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Sunday, 17.10.2021
eGovernment Forschung seit 2001 | eGovernment Research since 2001

COVID-19 introduced new uses cases (beyond safety and security) for video surveillance technologies employed in smart cities.

COVID-19 taught us that cities have continuously played a critical role in the management and containment of crises. As noted in a report by Cities Today, the post-COVID road forward requires a change in municipal mindsets — from building “smart cities” to building “resilient cities.” As we begin to focus on what life could look like after a pandemic of this proportion, we’re taking our learnings on resiliency to better prepare ourselves and our communities for the future.

Certain smart solutions, such as video surveillance, offer a solid starting point for understanding and improving proactive municipal responses. Once implemented, they allow cities to develop robust response frameworks in advance of future public health challenges.

No matter the scenario, it’s data that makes the difference. Effective collection, storage, and analysis of video data empower cities to make informed and educated decisions around the health and safety of their citizens. However, as data volumes and ingestion velocities increase, questions and concerns arise around the proper IT infrastructure required to leverage the true value of video data.

Because of the numerous changes that COVID-19 brought to our society overnight, we now have a new group of individuals that have garnered relevant knowledge in this space. Now is the time to look to those IT and security experts to better prepare for the future.

Smart cities provide insights that save lives

As COVID-19 made clear, the social nature of humankind is a critical viral vector — even a single infection can “super spread” if all caution is thrown to the wind.

According to Jimmy Whalen, CEO of Velasea, advanced video surveillance offers a way to capture and comprehend these scenarios, and in turn, help mitigate infectious impact at the point of contact. “The importance of the computer vision industry is evolving,” he says, “and the camera is the primary IoT device of the future. It has senses and can tell stories just like humans.”

Connected cameras are utilized to track critical data points, such as mask-wearing and core body temperature, enabling data systems to expediently create a statistics-based narrative in ways that humans cannot.

Enhancing smart video’s positive impacts

Video surveillance technologies deployed within cities are typically tied to safety and security applications, such as improving traffic management, tracking crime hotspots, or monitoring access to critical facilities.

COVID-19, however, introduced a new use case for these technologies by collecting anonymized temperature readings and movement data to detail, analyze and predict how infection clusters expand and evolve. And while the speed of video surveillance deployment has been impacted by COVID restrictions over the past year, this has not deterred intelligent cities from making necessary investments.

Kay Sharpington, a Gartner principal research analyst, noted, “Governments are increasing their spending on outdoor surveillance cameras to monitor cities for crime. In the wake of COVID-19, they are also used to track compliance with safety restrictions.”

Although regulations are changing and we’re reemerging from widespread lockdowns with loosened restrictions, we can choose instead to press on with establishing video surveillance frameworks that will continue to help mitigate the spread of viral threats by permitting cities to quickly analyze human movement patterns and rapidly devise targeted public safety protocols.

Empowering long-term adoption

To deliver on the promise of smart video solutions, effective data collection, storage, and analysis are critical. However, according to IDC’s research data in the Seagate Rethink Data report, just 32 percent of data available to enterprises is effectively utilized. In fact, the rapid uptake of video surveillance, IoT devices, and metadata captures nearly a third of global datasphere growth.

As smart video analysis becomes key to building and operating resilient cities, municipal governments must account for evolving infrastructure implications, including:

  • Increased data storage needs: More surveillance means more content, which results in larger data collection volumes and storage requirements. Meanwhile, large inputs of unstructured video data that previously would be archived now must remain available for deep learning. But not all storage solutions are created equal. Effective smart surveillance and video analysis require the adoption of the right architecture to increase storage collections and manage storage. In practice, this means the deployment of frictionless, tiered storage solutions capable of meeting both current and future video data-capture needs. At scale, this approach removes the need for city IT teams to manage and monitor limited-capacity data centers by offering reduced TCO and increased uptime.
  • Enhanced AI analytics: While improved data collection automation lays the foundation for smart surveillance, cities also need a way to interpret and apply this information to take meaningful action. The most successful cities integrate technologies that can analyze data from various sensors and sources, and newer video systems can be made capable of intelligent forensic searches that can find specific images or actions within a recorded video or even look across a video timeline to create a synopsis of related events. The ideal architecture would integrate customizable video analytics powered by AI to meet the needs of a particular facility. Neural network technology can enable systems to learn to perform customer-specific tasks by ingesting a breadth of video material obtained onsite.
  • Empowered edge solutions: Cities also need to consider edge solutions to help manage massive volumes of video surveillance data. While current cloud deployments excel at centralizing these resources, data collected at the edge and sent to the cloud for analysis before being routed back for action can result in delays that are undesirable and impossible for real-time public health or security responses. Improved, more powerful edge-computing deployments can help eliminate this backend backlog by managing the processing, filtering, and storage actions required.

Discovering emergent solutions for smart cities

Effective, connected video capture and analysis architectures require cities to deploy the right combination of front-line functions and backend support like intelligent camera systems, network video recording (NVR) servers, and end-to-end security solutions.

The basis of smart city video solutions is rooted in adaptable, intelligent camera systems. To build out infrastructure that both helps address current needs and evolving issues, municipalities must invest in customizable, AI-driven video solutions.

NVR servers provide high-performance scalability to municipalities to help meet collection and analysis requirements. These servers incorporate hard drives designed to manage AI workloads, reduce latency, and supply capacity to handle growing video data volumes.

Finally, cities must also deploy end-to-end security solutions for servers, storage, and AI appliances to ensure surveillance data is protected from collection to capture to analysis and every stage in between.

When designing for a city, IT architects must consider a number of factors as specific storage deployments will vary greatly according to required scale and precise use cases. Goals might include:

  • Populating large-scale high-performance VMS with storage that supports low-latency workloads
  • Safeguarding critical data and managing evidence-based data with secure end-to-end user access control
  • Scaling efficiently from terabytes to petabytes while accommodating nodes of any size; or lowering TCO with space-efficient, high-density enterprise storage systems with the highest possible IOPS per dollar.

Smart video technology has not only evolved in its ability to help mitigate current and future pandemic concerns but also paved the way for more robust, resilient, and responsive smart city management at scale.

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Autor(en)/Author(s): Jason Bonoan

Quelle/Source: RT Insights, 08.09.2021

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