Did you know that there are around 770 million surveillance cameras monitoring us worldwide, and that number is on the rise? A recent report by industry researcher IHS Markit suggested that the number of cameras will increase by as much as 30% by 2021, to a total of one billion electronic eyes.
Most of the world’s surveillance cameras, 54% of them are installed in China, but the US isn’t far behind with 30 million security cameras, which equates to 15.3 cameras for every 100 individuals.
One of the reasons for this proliferation is technology advancement, specifically in the field of AI, and, in this article, we’ll be looking at how AI is revolutionizing surveillance techniques.
Artificial Intelligence and the Camera Watching Problem
While America does have over 30 million security cameras working every day, less than 10% of them are continuously monitored. They function mostly as a deterrent to crime or as evidence collection devices.
Doorbell cameras and home security cameras represent a growth area in popular home electrical installation projects, but for obvious reasons, they are not often monitored.
The reason for this lack of monitoring is the near impossibility of having enough human eyes focusing on all screens connected to all the cameras all the time.
IHS Markit suggests that it would take at least 4 people per camera to have complete surveillance cover without breaks. This means that you would need 120 million people to monitor all the current cameras, potentially rising to 156 million by 2021.
To put that in perspective, the current population of the US is 327 million, and it seems unlikely that one-third of it would be available to surveil the rest.
Artificial intelligence is transforming the way we think about surveillance because it represents the ability to watch all of the installed cameras without massive workforce costs.
Advances in AI technology and image quality have led to faster and more accurate facial recognition. They’ve also allowed law enforcement authorities and governments to use their vast surveillance network to do everything, as the Wall Street Journal points out, from predicting crimes to managing traffic.
Advanced AI can also use programs like natural movement tracking and natural language processing to both scan for suspicious behavior and call the police in real-time to report a crime.
Expanding Into Other Sectors
While there is a certain dystopian image of large populations being monitored by computers that predict crimes, the same technology is also being used for that surveillance in less security-focused sectors.
Natural language processing (NLP) has recently been adopted by many sectors as a way of building effective chatbots. With customers increasingly preferring rapid communication and problem solving built into the websites of the companies they use, the ability of solutions like chatbots and live chat to provide answers and services has become increasingly important.
NLP allows chatbot programs to understand and respond to written communication. For example, the “Hello chatbots” program used by the travel website Hipmunk is able to assist customers looking for travel deals and help them book flights, hotels, rental cars, or packages.
When the communications or questions become too complicated for chatbots to understand, a live chat system with a customer service representative is normally used instead.
For instance, the online casino company Betway makes use of live chat so that customers can get the answers they need from Betway’s customer service team without needing to navigate away from their online portal and in a more rapid fashion than would be expected from phone or email.
Pet insurance company Petplan, having recognized that 77% of all social logins still use Facebook, implanted a live chat feature directly into their Facebook page to facilitate faster engagement with their customers.
The numbers to support the benefits of live chat are also there, with data analysis company Keen reporting a 30% increase in customer satisfaction after adopting the Intercom live chat system.
The two systems can even be intertwined with chatbots automatically connecting to a live chat system when they don’t understand certain inputs, or AI programs, combined with NLP, monitoring the responses of customer service operatives and suggesting possible responses.
In fact, in order to stop cheaters, provide the best customer service, and make gambling, both on and offline, as fair as possible, casinos now employ a range of cutting edge technology.
In order to stop gangs of cheaters working together, casinos have also invested in non-obvious relationship awareness, or NORA, software. NORA works by analyzing a huge range of available data to identify potential relationships between groups who are trying hard to make it seem like they don’t know each other.
For example, one particular group of criminals, which included a casino employee, was identified by NORA because the employee listed another suspect on a car-loan application that he had also given to the casino so they could confirm his employment there.
NORA is so effective that a version of the technology is being developed for use by the U.S. Department of Homeland Security.
The same facial recognition technology being used to solve crimes is used to scan the casino floors for habitual cheaters by combining it with software that looks for inviting characteristics, like tattoos or distinctive facial hair.
The same image clarity advances used to increase the accuracy of facial recognition are also utilized to take some of the most amazing pictures of our planet from outer space.
The development of better camera lens technology and higher quality digital imaging can also be combined with AI to produce more accurate images of everything from the bottom of the sea to volcanic lightning.
The technology allows photographers to take thousands of images and uses an AI program to sort through them and blend them to create an astonishing effect.
While there are certainly those that still have their reservations about the role that AI has to play in combination with surveillance, what cannot be denied is that it represents a shift in the way we approach the use of security cameras and its applications in other sectors are just as revolutionary. There’s still some time necessary to fully grasp the long term implications of these changes, but it’s certainly a fascinating area that both technologists and artists should explore.
