Hanwha Techwin Introduces AI Inside The Next Generation Of Video Camera

Compared to some other technologies, video cameras haven’t been around for that long. First used in 1942 to observe a rocket launch, cameras didn’t become used publicly until the 1960s.

This makes the technology’s numerous advances since then all the more impressive improving image quality and capture, footage storage, and integrations with wider security and business systems. Becoming what is recognized as a core part of every security function and beyond.

AI in video cameras

Video cameras are set to advance again, due to artificial intelligence (AI) maturing and becoming mainstream. A trend was accelerated by the COVID-19 pandemic with 52% of companies increasing their AI adoption because of COVID-19 and 86% stating that AI is mainstream in their organization.

In video cameras, AI plays a two-fold role in making image analysis possible but also improving the quality and reliability of captured footage. In doing so, AI is bringing new levels of situational awareness and understanding to security teams and other business functions.

Why does AI in video matter?

AI-based solutions help comb through vast volumes of data to see exactly what they need to when they need it

As the complexity of cameras and data has increased, so too needs intelligent and quick ways to process it. Modern-day video cameras capture a vast amount of footage and generate reams of data that is impossible for human teams to manually sort through. AI-based solutions are the only practical answer for this, helping staff comb through vast volumes of data to see exactly what they need to when they need it.

In many ways, AI adds a brain to video surveillance systems. With AI’s support, operators no longer just ‘see’ what’s happening but they have greater context from connected sensor data and they can focus on the events that need human input.

AI at work in current cameras

As for AI’s role in current video surveillance systems, it improves every part of operations, from situational awareness and response times to investigations and team efficiency.

Greater focus

More specialized AI can aid with traffic management, by analyzing traffic density

With AI continuously analyzing footage from video cameras, operators can focus solely on the things that require their direct input. AI can alert them to suspicious behavior, for instance, potential trespassing, emergencies like fire or flooding, and vandalism.

More specialized AI can aid with traffic management, by analyzing traffic density or average travel time in a particular area, flagging dangerous driving, or illegally stopped vehicles.

Fewer false alarms

Due to deep learning, AI cameras are now so advanced that they can differentiate between real events that trigger different actions.

For example, not triggering an alert when wildlife enters a predefined area but alerting staff if a person enters it. This reduces false alarms. Video noise can also be disregarded so operators don’t waste time and effort on false alarms.

Advanced search

Instead of manually watching hours of footage, AI can pinpoint the exact video needed from an event

Alongside this extreme accuracy, operators can also use AI tools, like the Wisenet WAVE smart search, to search for specific features or footage. Instead of manually watching hours of footage, AI can pinpoint the exact video needed from an event.

Operators can also find people wearing specific items of clothing, different age groups, and genders, and the various vehicle makes colors and number plates. With this, a shoplifter could be quickly identified or a stolen vehicle apprehended.

Enhanced image quality

AI is helping to improve the footage quality relayed to operators, as well as storage and bandwidth. The BestShot AI feature in Wisenet P series cameras automatically chooses the best images of an object or event to send to a backend server (minimizing storage and bandwidth requirements).

New AI technologies can also apply low compression rates to objects and people detected in the footage, and high compression to the remaining field of view. This improves bandwidth efficiency without compromising the quality of the footage that operators view. Plus, solutions like the WiseNR II noise reduction uses AI to reduce blur in noisy, low light environments. This is complemented by AI-based Preferred Shutter technology that automatically adjusts shutter speed to further reduce motion blur.

On the edge

One of the impressive things about current AI video solutions is that they can be pre-loaded in the cameras

One of the most impressive things about current AI video solutions is that they can be pre-loaded in the cameras themselves. These cameras have the processing power to analyze captured information at the Edge, eradicating the need for large amounts of data to be transmitted over the network.

This opens up more opportunities to run onboard analytics like people counting, object detection, and heat mapping without the need for an extensive VMS, NVR, or server setup. This makes implementing AI a lot more cost-effective and scalable.

AI for security 

This means that the power of AI can become part of your security operation from the moment of installing a camera. No coding or data science knowledge is needed to unlock this ground-breaking technology.

AI can do much more for security teams, helping to consolidate data, track entry and exit, detect tampering, and more. Plus, it’s helping organizations face all kinds of challenges beyond this, influencing their operations and adding value beyond security. Moreover, because AI is more easily deployable and cost-effective, these benefits are easier to realize than ever before.