Modern security operations essentially rely heavily on the data that the security devices record. However, it is still a challenge for security operators to go through large volumes of recorded videos for security assurance. Also, the limited human attention span can pose a challenge in going through the video surveillance data effectively. So, how to address this problem?
Considering the upsurge in smart devices and the corresponding technologies, all the gadgets are getting smarter, and cameras are no exception. A large number of cameras are already connected to Wi-Fi networks and can easily work along with other connected devices. Cameras, however, do not often come with intelligence built-in. Despite being a part of a large-scale security and surveillance system, most cameras were not equipped with artificial intelligence capabilities, at least until now.
Artificial intelligence can be harnessed to radically increase the efficacy of the surveillance systems by driving human attention towards things that can compromise the security by sending them real-time alerts.
Intelligent video surveillance can be developed to detect events or objects of interest. Let’s explore how artificial intelligence can redefine security and surveillance for enterprises:
Better attention span than humans
If we think about all the information that our eyes capture in a minute, it is zettabytes of information, if not more. The human brain has evolved to pay attention to certain types of activity while ignoring the details that seem irrelevant to us. In addition, we have varying attention spans and attentiveness dips when the focus is on the same type of monotonous activity. Security operators who are tasked to monitor video footages round the clock might miss some of the unusual activities as their attention span keeps fluctuating.
On the other hand, AI can be trained to observe every detail and notify the operator in case of any unusual activity found on the video feed. It can be trained to learn what typical activities in a scenario look like and detect incidents, behavior, or actions that do not follow the usual pattern. And, of course, AI can continue to function at a high level of efficiency round the clock, unaffected by mental or physical fatigue.
Object, facial, and event recognition
Even when a business has recorded extensive video footage, identifying specific events or people during or after an incident is difficult. With artificial intelligence capabilities, facial recognition as well as object and event recognition becomes much easier, which makes it possible to deliver real-time and proactive security.
For some businesses, artificial intelligence can also be applied to identify physical characteristics of the customers, which can be referred to as ‘faceless recognition’. In this type of recognition, a person’s height, build, gender, clothes, and posture are used to identify them in a crowd. Additionally, a person’s activity patterns can also be used to identify them.
Remote asset management
Plenty of business assets are located at remote locations or away from the industrial facility. These remote assets need monitoring in order to confirm that they are functioning as expected and to minimize sudden breakdowns and downtime. Video analytics can identify if assets are not optimally utilized or need maintenance without requiring the operators to check them in-person at regular intervals.
The ultimate goal of remote asset monitoring or management is to get maximum return on assets (ROA), which can be made possible using artificial intelligence for video analytics. Ideal machine conditions and performance metrics can be fed into the AI system to analyze the machine behavior patterns. This can be used to predict machine performance, and alert operators when to expect machine failures. Predictive analytics can save big bucks by reducing machine downtime, which is the key to have an uninterrupted production process.
Image processing for better analytics
Surveillance cameras do provide the facility of capturing high-resolution images and videos, yet most of the systems do not use it for video surveillance. Therefore, most of the images or video clips captured and analyzed by the operators are of low quality. This issue can prevent operators from delivering accurate analysis reports and increase the chances of missed incidents.
In such a case, image processing can be used to sharpen the low-quality images and video clips to make it easier to derive meaningful data from them. Operators can easily analyze the improved images, thereby reducing the scope of undesirable incidents.
Utilization of data deluge
As we all know, large portions of urban areas and public spaces are under video surveillance, with the cameras collecting a large amount of data every day. This is true for most of the parts of the developed economies. The intention behind collecting such data is to create a smart city that delivers higher convenience, better security, and improved energy management to the public. While a massive amount of data is collected, it is often not utilized to its full potential because of the legacy systems.
In order to derive valuable insights from this surveillance data, specialized software that works on state-of-the-art technologies can be used to analyze big data and generate security alerts. The derived insights can be of great use for security operators, who can then take required actions to protect people as well as important assets.
Wrapping Up
eInfochips has remained a strategic partner for various leading businesses in the video surveillance, analytics, identity management, biometric security, and public safety domains. With a strong set of IPs that helps us accelerate the product development lifecycle, we have delivered applications for retail, transportation and city surveillance, including applications for military, airports, commercial, residential, public transit, and government establishments. If you wish to develop an AI-powered video surveillance solution to help with your business operations, get in touch with us.
