Understanding video analytics: applications and benefits

What is video analytics?

Video analytics is an advanced technology that automatically analyzes content captured by video cameras. Intelligent algorithms process video data in real-time to generate information about what’s happening in a series of images. Video analytics for security is commonly used to detect and gain insights into the motion of objects, people and vehicles in CCTV footage.

Video analytics surveillance systems offer a more practical and effective way to review and observe security footage. Content captured by multiple cameras over several days can be automatically sorted by matters of interest, supporting security personnel in identifying and appropriately responding to suspicious activities in real-time and during investigations.

How do video analytics systems work?

Video analytics systems process video feeds using algorithms designed to detect specific stimuli. Captured images are reviewed in sequence by dedicated software tools that are programmed to check for certain events or objects that could represent a security threat.

In a basic sense, video analytics searches for anomalous differences in a sequence of images and then generates insights into these events using rule-based algorithms. For example, if a video camera captures an object moving through its field of view, video analytics will ask questions to help define the object and decide whether its presence merits further action.

Under the umbrella of video analytics, there are two main types of systems to understand:

• Traditional video analytics: Basic systems use rule-based algorithms to analyze video content. If something in a series of images changes, the software will ask a series of if-then questions to narrow down what it might be. However, traditional analytics systems can’t retain information or learn from previously recorded incidents.
• AI-based video analytics: AI-based video analytics also use a rule-based process to gain image insights. However, their algorithms use AI and machine learning tools to help them learn from wider data. In simple terms, deep learning in video analytics enables systems to learn patterns from historical events to improve detection accuracy.

Common types of video analytics in CCTV

Real-time video analytics enable security teams to identify patterns, anomalous events and suspicious activities that may otherwise go unnoticed. Video analytics cameras ensure key areas are always observed, with different video analytics algorithms specially designed to search for specific stimuli. Below are some common types of analytics.

Automatic License Plate Recognition (ALPR)

ALPR cameras use a special type of video analytics called Optical Character Recognition (OCR) to read license plate information on passing vehicles. ALPR technology can be used to support parking management and vehicular access control operations, as well as observe access roads and parking areas to highlight the presence of suspicious vehicles.

Crowd detection

Video analytics algorithms used for crowd detection are programmed to identify humans and measure the density of crowds in a camera’s field of view. Crowd detection analytics is used to improve safety at live events, alerting teams to potential bottlenecks and disturbances that might require further attention, as well as to track occupancy levels and spot unusual activity.

Facial recognition

Facial recognition is used to identify the presence of human faces in video content, as well as compare faces to those stored in databases. This type of video analytics can control access to secure locations and improve perimeter security by alerting teams to the presence of known offenders and unauthorized persons loitering around private properties.

People counting

People tracking systems analyze multiple types of biometric indicators to better understand the actions of humans in target areas. Through facial recognition, motion detection and behavioral characteristics, these systems can identify individuals and follow them through facilities to improve intrusion detection and occupancy management practices.

Object tracking

Object tracking video analytics monitor the presence and movement of specific items in a camera’s field of view. Algorithms can be adjusted to suit various video analytics use cases. For example, cameras may be programmed to monitor packages as they travel through shipping and fulfillment facilities or used to track cars in support of traffic control operations.

Motion detection

Video analytics algorithms optimized for motion detection are programmed to continuously search a predefined area for signs of movement. Surveillance video analytics with machine learning are commonly used for this purpose. Systems can be trained to understand how spaces are used under normal conditions, so they only alert security staff of motion likely to be of issue.

Unattended item detection

Video analytics systems can be programmed to monitor the appearance and movement of static objects in a set location. These solutions are well-implemented in public spaces like shopping malls, entertainment venues and transport hubs to help security staff identify potential bombs and ensure emergency exits remain free from obstructions.

Occupancy monitoring

Occupancy monitoring tools count the number of people that pass through a predefined area over a set period of time. This technology can be used to ensure safe occupancy levels are maintained and to collect data about how spaces are used. For example, in retail businesses, it can be used to determine when services are most popular and to measure the efficacy of organizational plans.

Key industry applications of CCTV video analytics

Bespoke types and combinations of video analytics tools can be developed to meet various use cases across different industries. Business owners, professionals and security teams may use off-the-shelf systems to address common security and organizational management needs or invest in creating custom solutions to meet unique industry requirements.

Below are examples of real video analytics use cases and key industry applications.

Healthcare 

Video analytics solutions help healthcare professionals facilitate safe environments for patients and staff. Facial recognition systems can help staff identify persons who may have caused issues in the past. At the same time, hospital cameras with object detection can be configured to warn security teams of contraband items, and weapon detection capabilities can flag potential firearms.

Industry-specific video analytics systems can also be created. For example, programs may be trained to spot concerning movement patterns associated with falls and medical events, enabling staff to set up instant alert systems for vulnerable patients. Video analytics, such as object tracking technologies, can also help staff ensure medications are taken as prescribed.

Transportation

Video analytics cameras that cover roads and junctions are used to improve traffic management in some modern cities. AI video analytics can scan license plates to determine how many cars are on the road at any given time, and this data can be used to inform the operation of infrastructure like traffic lights and public transportation networks, helping ease congestion.

Traffic monitoring cameras imbued with video analytics can also be leveraged to improve road safety, with AI systems able to identify potentially dangerous incidents unfolding in real-time. Systems can detect cars stopping in unsafe areas, moving erratically or traveling in the wrong direction, with findings sent to relevant authorities promptly to enable swift and appropriate responses.

Retail 

Video analytics security systems support retailers in developing effective anti-theft measures and loss prevention strategies to help protect people and property. Facial recognition analytics with machine learning capabilities can be taught to identify known shoplifters automatically, as well as taught to spot patterns in behavior and suspicious movements that have been associated with previous theft incidents.

Retail video analytics can also be deployed to help retailers better understand customer habits. For example, systems can analyze how customers travel through a store to help managers determine the best locations for certain products. Sometimes, video analytics may be deployed to gather customer demographic data, which can be leveraged to influence marketing efforts. 

Smart cities

There are several video analytics use cases in smart cities, with bespoke systems used to improve everything from safety and security to infrastructural efficiencies. Video analytics cameras imbued with crowd detection, object tracking and occupancy monitoring features can be used to spot security risks, ease congestion and influence law enforcement patrols.

ALPR video analytics can also be leveraged to develop automated parking management systems, helping citizens with vehicles travel through smart cities more efficiently. Video analytics data may also be fed into wider systems like waste management and transport planning solutions to help management teams plan efficient routes and practical operations.

Construction

When paired with a video analytics system, construction site security cameras can monitor worker behavior, detect potential hazards, and ensure compliance with safety regulations in real time. It helps track equipment usage, monitor site progress and prevent theft or unauthorized access by recognizing unusual activities. Advanced algorithms can also analyze workflow patterns to optimize productivity and reduce downtime.

Manufacturing

Video analytics cameras installed to cover busy production lines can be trained to identify issues in manufacturing operations. AI software can spot anomalies in raw materials and saleable goods to help businesses improve quality control operations, as well as observe machinery and equipment continuously to help inform downtime and maintenance plans.

Staff safety initiatives can also be improved with support from video analytics. Manufacturing surveillance solutions can be trained to identify anonymous and potentially dangerous events, like staff using machines incorrectly or failing to wear protective equipment, enabling managers to respond to potential safety risks promptly and with accurate information to help limit the impacts of safety issues.

Pelco’s role in advanced video analytics

An integrated and comprehensive video analytics system can help bolster your on-site security and enhance peace of mind, especially when paired with appropriate security solutions that fit your unique business needs. With many different types of video analytics available, it is vital to choose a security solution that suits your specific industry and aligns with your security goals. 

Pelco’s advanced security cameras and bespoke video management systems (VMS) seamlessly integrate with intelligent video analytics and offer enhanced security and operational insights, helping streamline business operations and improve safety. From Elevate’s direct camera-to-cloud technology that combines edge and cloud AI to a diverse array of security devices, these video analytics help you detect and prioritize what is happening on your site so you can take action.

The benefits of video analytics technology

Choosing to develop and deploy bespoke video analytics solutions can provide businesses and security professionals with several significant advantages. With intelligent software used to efficiently manage and draw insights from vast amounts of data, human teams can improve the delivery of key tasks by automatically highlighting high-quality, relevant insights.

1. Improved efficiency

A typical security system will contain many IP cameras and monitors positioned to cover key areas. Even the slightest change to a security feed could signify an unfolding threat, but teams may struggle to effectively observe all cameras continuously. 

Video analytics security systems can be trained to automatically detect and warn operators of anomalous events, with insights sent to CCTV control room staff and on-site personnel via SMS or email. This helps ensure all suspicious activities are brought to the attention of relevant personnel, with high-quality records of events instantly generated to improve investigations. 

2. Enhanced decision-making

Alongside detecting anomalous events that may require further investigation, video analytics systems can discern what type of incident may unfold. Informed by key types of video analytics like object tracking and facial recognition tools, staff can be warned of the presence of firearms, unauthorized persons or crowds forming to support informed incident responses.

3. Reduced false alarms

While traditional security systems can be effective crime deterrents, operators or central monitoring stations must perform additional analyses to understand the reasons for activation. It’s estimated that 95% to 98% of triggered burglar, panic and robbery alarms are false positives, potentially leading to time and resource waste that could cause organizations to become vulnerable to wider risks.

As video analytics security systems are designed to identify and understand specific stimuli in the unique conditions of their specific environments, the risk of false alarms can be measurably reduced. This enables staff to respond to risks quickly and reduces time spent analyzing physical security data, so staff can focus on important tasks.

4. Potential cost savings

While the upfront costs of developing video analytics systems can be high, businesses implementing these tools can enjoy long-term cost savings. Primarily, the improved accuracy of video analytics security systems can help limit the financial impacts of events like theft and property damage, with further benefits found in organizational improvements.

Less time and fewer resources will be required to analyze, organize and act upon security data, allowing organizations to improve the efficiency of CCTV monitoring and investigative processes. Video analytics solutions may also be deployed to observe how employees and guests interact with physical assets and infrastructure, helping businesses improve services and meet client expectations.

5. Continuous improvements

The data collected and analyzed by video analytics tools can be leveraged to continuously improve wider aspects of a business’s operations. For example, video analytics in conjunction with AI cameras can help professionals understand the types of threats their organizations are most vulnerable to, influencing future decisions on improvements made to security systems and internal policies. 

Similar principles can be applied to other applications of video analytics. Systems deployed to observe manufacturing tasks can produce insights regarding production improvements. ALPR analytics can help teams improve parking management operations, and behavioral analytics can support customer experience improvements in retail and hospitality settings.

Considerations for implementing video analytics systems

Video analytics security and business management systems may only provide measurable benefits if adapted to suit an organization’s unique needs. When developing bespoke video analytics solutions, business owners should consider the following factors:

• Processing: Analytics software can process data in a central server or at the nearest device. Older cameras usually require server-based systems, which often suffer from latency when processing insights. In comparison, newer IP cameras can leverage edge analytics to process data and generate insights into the device itself in real-time.
• Detection accuracy: Video analytics with machine learning and AI features can be used to develop highly accurate systems. The software can be trained to understand the normal operating conditions of target areas and alert staff to anomalous events.
• Scalability: Security needs may change over time, so it’s vital to choose a solution that can be scaled as needed. Consider how easy and cost-effective it may be to add new hardware and video analytics software features to proposed installations.
• Integration possibilities: Insights generated by video analytics tools can be used to inform the operation of wider security systems. Check that desired solutions support open API configurations and are compatible with existing business security devices.

Future trends in video analytics

Growing interest in AI-informed technologies has led to increased adoption of AI across business sectors,with as many as 72% of organizations adopting AI to perform at least one business function since 2022. As AI and deep learning algorithms become increasingly advanced, more industries are poised to benefit from smart video analytics systems.

AI-informed video analytics are now commonplace in modern smart cities and smart building technology, with tools not only used to improve security but also boost energy efficiency, monitor the environment and help ensure infrastructure is properly maintained. Video analytics linked to the Industrial Internet of Things (IIoT) help professionals perform these tasks by enabling physical infrastructure to be adjusted autonomously in response to high-quality data insights.

Interest in emerging AI technologies like video analytics also stretches to smaller businesses and applications, with research published in 2024 finding that 98% of small businesses now use AI-enabled tools. As video analytics software becomes more affordable and user-friendly, its adoption across all manner of industries and environments is likely to continue to increase.

Conclusion

Real-time video analytics provide numerous significant benefits to businesses across most major sectors, enabling professionals to gain actionable insights into important security, infrastructural and organizational processes. Using unique video analytics systems, teams can improve security responses, gain insights into business operations and support human workers in performing tasks safely and efficiently, which can benefit modern businesses of all sizes.