A look ahead – a different perspective


I’m sure you’re all reading many other “predictions” blogs this time of year focused on Artificial Intelligence, analytics, and the cloud. Certainly, those are the important topics to track. In this piece, however, we’ll go a few layers deeper into these areas, and hopefully bring to light some aspects of these subjects not commonly discussed.  

With the rapid changes occurring in our industry, the accelerated development of new technologies, and constantly shifting customer expectations, solutions providers need to always keep looking ahead, or risk falling behind perhaps permanently.  

Let’s start with Artificial Intelligence.

Across our industry we’ll continue to see more deployments of “smart” cameras and devices that combine AI and deep learning algorithms. The result will be more targeted forensic searches, enhanced operational efficiency, and minimized storage and bandwidth requirements.

At its most basic level, AI, and its subset technology machine learning, refer to the ability of “machines” to learn over time. Think of it like auto correct, or when Netflix recommends a movie you might like.

In surveillance it's well-proven that AI, especially when combined with deep learning, can produce more accurate searches that pick up on only the elements a security team needs to see. That’s simply about increasing accuracy through AI algorithms.

A term we should begin discussing more when it comes to AI is “context awareness.”

It’s already happening in other AI applications, for example, subtitling and captioning of movies or TV shows. Where basic AI models translate sentences one by one, context aware AI can “read between the lines and accurately considering the “context” of a conversation, language nuances and the subtle differences of gender, slang, and multiple word meanings.

We're already doing that in our surveillance products. Think about WiseStream III, our AI-based “’smart” compression and noise reduction technology. It can say to a user “Here’s this high-resolution camera footage, do you want to reduce bandwidth and manipulate the compression based on the objects you care about?”

Context awareness takes AI beyond the level of pre-configured algorithms. It’s making a device aware of what I care about and gives systems the ability to gather information about its environment and adapt its behavior accordingly. Now, the camera is making choices to optimize its performance based on what it has learned is important to the user.

When we first started introducing AI into our products a few years ago, it was done on a selective and specific basis. We could detect a person or vehicle by specific attributes and trigger an event, start recording or initiate a forensic search. That’s extremely useful, but it’s also AI 101.

Through ongoing firmware updates, our newer models are able to take that targeted AI detection and internally adjust what the camera is doing. Again, it’s context awareness.

It’s also a key element of our WiseDetector, which can train a camera on a custom object. If I have a manufacturing facility or a warehouse, and I want to know when a forklift goes by or if one of my robots has moved around the warehouse, then the camera can optimize internal settings – shutter speed, noise reduction, use of WiseStream – all based on what I care about.

Heavily wooded areas versus open areas could also be factors in determining context. Most people don't care much about trees swaying in the wind. They’re probably more focused on the fence line or only want to see people walking inside the perimeter. Because those trees are not AI objects that we care about, context awareness will prevent your security system from wasting bandwidth or optimizing shutter speed just for them.

It's the next level of AI’s ongoing learning about its surroundings.

Sensor Fusion

It’s common for customers to want to integrate data from multiple camera sensors. That data could relate to smoke and fire detection, or sound detection.

The idea is taking multiple sensors, combining their data types, and having it all report into a VMS. In the case of our bi-spectrum cameras, we have a visible and thermal sensor and we're overlaying the video and the AI data from each. I could be watching a thermal imager and still see people in cars coming by because it's overlaying, or using, the AI data from one sensor on the other. Another example is using RADAR and being able to use that data with thermal or visible cameras to gain a full picture of a facility or perimeter and identify an object as a car because it knows that based on the data from another camera.

The idea behind sensor fusion is that you can visualize all your data in one place -- even if it’s not all directly video related, even in blind spots -- without having to check 12 cameras.

Seeing through the Clouds

The cloud has been a topic for years, and 2023 will be a year of continued acceptance. Many customers have moved past their lingering concerns and doubts about cloud security and reliability. Those hesitations have led to many customers trying the best of both worlds, maintaining hybrid cloud/on premise surveillance infrastructures.

We’ll see much more blending of on-prem systems with cloud backup or cloud archiving, with more customers embracing the idea of picking and choosing and only paying for the cloud services they need.

Several factors will dictate a customer's choice of hybrid, on-prem or both in 2023, mostly volume of data and bandwidth. It's also important to evaluate how sensitive your data is. If it's financial data, or it's GDPR controlled, you may not want to put it all in the cloud. Plus. Some markets, like cannabis, have regulatory mandates requiring offsite storage of video surveillance footage.

We’ll see more customers look to using the cloud on an “as-a-service” basis, creating customized security network infrastructures enabling flexibility, efficiency, lower unit cost and scalability – all while being simple enough for users to manage themselves. They will embrace the ability to easily scale bandwidth up or down, or for certain time periods, for example if their business is seasonal, they can plan for busier times of the year.

So, there you have it: a focus on the main topics that will impact the industry on 2023, but hopefully with enough of a different perspective to help you customize and sale for your individual business.

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About Hanwha Vision

Hanwha Vision (formerly Hanwha Techwin) has been leading the global video surveillance industry with world-class optical design, image processing and cybersecurity technologies for more than 30 years. As it broadens its business to become a global vision solution provider, Hanwha Vision will deliver more valuable and meaningful insights to customers by collecting key information and providing big data analytics utilizing AI and cloud technologies.

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