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Advantages of Using Artificial Intelligence in
Video Surveillance

Advantages of Using Artificial Intelligence in Video Surveillance

AI video analytics has gained immense popularity over the past couple of years due to a large number of real world use cases. Despite being in its nascent stages, this technology has received wide acceptance which is evident by its massive growth. According to a recent projection, the AI video analytics market is set to grow into a $22 billion industry by 2027.

Nevertheless, business leaders must be extremely cautious while choosing an AI solution to protect their place of business. Currently, the physical security industry is exploding with video surveillance tools and applications.

We know how overwhelming this can be and to make that convenient we shall now discuss the actual advantages of using AI technologies such as face recognition, object detection, and intrusion detection from a security perspective. As we discuss each advantage, we shall analyze its efficacy in real-world scenarios.

Real-time threat detection

Video surveillance has long since been criticized as a reactive technology, only useful for forensic review after an incident had already occurred and was deemed unsuitable for real-time threat detection. Back in the days, security teams had to rely on external security cues and plan further measures accordingly. This involved manually monitoring cameras after being informed of a potential attack which in most cases was futile.

Contemporary video surveillance makes use of AI video analytics and is capable of detecting and reporting anomalies within a fraction of a second, thus making it a proactive security system. This is important for public places with heavy footfall and large campuses such as airports, retail outlets and tourist hotspots. These places have hundreds of cameras, so non-AI video surveillance would be impractical. People are prone to fatigue which inevitably results in a decline in productivity and response time and increases the possibility of human error.

In an airport, there are many ways in which AI video surveillance can make operations smoother. These include parking supervision, monitoring entry points, tracing lost or misplaced luggage, streamlining runway operations, enforcing social distancing and thermal screening. You can check out how Scylla AI video analytics was deployed for Oman International Airport to see how artificial intelligence can be leveraged during the pandemic for thermal screening and mitigation of risks.

Powerful Intrusion Detection Systems

According to the FBI, over 57.5% of burglaries involve forceful entry, 6.3% are forced entry attempts and 36.2% involve unlawful entrance into protected properties. Therefore, a powerful intrusion detection system is the first line of defense and an invaluable tool for any organization or individual. It is most effective when the detection response time is faster and there are negligible false positives.

Motion detection cameras used without AI video analytics are unintelligent devices that alert against everything that moves, be it an animal or even a shadow change. These cameras can raise anywhere between 100 to 150 false alerts per camera per day. This can be quite a burden for sites with hundreds of security cameras installed to monitor thousands of visitors.

On average there is one camera for every four people in the US. This gives a perspective on the overwhelming amount of video data from a supermarket or an airport with hundreds of security cameras. Moreover, the PTZ cameras which are commonly installed at such places require the right AI solution as not all solutions can handle a moving image. Scylla Intrusion Detection technology can fill this void as it is fully capable of being integrated with PTZ cameras and can also analyze the feed in real-time.

Scylla Intrusion Detection System can solve this issue by creating an intelligent surveillance infrastructure that works exceptionally fast with a response time of under one second. As it is trained on a comprehensive dataset, Scylla is capable of identifying specific humans and objects, drastically reducing false positives by 99.95%.

If an intrusion is detected, Scylla sends essential visuals and metadata to the security unit which enables them to take prompt action. It can also be configured with access management tools to lock certain parts of the premises in case intrusion is detected. In the case of banks, it can be configured to lock the bank vaults and other zones. On the other hand, schools and colleges can also use it to automatically seal classrooms if an intruder or gunman is detected. With Scylla object tracking technology, the gunman can be tracked on campus real-time even after the weapon has been hidden.

Artificial intelligence in video surveillance

Smart Object Detection

Traditional computer vision solutions were challenged in identifying objects such as weapons in the real world.

Scylla Object Detection system comes with an innovative neural network that takes into consideration all of these aspects before reporting an incident which brings down the rate of false alarms to below 1%. Furthermore, it can be used to detect both visible and concealed weapons by integrating with the appropriate hardware infrastructure.

To identify concealed weapons, Scylla must be attached to the X-Ray or the millimeter-wave scanning machine while the CCTV and drones are adequate to detect visible weapons.

Loss Prevention

In 2019, over 73% of property crimes in the US included some form of larceny and that led to a total loss of over $5.9 billion. Of those larceny crimes, over 22% included shoplifting and thus summed up to about $1.3 billion in reported losses.

According to yet another study reportedly issued by the National Retail Federation Survey, US retailers lose over $50 million US Dollars annually due to theft and shoplifting accounts for about 36% of that. This menace can be curbed with Scylla’s Retail Suite, which is a comprehensive AI video analytics solution that’s designed for retailers. Its proactive loss prevention mechanism helps detect suspicious behavior that may result in shoplifting.

Scylla is a next-gen AI Video Surveillance solution that not only allows enforcement of loss prevention measures but can also provide heat maps for smarter consumer behavior analytics. It allows retailers to get actionable customer insights and use them to predict product demand, estimate the effectiveness of store performance and take action to optimize operations and improve profitability.

One strategy is to use in-store traffic analytics to identify areas where people spend the most time. This helps understand popular locations and products and use this data to optimize product placement, for example, by putting higher profit margin items where people focus their time. Besides, heatmaps for foot traffic can assist with layout optimization and staffing decisions - such as increasing the number of employees at peak times. This can minimize waiting times in queues and ultimately enhance the customer experience.

With smart software, it is easier to understand trends and assess the effectiveness of marketing efforts. AI analytics can generate insights based on demographic traits such as gender, age, customers’ interests and habits. With all these data, it is easier to meet customers’ needs and provide them with more relevant and personalized product recommendations.

Collected statistics can also help identify vulnerable spots in the store where most shoplifting cases occur and improve security efforts there for effective loss prevention.

Finally, it aids in enforcing social distancing measures such as wearing masks and maintaining a reasonable social distance. None of that is possible through cameras not powered by AI analytics unless a large team of security personnel is deployed to check real-time video streams, which is costly and impractical.

Quick Data Extraction

Reactive security measures such as looking through video footage to get more information about events forensically might seem easy but without AI video analytics, it can be extremely difficult and time-consuming. Security personnel working at large campuses and business premises like airports, universities, hypermarkets and other similar places would agree with this.

After all, such places have hundreds of cameras installed and each camera runs 24/7, accumulating an enormous amount of video footage, making searching this data time consuming and costly. Nonetheless, it is essential for investigations and law enforcement officers, and that’s when AI video analytics can be of great use.

Contemporary AI-based video surveillance systems enable the user to search for a specific action or object in all the footage much faster than a human operator. Engaging AI in forensic analysis drastically reduces the amount of time that goes into extracting insightful data to investigate issues.

Final Takeaway

We have discussed some of the key advantages of using AI-powered video surveillance as part of your security infrastructure. These are designed to keep your business premises safe by preventing loss caused due to shoplifting, intrusion, robbery, and other types of high-impact events. This is achieved through a series of algorithms that are programmed to work in tandem with existing cameras and video management systems, to create a truly intelligent and proactive surveillance system.

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