AI Video Analytics: Intelligent Ai Video Analytics Service

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Last Updated on August 31, 2022

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AI Video Analytics Overview

With the advancement of disruptive technologies, AI video analytics is fast making inroads into various industries; opening more opportunities for entrepreneurs and businesses to improve efficiency and productivity.

Here is a summary of the benefits, challenges, and applications of AI video analytics as the technology stands today.

Introduction to AI in Video Analytics

AI video analytics is one of the fast-developing futuristic technologies that is sweeping across industries. According to estimates, the market size of AI video analytics is expected to reach nearly USD 15 billion with a nearly 21 % compound annual growth rate (CAGR) from 2021 to 2026.

AI video analytics is combining the powers of deep learning with artificial intelligence and computer vision to give “Sight” to machines, thereby, unlocking massive revenue streams for industries.

Well, if you aren’t much into AI video analytics, we got you covered. Below, we will be exploring the entirety of AI video analytics including the current stage of technology, its benefits, challenges faced, and applications in different industries.

What Are AI Video Analytics?

AI video analytics is the technology that gives machines the “Sight” to identify and extract useful data from video footage. The data is often extracted by tracking objects in the footage (people, events, etc.).

For better understanding, the job that was previously undertaken by the security guard by monitoring video footage from his cabin will now be performed by automated algorithms through AI video analytics.

The intelligent computer vision algorithms coupled with machine learning and AI will be able to detect digital patterns, analyze and process them and extract meaningful information from the videos. Any object detected in the footage will be classified and followed throughout the footage.

The AI video analytics technology can deliver various insights from footage including;

  • Dwell Time: Monitor and track customers as they move through the store
  • Pass-Through Rate:  assess and evaluate the traffic flow through streets
  • Object Classification: Detect and identify objects/abnormalities in a footage
  • Feature Recognition: detect, follow and identify mysterious movements or objects as potential threats within a footage 

Irrespective of the data type used, the technology is all about bringing automated efficiency, deeper business intelligence, and real-time insights to users.

What Are the Benefits of AI Video Analytics?

The advancement in computer vision, artificial intelligence, and machine learning is rapidly increasing the scope and benefit of AI video analytics technology by bringing more efficiency and accuracy.

Today, AI video analytics have made inroads across various industries and sectors, from manufacturing to retail and from security to hazard monitoring. Below are some of the worth-mentioning benefits of AI video analytics:

1. Business Automation

Manual extraction of data from footage has traditionally been a slow and laborious process for businesses.

While previously business leaders have to rely on days or weeks old footage to extract relevant data and make important business decisions.

Today, AI video analytics is automating data collection, processes, and analyzing for businesses; enabling businesses to be more efficient with timely decisions.

2. Real-time Alerts

By automating business processes, companies are in a better position to use data for real-time decision-making. AI video analytics is helping businesses to improve their readiness with real-time situational awareness.

From security agencies to retailers, AI video analytics is helping cross-sector industries to get access to real-time data and respond swiftly to any developing scenarios.

3. Enhanced Business Intelligence (BI)

The computer vision and machine learning algorithms that power AI video analytic systems are powerful enough to undertake deeper dive into the data and extract more useful information than the legacy systems.

Whether the job is to track at specific times, analyze historical data, or generate a heat map, the powerful algorithms are fully capable of delivering insightful business intelligence to the users.

These are just some of the various benefits offered by AI video analytic systems. Some other worth-mentioning benefits of the system include:

  • Greater quality assurance
  • Enhanced security
  • Accurate predictive analytics
  • Powering autonomous vehicles; and
  • Many more

What Are the Challenges of AI Video Analytics?

While the technology is undoubtedly revolutionizing legacy systems, it certainly has its fair share of challenges that impede its cross-industry implementation. Some of the greatest challenges faced by technology include;

1. Environment

For the most part, AI-video analytic systems are implemented in complex environments that entail various moving parts and detailed layouts.

To extract the full potential of the technology, it’s crucial to understand the use cases of the system that may assist the camera network system to capture data from all requisite visual fields.

2. Expertise

Just like some of the other disruptive technologies, AI video analytics is a rather complicated technology. To be able to fully realize the potential of technology, skilled and trained resources are required.

From model training to the understanding of the DNN models and edge deployment, there are various sophisticated components involved in the system, which need to be mastered to make these systems work.

3. Cost

While the technology has significantly matured over the years, it is still a relatively new and expensive system with various cost components attached.

From infrastructure development to maintenance and training, the actual cost of AI video analytic systems can be out of reach for the liking of most businesses.

Business Applications of Video Analytics

As discussed in the previous sections, AI video analytic systems bring various operational and procedural benefits to many industries. Below, we have quickly round-up some of the industries with the most scope and application of AI video analytics.

1. Retail

Some of the widespread applications of AI video analytics in the retail industry include;

  • Improving customer experience
  • Inventory tracking
  • Layout planning
  • People counting
  • Product placement; and
  • more

2. QSR

Some of the widespread applications of AI video analytics in the QSR industry include;

  • Increased throughput
  • Enhanced in-store operational efficiency
  • Greater efficiency for drive-thru locations; and
  • More

3. Security

Some of the widespread applications of AI video analytics in the security sector include;

  • Intruder detection
  • Automated alerts
  • Biometric security; and
  • more

4. Construction

Some of the widespread applications of AI video analytics in the construction industry include;

  • Increased productivity
  • Better labor management
  • Effective theft prevention
  • Enhanced building inspection
  • Timely safety alerts; and
  • More

5. Transportation

Some of the widespread applications of AI video analytics in the transportation industry include;

  • Accident prevention
  • Automatic number plate recognition
  • Heat mapping; and
  • more

6. Smart Cities

Some of the widespread applications of AI video analytics in smart cities include;

  • Incident detection
  • Traffic monitoring; and
  • more

7. Manufacturing

Some of the widespread applications of AI video analytics in the manufacturing industry include;

  • Quality assurance
  • Anomaly detection
  • Remote troubleshooting
  • Robotics; and
  • more 

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Rahul Choudhary is a technology and troubleshooting expert. He gives his expert opinion on different technology trends and provides troubleshooting guides for different apps, websites, & consumer hardware products. He graduated in BA English Honours from the University Of Delhi, and later he learned HTML and WordPress. He also did a certificate course in Hardware and Network Troubleshooting , and a certificate course in Computer Architecture.