Is AI really necessary for video surveillance?

AI is often used as a term to attract organisations with promises of cost savings and, often, unrealistic, levels of accuracy. But is the new technology always essential? Chris Price reports.

When it comes to video surveillance, Artificial intelligence (AI) is often presented as a panacea – a technology providing all the answers to all the client’s security problems. Not only can it save money, it can also offer unlimited functionality and, some claim, close to 100% accuracy.

However, the truth is somewhat different. While AI does have a growing role within surveillance, it’s not without its faults. Nor is it always necessary for video surveillance with many systems on the market able to provide solutions using existing data analytics without the need for investment in complex deep learning (DL) or neural networks that imitate the human brain.

“The way AI works is actually pretty crude,” Dean Drako, Founder and CEO of cloud-based video surveillance provider Eagle Eye Networks, admits. “You basically pick thousands of images that are what you want and thousands of others that aren’t what you want. Then you train the system by teaching it.” Where cloud-based surveillance companies like Eagle Eye Networks come in is that they can do a lot of training of AI systems, saving companies the time and expense of doing it themselves.

By Chris Price
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Eagle Eye Networks

Since 2012, Eagle Eye Networks has provided smart cloud surveillance solutions, leveraging AI to drive natural language search, automation, and more. Eagle Eye’s camera-agnostic approach heightens security while saving money, time, and resources.