Simplifying Surveillance in the Age of More

Why an integrated, enterprise approach to IoT surveillance is the way forward

More cameras, more sensors, more intelligence―today’s advanced video surveillance systems do more than ever before to protect people and property, with applications far beyond perimeter monitoring and access control.

However, as a recent IDC white paper points out, putting new surveillance technologies to work quickly gets complex. More devices, more data, and more connections mean more potential security risk and more integration and management challenges.

With widespread digitization, surveillance moves from what was once an essentially self-contained function to one that spans the larger enterprise IT/IoT environment―with implications for infrastructure, security, data management, analytics, operations, software development, and workplace tools.

More “things”

In many ways, video surveillance via the first IP (Internet Protocol) cameras in the mid-90s was the original IoT use case, where digital cameras collected and centralized information about the physical world. Fast-forward twenty plus years to today. The ecosystem of digital IP cameras has extended outward to a web of interconnected “things” in surveillance, including not only more advanced imaging sensors but also other types of IoT sensors capable of detecting and digitizing information about the physical environment ranging from chemical signatures to temperature to pressure to sound to vibration. The growth of this market is continuing its upwards trajectory. By 2021, IDC predicts that annual shipments of fixed IP/network surveillance cameras will exceed 130 million and mobile surveillance cameras (e.g.,  drones, vehicles, body wear) will top 73 million.

A more complete picture

The ability to combine digital video data with other IoT-sensor surveillance data as well as with other data sources (e.g., employee records, building schematics, campus maps) and powerful analytics (e.g., telemetry, facial recognition, machine learning, artificial intelligence) enables a new kind of computer vision. Security officers gain a more immediate, complete, and accurate picture of situations as they unfold. The likelihood of useful machine-recommended responses grows. And investigators gain digital search and analysis tools that make inquiries into past incidents much faster and easier.

More data

One of the biggest challenges is storing, aggregating, analyzing, and protecting the massive amounts of data generated by a greater number of cameras with higher resolution, multiple modalities, and additional IoT sensors. Security departments are turning to IT organizations for expertise in how best to meet the demands of compute performance, storage, and backend analytics as well as with how to comply with the longer retention periods being set by regulatory bodies and institutional policies. New storage technologies and tiered storage approaches are needed to achieve efficiency and resiliency. And many enterprises are looking to hybrid or private cloud storage, especially for archiving video data, for the flexibility and scalability it offers.

More vulnerabilities

Each IP camera and IoT device in the surveillance network is a potential attack vector, making advanced security methods critical—from software-defined network micro-segmentation to edge compute security to over-the-air updates.

More complexities, more opportunities

The buildout of advanced surveillance systems presents significant challenges in terms of hardware, software and network integration, deployment and onboarding of new devices over time, and ongoing management. But rather than addressing these challenges at the solution or even application level, organizations should tackle these challenges using a broader enterprise-wide lens—more specifically, by looking at how the solution can be leveraged to help drive future growth and transformation, including:

  • Digital transformation: Determine how surveillance data and other enterprise and external data can be leveraged with advanced analytics, machine learning, and AI not just to address safety and security objectives but also to advance other objectives in areas such as product quality, customer experience, and market differentiation.
  • IT/OT transformation: Achieve new agility and efficiencies through architectural and operational alignment of IT and OT investments.
  • Workforce transformation: Address changes in roles and responsibilities and provide the right type of display and dashboard tools.
  • Security transformation: Take a more proactive, built-in software-defined approach to secure enterprise data and systems to better handle the increased number of threat vectors.

A more open, holistic, and integrated approach―from camera to core to cloud

According to IDC, the best approach to deploying advanced surveillance systems and integrating them into the greater IT environment is with an open, integrated, and holistic platform.

As the number one global infrastructure provider for surveillance solutions today, Dell Technologies has done just that with our new Dell Technologies IoT Solution for Surveillance platform. IoT Solution for Surveillance is an end-to-end surveillance platform built on Dell and Intel® technologies―with the customer’s choice of devices, software, and analytics―all validated in one of our three global Surveillance Validation Labs. The open architecture includes designed-in security and scalability that reduces risk, cost, and complexity while providing the flexibility to adapt to future innovations and needs.

Dell Technologies IoT Solution for Surveillance combined with our expert strategic consulting services and backed by the Dell EMC Global Services and Support team equips organizations with the right solutions, skill sets, and services needed to meet their surveillance needs today while preparing for what’s coming tomorrow. If we can be sure of one thing, there will always be more.

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About the Author: Frank McCarthy