Four Considerations for Leveraging Artificial Intelligence (AI) in Surveillance Systems

New video intelligence developments in cameras and sensors can help integrators expand beyond security, with the right planning.

Four Considerations for Leveraging Artificial Intelligence (AI) in Surveillance Systems

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In what seems like the blink of an eye, security cameras have evolved into smart sensors. With the help of artificial intelligence (AI) and video analytics, cameras can now spot security threats on their own, without someone always watching the video feeds, and improve how everything from safety risks to customer experiences are monitored.

This broader use of video intelligence outside of just security can make workplaces safer and more efficient. But to use these new capabilities effectively, you need to understand how to plan and design camera systems that can meet – and exceed – your customers’ needs.

Let’s explore the criteria that will be key to transforming what your customers and businesses can do with security cameras.

Assess the Environment

Expanding video intelligence into applications beyond security requires a holistic understanding of your customers’ operations and how these technologies can potentially fit.

Start by examining your customers’ challenges and pain points. Hold in-depth, design thinking sessions with key stakeholders at your customers’ locations to explore how video could be used in new ways. This includes looking at the facilities, how people work and what processes are in place. This could uncover opportunities to use cameras in applications outside security, such as merchandising, safety, occupancy and operational insights.

Additional factors, such as state and local laws, also must be considered. For example, anonymized capture may be needed to help prevent bias and protect people’s privacy, especially in settings like medical facilities, schools and courthouses. If laws including HIPAA or the EU’s GDPR apply, it can also affect where cameras can go and what data they can collect.

Consider Your Deployment Options

More applications for video intelligence beyond security inherently create more deployment considerations. These can range from the camera’s placement and field of view to an environment’s lighting and potential sources of glare, to where the analytics will be processed.

Where you place cameras can be critical for helping your customers collect the information they need to measure targeted analytics accurately. If vehicle activity is monitored, for instance, camera placement should exclude a nearby road in the camera’s field of view that may result in collecting unwanted or inaccurate information.

Similarly, an application like people counting or line queueing can be easier to measure if cameras are placed in a straight-down view.

Evaluate Your Security Camera Processing Needs

Unlike legacy, analog cameras, advanced cameras require processing power to leverage their full capabilities. This will be a critical part of any discussion with customers looking to upgrade their camera systems, regardless of application. When it comes to processing AI-powered analytics, you have four options. Each has its advantages, costs and requirements.

  • Analytics at the edge is a good option when using a camera for one application, like fire detection or gauge reading. However, this option can have local data storage limitations and only run a limited number of analytics on a camera at one time.
  • Cloud-based analytics is a good choice for applications involving multiple or remote locations. This option is easy to install, scale and maintain. Depending on the use case, that scalability and flexibility can be appealing, especially when compared to solutions such as network video recorders (NVRs) and servers that can be expensive and may not be feasible on a large scale. The trade-off is that cloud-based analytics typically has a recurring fee based on factors like the number of cameras used, the resolution required and how long data is stored.
  • Server-based analytics avoids recurring fees, but an on-premises server must be factored into the overall cost. Manufacturers offer bundles that include cameras, servers and video management systems. If using solutions from multiple manufacturers, make sure they’re compatible.
  • A hybrid solution can use a combination of the above approaches to bring each of their unique benefits to a project. For example, you could use on-camera storage and analytics while allowing the device to be managed with a cloud-based application.

Identify the Security Camera Infrastructure Needs

The unique demands of each project will determine whether your customers can use their existing infrastructure or if additional equipment investments are needed.

Some applications can leverage existing cameras. For example, a line-crossing or area-of-interest application that uses server-based analytics processing are tasks that could allow you to use your existing cameras. But for applications that run at the edge, you may need to work with your customers to implement newer, more sophisticated cameras.

It’s also important to consider the infrastructure behind the camera. Deploying more cameras or cameras with additional sensors could strain network bandwidth, for instance. And cabling limitations could restrict camera deployments to 100 meters from power and connection sources.

Implementing a utility-grade (UTG) cable infrastructure can help your customers meet their application and connectivity needs not just today, but in the future as well. UTG cabling delivers performance and reliability levels beyond industry standards, and can reach at least 150 meters, some as far as 185 meters.

Audit, Adapt, Achieve

It’s clear that AI-powered video intelligence is changing the game for security cameras, turning them into smart sensors that can be effective solutions in a wide range of applications. By understanding the possibilities, you can have solutions-focused conversations with your customers and work with them to look at their options, and plan carefully. Not only can these conversations potentially uncover additional revenue opportunities, they can also lead to deeper relationships with your customers.

Tara Dunning is vice president, global security and infrastructure, at Wesco.

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