AI analytics leverages the current capabilities of artificial intelligence and machine learning technology to monitor and report on the behavior of people and objects captured on video footage. The application of these analytics can improve security by providing better situational awareness, identifying potential threats, and alerting security personnel to potential risks.
AI analytics can be viewed as the result of automating data analysis, an activity that was formerly labor-intensive and time-consuming. Utilizing AI analytics methods such as natural language processing (NLP), speech analytics transcription, and computer vision for image and video analytics, it was able to analyze unstructured data.
Video Analytics Today
Video analytics utilizes artificial intelligence and aims to fulfill specific tasks by applying computer vision and deep learning to video recordings or live video streams. This analytics technique is gaining rapid popularity, as it has been adopted by a number of tech businesses desiring to leverage the latest AI technology as well as companies that have already operated video surveillance systems prior to the development of AI and are now interested in using it to enhance their security.
In 2022, the video analytics industry has such a huge impact on data-keeping and security in businesses that it is even projected to be worth $19.3 billion dollars in 2029. Experts say from the same report that the video systems industry will continually grow as more and more companies are focusing on convenient avenues of monitoring their workforce as well as improving the security of their important data against any kind of security breach. Here is how video analytics manage to do so.
What is Video Analytics?
Essentially, video analytics is a software tool that analyzes hours of video footage and notifies employees when an important event occurs. Using a combination of AI, deep learning, and data analytics, video analytics processes video footage.
The analytics software is available in three varieties:
- Camera inside
- Third-party software
Video analytics software establishes a connection with each camera and begins data processing using edge analytics. Processing data involves removing unimportant portions of the video feed and providing only pertinent footage to the central system.
But how does an analytics system determine what is significant and what is not? Using statistical algorithms and deep learning, the analytics software differentiates between a typical and an odd incident, and then sends the normal footage to a central server to be alerted to its own company security personnel.
In the central system, powerful analytics will analyze the footage to ensure that only the most crucial images are displayed on security monitors. Some sophisticated systems can use the camera as Internet of Things (IoT) sensors and do metadata analysis to provide extra information. Once the analysis has been completed, the uninteresting film is filtered away, leaving only the significant incidences on the security guard’s tape.
Security Protection: How It Works in Real-Time
Video analytics generates considerable excitement in the surveillance market because of its security-enhancing capabilities. Using video surveillance cameras, video analytics through motion detection may determine if an individual breaches a virtual barrier. After detection, an immediate alert is given to security personnel.
With the aid of video analytics, the security teams may also establish no-movement zones using motion detection. The zones can be of any size or shape, and if someone enters one, cameras will quickly alert security. Security cameras are also able to scan an individual’s face and compare it to a list of public and private databases.
Video analytics can also measure the number of people in a specific region, which is particularly valuable in huge venues such as sports arenas. If there is a high measure of foot traffic in a particular area, the system will notify security staff so they can manage the issue.
Safety and Security of Data
Compliance-related concerns may have a substantial impact on operations, depending on the industry, if they are not properly prepared for and addressed. Companies are always on the lookout for security inside jobs especially the dispersal of crucial company information is deemed a grave offense.
There are industries, however, that need utmost security not only in their sensitive data but also in monitoring suspicious fraudulent activity that can arise in potential financial threats. One example of this is in casinos. For instance, it is crucial for these businesses to know if an employee is leaking important information or if a customer is engaging in potential money laundering concerns.
In the healthcare industry, whenever a facility or organization holds protected health information (PHI) whether physically or digitally, they must ensure that the data is secure and confidential so that only authorized employees may access it. This may even involve replacing traditional passwords on computers with facial recognition-based access and encrypted file contents. Physically, it may involve installing privacy screens on monitors, access control on doors to sensitive files, and surveillance cameras across a facility to record access to areas containing PHI.
The face recognition technology that merges clear surveillance footage with transaction data and extremely accurate analytics can also aid in the detection of identity fraud in the banking sector. Video can be used to identify VIP clients and high-value transactions, which can then be subjected to further analysis.
Through facial recognition systems, video analytics companies enable the option to blur the faces of bystanders who have not opted into face-scanning during video playback. It is also best to avoid redundant data acquisition. It is to the best of the company’s faith whether to opt or not to record the faces of non-watchlist members.
Once this option is activated, photographs of non-enrolled individuals’ faces will no longer be displayed in the gallery or saved on the server. Clients can then minimize unnecessary compliance risk and only record and process detections of individuals on a company’s watchlist.
Spotting Suspicious Behavior through Motion Detection
Video surveillance with cognitive data analytics can identify persons of interest (POIs) in real-time using live facial recognition, allowing your security personnel to swiftly respond to threats while respecting bystanders’ privacy.
VIPs to whom businesses would like to provide a superior customer experience, known felons, shoplifters, and dangerous criminals are all examples of persons of interest. Knowing who is on and in close proximity to your property, especially in retail stores, at all times enables a quicker, more accurate, and more suitable reaction. Without video analytics solutions, most software that automates the identification of individuals on watchlists performs poorly under real-world settings.
This is due to a number of reasons: images are often of low quality, occluded, or taken at an angle; the person’s appearance may have changed since being added to the watchlist; there may be more than one person in the frame; and, most importantly, processing video in real-time is computationally demanding.
In many cases, it is only through advanced video analytics that individuals on a watchlist can be accurately identified. This technology can detect, track, and recognize people in real-time, even if they are partially obscured, at different angles, or in a group. Neural networks have been battle-tested by the most demanding users and academic standards to assure the highest accuracy even when the POI is not looking at the camera, is in a crowd or was shot under less-than-ideal settings.
Now, automated POI alerting enables users to identify POIs and the individuals they’ve interacted with in real-time through face and attribute recognition. In addition, the same technology in video analytics works for analyzing live video feeds to identify crowd density, loitering, and other types of risks.
Examples of Video Surveillance Systems in Tracking Sensitive Workflow Processes
There are industries wherein a keen look at how their standard processes are done should be monitored in real-time, 24/7 through special surveillance systems. Some examples are:
Regarding hospital safety and security, video analytics software can detect when a person has fallen and can automatically summon help. It can also be used to monitor medical equipment and medication to prevent theft, and to make sure that staff members are washing their hands and wearing protective gear. The ability to detect real-time video surveillance for object recognition and personal real-time alerts improves overall hospital operations.
Advanced video analytics based on artificial intelligence may also track assets, monitor building landscapes, even monitor behavior patterns and equipment in the room and activate loitering detection, all while keeping HIPAA compliance and respecting personal privacy.
Even though hospitals may be surrounded by numerous security personnel, cameras, and monitors, it is difficult for people to maintain an accurate reading across multiple monitors over a particular time period. However, with AI Vision, you can receive real-time alerts when a person of interest enters the hospital, wanders into an off-limits area, or attempts to leave with restricted items. Even better, videos powered by AI can also assist hospital visitors.
Facial recognition technology might also be used to flag and follow personnel for secondary screening, such as detecting someone with a high temperature, surgical gear, and other protective personal equipment, or detecting someone without a face mask.
Moreover, video recognition technology can also be utilized for situational awareness, such as the monitoring of patients falling out of bed, visitor logs, and precise equipment readings.
Staffing and Logistics
Another important example of how video analytics can be used to improve security is in the staffing and logistics industry. This is particularly important for package handling and distribution centers.
In these cases, video analytics can be used to track inventory levels and movement, as well as to monitor employee productivity. The technology can also protect workers who are surrounded by forklifts and other moving equipment. In the majority of cases, accidents are the result of negligence, human mistake, faulty machine operation, and staff who do not adhere to safety requirements.
Smart camera solutions work as efficient security system surveillance in such a way that it can monitor employee behavior and compliance with safety protocols. The technology can be used to create a virtual tripwire that will send an alert if someone crosses into a restricted area or attempts to remove an item from the premises. Smart camera technologies are also useful for object recognition. In this event, the company itself can use traffic light control systems to create a virtual stop sign that can aid in preventing an accident from occurring.
Real-time video analytics systems for the security industry have become progressively more reliable, accurate, and affordable. The benefits of installing such a system are many and video analytics should now be considered an essential part of any comprehensive security solution.
Cameras are constantly becoming more sophisticated, with the ability to not only record high-quality video but also to detect and recognize objects and people. This means that they can be used for much more than just security.
Video analytics can be used to protect important data, monitor employee productivity, and even improve hospital operations. The technology is constantly evolving and becoming more sophisticated, which means that the potential uses for video analytics are only going to increase.