Artificial intelligence (AI) presents a perfect solution to compensate for unmanned environments or those with limited staffing, or the loss of vigilance after looking at a screen too long. AI can help us not only watch continuously, but also feed systems that are able to sort, organize and categorize massive amounts of data in a way that human operators cannot. And it can do so far more reliably than traditional video analytics ever did.

When budgeting for video surveillance cameras, there are multiple factors to consider that affect cost beyond the camera itself. It’s important to also know the cost of installation, and the cost to service or upgrade a unit in the future. While configuring a small number of cameras will likely have little impact on cost, the labor involved in installing and servicing hundreds of cameras can be significant. A modular approach to camera design is necessary to reduce the installation costs and long-term maintenance of such cameras.

It’s helpful to reflect on where we are now versus where we are going. Today, there is still more discussion about what might be possible than actual physical products on the market. Much of the conversation centers on practical ways to utilize deep learning and neural networks and how these techniques can improve analytics and significantly reduce false-positives for important events. 

While the concept of the multi-sensor or multi-directional camera is not new, there have been noteworthy advancements that make these cameras the best choice for many types of security installations.  In the past, many multi-sensor cameras were not able to deliver high frames per second / per sensor (fps) for smooth, clear motion capture and frequently represented a compromise in performance.