Coming of Age

Coming of Age

Innovation and automation are being built on strong data foundation

There have been on-going discussions the past several years about how Big Data and Artificial Intelligence (AI) can be used to modernize physical security systems and operations. The truth of the matter is that digital transformation has already been taking place for quite some time, albeit in small steps with what is now a very fast-paced technology evolution.

What were once high-level theoretical discussions on mining data from both traditional physical security operations and scores of new and emerging IoT devices have now become a reality. This next generation of innovation and automation is being built on strong data foundations and data intelligence. And it is changing perceptions on how physical security systems need to be designed, implemented, and managed in this new era of datadriven physical security solutions.

Perhaps the most significant take-away from the genesis of data- driven physical security is the change in mindset from reactive to proactive systems technologies – the ability to autonomously process data in real-time to reduce friction in business process execution by eliminating human intervention, and to deliver actionable insights and even predictive analysis.

This has the potential to dramatically increase the overall effectiveness and efficiency of physical and cyber security operations, mitigating risk across the enterprise. As a result, physical security technologies and operations will continue to leverage real-time business intelligence across the enterprise to facilitate real-time decision making.


One of the biggest challenges faced by security professionals today is the ability to harness and analyze the tremendous volume of data being generated by physical security operations containing spatial, sensor and transactional data and network of devices to derive meaningful actionable intelligence. With the bulk of such data being unstructured data, new data-driven solutions are required to contextualize this disparate and fragmented information in a seamless way.

One of the reasons this presents such a daunting challenge is that physical security operations typically employ several different point-of-control systems and associated sensors / IoT technologies such as Physical Access Control Systems (PACS), video surveillance, intrusion sensors, biometrics, visitor management, dispatch, incident management systems and more. For the most part, these systems are not highly integrated and provide siloed views of activity which fail to provide a complete picture, precluding intelligent insights from being drawn since all the data is not being analyzed in the same context.

The first step in resolving the fragmented challenge is to bring data from these otherwise disparate system technologies together onto a special purpose unified platform. It requires discovering, connecting, integrating, transforming, managing, analyzing, and storing valuable data insights and enable the execution of applications that are smarter and intelligent – net-net derive 5-10X value.

The next step is to understand how and where to use this newly found data intelligence to improve business processes. For example, can one apply data science to predict occupancy levels of a building or a floor to better schedule employees coming into a facility during today’s pandemic times? Can one use data intelligence and predict what physical security IoT sensors or devices will fail within 30 days, and make the retroactive repairs as opposed to being reactive? There are numerous such promises of the data science discipline.

Last, but not the least, is to make this all very simple for users to consume. The data science, the machine learning and the arti- ficial learning can only work if the intelligence and insights from the myriad data sources are driven to the applications without heavy lifting or understanding of computer and statistical science. It should be very easy for users to incorporate these applications into business operations. New developments in AI powered software platforms can help alleviate both physical and cyber threats by inferencing from large volumes of data, and quickly triangulate small subsets of pertinent information, provide actionable insights etc. This not only simplifies and improves physical security operations while delivering tangible ROI and lowering TCO, it also automates major security functions related to Physical Identity and Access Operations, SOC Automation and Cyber-Physical Security defense.


New data driven solutions are now coming to market that promise to address many of the inherent legacy system and data integration challenges that plague the physical security industry. A prime example is the recently unveiled Vector Flow platform, which is capable of processing and analyzing vast amounts of data from otherwise disparate security systems, data stores and input devices.

This innovative new solution derives actionable intelligence from physical security data using advanced Artificial Intelligence (AI) and Machine Learning (ML) algorithms that empower a whole new range of highly advanced automated physical security applications that were previously unattainable. A truly converged data driven physical security solution, the new platform presents myriad opportunities for digital transformation and improving several major business processes such as:

Physical Workforce Identity & Access Management (PIAM) which unifies and streamlines identities, access and badges; on/ off boarding processes; physical access provisioning; access audits and compliance to regulations; risks analysis and prescriptions and mobile self-service.

Physical Security Operation Center (SOC) Automation for autonomous false alarm reduction and reporting, unlimited device monitoring and auto optimization, auto configuration of devices, and auto detection of faulty devices, along with provisioning automated virtual SOC assistants using AI/ML playbooks.

Cyber-Physical Security to enforce “defense in depth” using advanced AI models that detect vulnerabilities in physical security, IoT and building automation devices to prevent cyber surface attacks and reduce organizations’ exposure to overall risk.

Vector Flow’s data-driven solutions are already implemented at several Fortune 1000 companies. This includes a global telecommunications provider with over 450,000 identities – the Vector Flow team replaced the legacy PIAM application with a new AI-enabled physical identity lifecycle application. The new solution promises to save millions of dollars in direct costs over the course of the contract while increasing overall security operations productivity, compliance to regulations and delivering valuable service to the enterprise.

In another example, a top Research and Pharmaceutical company, focused on anti-viral drugs and treatments, deployed Vector Flow’s AI-enabled solution to streamline SOC operations, enable AI-driven device health prediction, reduce false / nuisance alarm counts and streamline SOC functions by establishing and measuring KPIs across all SOCs including compliance with newer regulations such as AB 685 & SB 1159 for building occupancy during Covid-19 times.

This article originally appeared in the September / October 2021 issue of Security Today.


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