critical issue with Big Data is cybersecurity and considering the transport of various data feeds and the potential use of Cloud computing for information aggregation and processing.

Cloud computing provides the unique ability to access powerful tools like machine learning on a per need basis. This data repository will continue to grow, making it more susceptible to cyber attacks. Consequently, physical security personnel have to work closely with IT teams to ensure cyber hygiene and cybersecurity.

With all systems and sensors connected in this architecture, it is very important to keep a close eye on regulations, particularly on GDPR-related requirements. Special attention is needed to make sure that any personally identifiable information is scrubbed thoroughly and is not transferred across country borders when it is not allowed.

Our Role as Security Integrators

As we dive deeper into the Big Data age, integrators play a key role in that they have the ability to consolidate, manage and analyze the data. In the new age, hardware is becoming more of a commodity and the value-add lies in the services the integrator can provide above and beyond physical security.

More and more of the client base is moving toward Big Data-based systems for their own use and are expecting the same from their security providers. In the coming few years, Big Data mining will continue to grow in our space and we will have to be ready for it. This is our future.


Moiz Neemuchwala is Innovation Product Manager – IoT/Big Data, Stanley Security.

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