We live in a world where threats appear every day; it can be a person sneaking into a premises without permission or an unusual object left unattended at a crowded place. To deal with such threats, we cannot rely on an outdated security system. Although legacy surveillance systems do work, they do not react as soon as an incident occurs. The reason they are considered outdated is because of their passive approach. To turn this passive approach into a proactive one, AI video analytics comes into play.
AI video analytics is the new-day surveillance system that triggers alerts in real-time. It utilizes computer vision, machine learning, and real-time processing engines. These help it differentiate between usual and unusual activities and objects and notify accordingly.
Want to know how AI video analytics detects threats in real time? Read this blog and discover everything from market trends and working mechanisms to real-world use cases and benefits of AI video analytics.
Market Stats on AI Video Analytics
- By 2035, it is anticipated to have grown from USD 10,559.7 million in 2025 to USD 56,689.4 million.
- The market for AI video analytics is anticipated to expand at a robust 18.3% CAGR from 2025 to 2035.
- Due to the substantial presence of industry leaders, North America dominated the global AI video analytics market with a 40% in 2024, as stated by Precedence Research.
What is AI Video Analytics
Similar to the traditional monitoring system, AI video analytics works by observing the video feeds. What makes it different is its proactive approach. Unlike the traditional system, it does not just act like a camera connected to a storage box. Surveillance cameras powered by AI video analytics are active throughout. They analyze the video in real-time, which the legacy system fails to do. Along with real-time video analysis, the system also detects anomalies and alerts the security personnel to initiate appropriate action.
An AI video surveillance system does not get tired of observing and analyzing, as the processes are automated. Not only does this make the system more efficient, but it also enhances accuracy. It utilizes a powerful blend of computer vision and machine learning that helps in differentiating anomalies from other activities and people.
How is AI-video Analytics Different from Traditional Video Surveillance
| Aspect | Traditional Video Surveillance | AI-Powered Video Analytics |
| Monitoring | Legacy video surveillance systems are monitored manually. | An AI-powered video surveillance system is automated and does not depend on human operators. |
| Response | The response is delayed if the threat is not spotted by the operator on the spot. | AI video analytics responds in real-time. |
| Scalability | The scalability of legacy monitoring systems is limited. | An AI video surveillance system offers easy scalability. |
| Detection | Does the job of capturing everything that happens. | Does not just capture, but detects faces, objects, and behavioural activities. |
| Accuracy | It may not be very accurate, as legacy video surveillance systems are prone to human error. | The accuracy of the AI video surveillance system is exceptional. |
| Cost | The cost of setting up is less, but maintaining requires human operators, which increases the overall cost. | AI video monitoring systems are cost-effective in the long run. |
Read More: AI Video Analytics in Retail: CCTV Security Solution
How Does AI Video Analytics Detect Threats in Real-time
The following steps explain the working mechanism of an AI video analytics for threat detection in real-time:
Step 1: Captures Video Feed with Smart Surveillance Cameras
In this stage, the smart CCTV surveillance cameras capture the video. The video feeds are then sent to either the server or the cloud, depending on the system. Real-time video feeds ensure that the camera captures every incident without any interruption.
Step 2: AI Monitors the Feed Continuously
The AI video analytics system continuously monitors the video fed into the system. The system is powered by artificial intelligence, so it is automated and does not depend on human operators. It does not lose focus or get tired, ensuring that the monitoring process is never compromised.
Step 3: Object Detection
A real-time video analytics system detects the elements in the footage while monitoring. It utilizes its trained models to differentiate between usual and unusual objects. This helps the system be proactive instead of reactive and detect accurately in real-time.
Step 4: Behaviour Analysis and Threat Detection
Apart from detecting objects, AI video surveillance also analyzes behaviour in real-time. The system does not react to the normal behaviour or activities like staff entering the premises. It flags unusual activities like a fight breaking out.
Step 5: Notifies and Alerts
A real-time threat-detecting video system does not just flag an activity, object, or person as a threat. It goes beyond simple detection by notifying the security personnel in real-time. In case of emergencies, it can even trigger safety alerts and actions along with notifications and alerts.
Step 6: Continuous Data Storing and Improvement
The intelligent video surveillance system not only monitors and detects, but also stores the data throughout its operation. It manages every footage and stores it for future reporting and investigation. Over time, the system gets improved with continuous threat detection, refinements, and updates. It can even provide smart insights based on the activities it records.
Benefits of an AI Video Analytics System for Threat Detection
A video analytics system powered by artificial intelligence comes with the following benefits:
Rapid Response
With the help of real-time threat detection, an AI video analytics system enables rapid responses. It reduces the time spent on manually going through every footage to identify the threat. The video surveillance system automatically detects threats and immediately alerts the security personnel to take the required action promptly.
Eliminates Human Error
An intelligent video surveillance system is powered by artificial intelligence that automates the task of monitoring. Since the system does not require human operators to manually observe, the chances of missing any incident are reduced to null. Automation makes the system free of human error.
Enables Proactive Actions
Video analytics powered by AI stores the recorded footage for future reference. But it is not solely used for references; the system analyzes the patterns in the footage collected throughout to provide insights. These insights can help the business know the red and green points and make decisions accordingly.
Uninterrupted Monitoring
Now that you already know that AI video analytics for threat detection is free of human dependency, it is clear that it does not get tired or bored while monitoring. This means that the monitoring is uninterrupted and overlooks nothing. It can monitor 24/7 without needing breaks or being distracted.
Enhanced Efficiency
Real-time threat detecting video analytics system is not just effective, but also efficient. It is operationally efficient as it does not require a lot of staff to work on different shifts to monitor the environment. It brings cost efficiency as it detects threats and maintenance needs early, preventing damage to property and downtime.
Scalability and Adaptability
AI video analytics are built in a way to adapt to your organization’s growth and scaling needs. The system can be scaled across departments and networks without needing to set up new ones at every location. The server allows scalability. For adaptability, the system can easily work in different environments, be it a manufacturing unit or an airport.
Read More: AI-Powered Video Analytics for Public Sector
How Different Industries Use AI Video Analytics for Real-Time Threat Detection
Curious about how real-time threat detection with AI video analytics works in different industries? Read these industry use cases and find out:
Retail Industry
In the retail industry, AI video analytics for threat detection helps in identifying suspicious activities. It flags unusual behaviour like loitering or theft and alerts when someone tries to access restricted or staff-only areas. It keeps a track of customer movements and deploys security when needed.
Healthcare Industry
In the healthcare industry, patient safety plays a very important role. AI video analytics empowers healthcare professionals to monitor patients 24/7 and provides the required medical assistance promptly. It helps in protecting restricted areas like medicine storage, the ICU, etc. AI video surveillance helps protect both the patients as well as the premises.
Manufacturing Industry
The manufacturing industry utilizes heavy tools and machinery. In an environment like this, AI video analytics helps in ensuring safety compliance. It checks if workers are wearing the required safety gear and alerts in case of its absence. Real-time detection helps in restricting unauthorized people from entering hazardous areas and keeps a track of machinery behaviour too.
Education Industry
AI video analytics, when applied to the education field, helps in detecting fights and violent behaviour of students. With the help of real-time threat detection, it identifies intruders and sends an alert to the security personnel to take action thereafter. Apart from this, AI video surveillance helps in managing crowds during events.
Logistics Industry
In industries like logistics, monitoring is crucial as the goods stored and moved are high-value. The complex workflows are supervised with the help of intelligent video surveillance. The real-time threat detection helps in preventing unauthorized access, ensuring package safety, and tracking activities.
Banking and Financial Institutions
AI video analytics helps banking and financial institutions by detecting abnormal behaviour. It helps enhance the security of banks to prevent theft, tampering, and robbery. Video analytics facilitates 24/7 monitoring and real-time threat detection, ensuring safety during cash transfers.
Similar Read: Developing Queue Detection AI Systems for High Traffic Scores
How Quytech Helps You Build Smart AI Video Analytics Systems
With over 14 years of industry experience and deep market exposure, Quytech excels in building cutting-edge AI video analytics solutions. Our team of dedicated and capable developers brings in the best technology and industry knowledge to build real-time threat detection solutions.
We emphasize creating customized and scalable solutions that not just meet but exceed your expectations. With scalability and adaptability at its core, Quytech’s AI video analytics solutions are made to grow with your business.
Conclusion
As traditional systems fail to keep up with the rising demands for better security, AI video analytics for threat detection comes to the rescue. With enhanced security, real-time threat detection, a proactive approach, and uninterrupted monitoring, AI video analytics is giving the security system a much-needed makeover.
As different industries begin to adapt to AI video analytics, the change does not reflect the future, but the current safety demands. Adopting video analytics isn’t just about upgrading security; it’s a step toward embracing a more futuristic, intelligence-driven approach.
FAQs
No, AI video analytics does not replace security staff. Instead, it supports them. This system helps in allocating the staff to security tasks other than monitoring.
Yes, when integrated in infrared or night-vision surveillance cameras, the AI video analytics system can work during the night or in low-light conditions as well.
When you collaborate with reliable partners or hire top 1% AI developers, they ensure that your AI video analytics system follows data security regulations.
Not necessarily, AI video analytics can also be integrated with existing surveillance cameras. But for best results, upgrading to AI-compatible cameras is often recommended.
