Video Analytics – Emergence And Industrial Uses

Video Analytics – Emergence And Industrial Uses

Video analytics has attracted immense curiosity and interest over the past few years.

We can also call it video content analysis or intelligent video analysis.

It can automatically analyze videos to extract information and detect temporal and spatial events.

Recent modifications have taken this technology to a new level wherein some applications can count the number of guests in an event/shop, detect license plates, and give you real-time data on how many parking slots are available.

With such increasing advances in algorithms used, real-time video is being used in a wide range of sectors, mainly for safety and security.

It has automated numerous tasks that humans used to do previously. The main reason for this automation is because continuous and accurate monitoring of objects and actions is impossible for humans.

Video analytics and motion detection

Motion detection is the most crucial task in video processing. It helps to draw important information such as object tracking.

Object Tracking is the process of estimating the path of an object in motion in a video stream.

Motion from continuous video streams can be detected through optical flow and background subtraction.

Frame referencing or pixel matching are the processes through which it is carried out.

Visual surveillance is an essential technology for the fight against terrorism and crime, public safety in transport networks like airports and train stations, town centers, schools and hospitals, and other public facilities like traffic lights, railroad crossings, etc.

Video analytics market

With the use of VA capabilities, the video surveillance market has many players that provide a range of commercial products.

Along with big names like IBM & Honeywell, newer disruptive companies like Tooliqa, AllGoVision, and Intellivision are some companies that specialize in real-time Video Analytics.

Tooliqa focuses on converging deep learning, computer vision and 3D to make advanced technology solutions find innovative applications in its range of products and services.

Most companies that implement video analytics applications do so by using public domain computer vision and image processing libraries.

The most offered video analytics functions that several companies provide are Unattended/Left-Behind Baggage Detection, Person Tracking in non-crowded and crowded environments, Person-baggage Tagging, Object removal detection, loitering detection, Tail-gating detection, and Tamper detection.

Industry applications of Video analytics


Many retail stores rely on video surveillance (CCTV) cameras, which they use to monitor the property or investigate an incident using video footage post-event. In addition to those camera networks, video content analytics systems provide the valuable data recorded by those video cameras.

Retailers can use video analytics to understand the shopping behaviors of their customers.

Store managers benefit immensely due to the insights provided into how customers navigate the floor. Other than using anti-theft mechanisms such as face recognition algorithms to prevent any shoplifters, the retail industry can also streamline operations by:

Reducing crowding hotspots

Preventing crowding is an important factor in a safe customer experience- especially since the COVID-19 outbreak. Video analysis data can help uncover the reason behind these crowds. They can also provide information on better crowd management to prevent future crowding and long queues.

We can use video content analytics to trigger alerts by detecting proximity and people counting.

Maximizing sales

Since these algorithms can recognize faces and people’s characteristics such as age and gender, detect walking patterns, and direction of gaze, retailers can use this to create optimal store layouts and figure out which displays, or promotions are inviting the most traffic.


The healthcare sector has invested immensely into the latest technology to ensure the safety of its patients and staff due to the involvement of strict corporate legislation. They rely on video analytics to increase security and awareness of the environment inside the healthcare facility.

The study of patient and visitor traffic can be valuable in planning ways to shorten waiting time while ensuring easy access to the emergency room.

Monitoring of kids and elders

If children or elders as patients in a homecare setting are left alone by the staff, there is a chance they might fall and hurt themselves without anyone noticing quickly.

These falls can sometimes cause death in elders and major injury in children, this is why at-home monitoring is important to recognize abnormal movements or periods the person is lying on the floor or incapacitated.

Ward monitoring and occupancy

Several healthcare facilities use video surveillance to detect the traffic of patients and vacancies of beds. This feature was very helpful during the pandemic when people were instantly notified about any bed vacancies through various applications.

Smart cities - Transportation

Increasing traffic in urban areas cause major traffic jams and roadblocks. Video analysis has proven to be an enormous help in the area of transportation, aiding in the development of smart cities.

Detecting dangerous situations

Vehicles catching fire, moving eerily, or just being in an accident. These systems are helpful as evidence as well as alerting the concerned authorities to provide immediate help.

Further, optical character recognition helps decipher the number plate of vehicles and keep a record of the vehicle’s movements.

Vehicle counting

This involves differentiating between vehicles like cars, buses, bikes, trucks, etc. to generate statistics that we can later use to obtain insights about traffic.  


The capability of video analytics for security surveillance systems through video are advancing significantly. Users have actively demanded intelligent security solutions. It focuses on automating challenging security tasks such as:

  1. Monitoring high numbers of live video streams,
  2. Providing instant actionable alerts for a variety of activities
  3. Verifying alarms in remote locations, etc.
Facial recognition and license plate recognition techniques are used to identify people and vehicles in real-time.

Face recognition algorithms are trained to spot known shoplifters. They can also spot, in real-time, a person hiding an item in their bag or stuffing it in their clothes.

Apart from serving security concerns, it also detects:

  1. Traffic and crowd management
  2. Footfall analysis
  3. Social distancing
  4. Face mask detection during the pandemic.

With the continuing advancement of computer-related technologies, video analytics remains an area of constant and active advancement.

Tooliqa specializes in AI, Computer Vision and Deep Technology to help businesses simplify and automate their processes with our strong team of experts across various domains.

Want to know more on how AI can result in business process improvement? Let our experts guide you.

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Quick queries for this insight

How can video analytics help in healthcare?
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In healthcare, video analytics can be used to track patient movement, monitor vital signs, and detect behavior that may indicate a health problem. For example, video analytics can be used to automatically detect when a patient has fallen and send an alert to staff. Additionally, video analytics can be used to monitor vital signs such as heart rate and respiration. By tracking changes in these vital signs over time, video analytics can help to detect early signs of illness and provide valuable insights into a patient's health.

How is motion detection achieved in video analytics?
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There are various ways to detect motion in video analytics. Many surveillance cameras use a motion detector to trigger an alarm or start recording when movement is detected. This type of detector uses infrared technology to sense changes in the heat emitted by objects, and can be affected by factors such as sunlight and wind. Other methods of detecting motion include image subtraction, in which two images are compared and any differences are highlighted, and frame differencing, in which each frame of a video is compared to the previous one. By analyzing the pixels that have changed between frames, it is possible to detect even small movements. These methods are often used in combination to achieve accurate results.

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