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Artificial Intelligence For Video Surveillance
There’s no denying that video surveillance technology has come a long way over the years. From grainy videos in its early stages to the quality software and clarity today, video surveillance continues to make great strides and advancements.
History
The goal of security cameras and surveillance systems is to capture, detect, and deter any unlawful behavior in and around homes, businesses, and public areas. Before, installing a security camera system was a costly and laborious job, involving lots of wires and cables running throughout the building. As technology progressed, security cameras became more accessible and affordable, allowing more users the opportunity to invest in their security. Now there are numerous DIY solutions that make it easy for homeowners to install and set up on their own security systems.
For businesses, implementing a team of people to actively monitor security cameras at all times was once the only option. Now, much of the monitoring aspect of security and surveillance systems can be automated. Rather than having the mundane task of watching numerous monitors, security cameras now have the ability to detect any suspicious or abnormal behaviors and will alert a security officer as necessary.
While we have seen the security industry flourish over the years, this is just the tip of the iceberg. Our technology will continue to advance and amaze us in ways we never thought possible.
Artificial Intelligence
Artificial intelligence (AI) in video surveillance enables the “smart” features we now see with security cameras. In general, security cameras enable us to monitor situations in real-time or go back to review previous footage. With the integration of AI technology, not only can we monitor in real-time, but potential issues can be identified before they become real problems.
With the emergence of video analytics, footage can be analyzed immediately to identify any abnormal activity or threats early on. This technology helps the software ‘learn’ what is normal in order to identify unusual behavior and is meant to make up for human error, rather than replace human monitoring all together.
While it was always a goal to integrate AI and video surveillance, the technology, from a hardware standpoint, was not ready. One of the issues that needed to be addressed was decreasing the power demand to a level low enough that would allow the technology to be embedded into the cameras.
As more cameras emerge with new AI technologies and processes, we will begin to see more advanced features including crowd density monitoring, facial recognition, stereoscopic vision, and behavior analysis.
Behavior analysis in particular is what a lot of tech companies are focusing on. By implementing a technology that can identify and recognize precursor patterns associated with crimes and other bad behavior, we may be able to greatly improve public safety and security.
A great example comes from the West Japan Railway, where it was found that 60% of people hit by trains in Japan were intoxicated. They have now installed security cameras that can automatically search for and detect signs of intoxication. Sleeping on benches, stumbling, falling, or standing motionless for long periods of time are behaviors that are recognized by the AI system. Human attendees are then notified and sent to check on the person.
Of course, a conversation about video surveillance always includes concerns about privacy. No one wants to feel like they are constantly being monitored, but developers insist that these systems know when to stop collecting information and monitoring. As these technologies continue to develop, you may soon be able to “teach” your system when to record and in which situations recording should halt.
Although it is still in its early stages, AI technology and video surveillance is heading in a positive and exciting direction. Mass adoption may still be a ways to go, but it’s great to see AI being applied in a new setting.
What are your thoughts on artificial intelligence and the video surveillance industry? Share with us on Facebook, Google+, Twitter, LinkedIn, and Pinterest. Browse our selection of security cameras and equipment online at SecurityCamExpert.com. To learn more about our installation services or to request a free quote, please call 888-203-6294.
Improving Cyber Security With Artificial Intelligence
The use of artificial intelligence in security systems provides more flexibility, especially with new cyber threats always emerging. Namely, machine learning has garnered much attention for its involvement and improvement of security systems.
Most people use the term “artificial intelligence” loosely these days, but it traditionally refers to the theory and development of computer systems that may perform human tasks. Machine learning is a type of AI that allows a computer to learn, grow, and change when presented with new data.
The evolution of AI can be best described in three stages. First is the basic expert system. If we used this system to help distinguish between a dog and a cat, for example, it would use a single feature such as number of teeth to make the decision. Second is the probability-based system, which evaluates different factors (ex. number of teeth, weight, size) to determine the probability (expressed as a percentage) of the object being a cat or dog. Lastly is deep learning, which uses seemingly endless amounts of labeled samples to differentiate between cats and dogs.
If we applied these to antivirus systems, you could understand how a basic expert system would be weak and need constant updating for new threats. The probability-based system would be a bit stronger, however, only so many features would prove relevant resulting in disregarded data. Deep learning seems the most promising, and a startup called Deep Instinct is looking to develop this approach for cyber security.
Within the Deep Instinct laboratory, the deep learning system is trained on all the known samples of malware, which takes about a day to complete. The process requires heavy-duty graphical processing units to analyze the data, and the end result is a trained system about a gigabyte in size. It is then reduced to about 20 megabytes and can be installed on any endpoint device (including mobile). It works to analyze any incoming threats within a few milliseconds to keep your devices safe.
To keep the system up -to-date, new malware samples are added every few months, and updates are automatically sent to the end point devices. But even if the system is not updated for months, the small brains within the end point devices remain vigilant and can detect new files. The success rate is promising and deep learning systems will likely gain more popularity over time.
While deep learning systems are great for detecting threats, they are not the best for explaining how they did it. Eureqa is a proprietary AI engine from Nutonian whose main job is to find out why things happen. It has proven very valuable for researchers and journal publications, but it also plays a role in cyber security by helping to determine the anatomy of a cyber attack.
Still, cyber security can be a tricky mess. Constant updates are necessary thanks to appearance of new threats and attacks daily. Even though you are employing security systems to protect your data, there are still vulnerabilities between updates. And during that time, hackers can use the security software to test their attacks until something breaks through, leaving numerous customers at risk.
Tailoring your cyber security approaches can help to combat this. For example, Masergy Communications is a managed networking company which uses a combination of both local and global factors to predict and prevent cyber security issues or attacks. The unique local indicators help to improve accuracy.
Acuity Solutions offers the BluVector appliance which uses machine learning for cyber threats, and also uses a local and global approach. The pre-trained engine learns what a benign code looks like, receives updates based on global data, but also engages in new learning based on the individual customer. While the global data is shared, the customer-specific data is not, creating a more unique and secure experience.
As discussed, artificial intelligence and machine learning can greatly benefit different aspects of cyber security. What are your predictions on the future of AI in security solutions? Share with us on Facebook, Google+, Twitter, LinkedIn, and Pinterest!
For a wide range of security cameras and surveillance equipment, please visit SecurityCamExpert.com. To speak with a representative or request a site survey, please call 1-888-203-6294.