The Utilization of AI in Video Analytics

The advanced technology era has demanded that all processes be automated, including camera monitoring processes. Typically, camera monitoring is done manually by humans, which often leads to many "human errors" since humans naturally feel tired or bored when repeatedly monitoring the same activities in front of a camera.This is why companies have shifted from traditional monitoring methods to automated monitoring using computers.

In this article, you will learn:

1. What Video Analytics is.
2. The role of AI in Video Analytics.
3. Examples of Video Analytics Applications.

The Role of AI in Video Analytics

Data Analytics is referred to as the knowledge of studying raw data to generate valuable information. But when the data is in the form of video, it is known as Video Analytics. In its process, Data Analytics is assisted by various AI (Artificial Intelligence) techniques to identify patterns in data.

AI techniques such as machine learning, deep learning, etc., can be trained to help detect, identify, and categorize data more quickly and accurate, while minimizing errors that may arise from human involvement.

Compared to traditional monitoring, which requires 2-3 shifts for 24/7 operations and is prone to human error, Video Analytics enables real-time and precise results.

Video Analytics Workflow

There are three stages in processing data in Video Analytics, including:

1. Input: Since video analytics involves processing data in video format, the raw data is directly captured from the CCTV/camera devices.
2. Process: In this stage, the video is processed according to the objectives of the application. The video is processed frame by frame and then reassembled into a video with processed data that can provide information to the user.
3. Output: The newly processed video can be displayed on various devices in the form of web, desktop, or mobile applications in real-time.

Example of Video Analytics Implementation

Let’s take an example of Video Analytics implementation on traffic. Essentially, Video Analytics installed on highways can serve three functions:

Video Analytics for Vehicle License Plate Recognition

Using high-speed CCTV cameras, video analytics can detect and read license plates of passing vehicles in real-time. This allows authorities to utilize the data in other systems, such as for electronic ticketing processes.

Video Analytics for Traffic Monitoring

Video Analytics has proven effective in observing and analyzing traffic conditions. It can determine the causes of traffic jams and analyze the affected area. In the event of an accident, the data from Video Analytics can serve as evidence for authorities to manage the situation.

Video Analytics for Vehicle Counting

The goal of this application is to categorize vehicles that pass a specific area. Categories can include cars, motorcycles, buses, and taxis. The resulting data can help authorities monitor traffic density in one area compared to others, making it easier to identify and address traffic jam points based on the data provided.

Implement Video Analytics Now!

With specific goals, Video Analytics has proven to help many companies automate processes and generate high-value data.

With over 11 years of experience in Digital Transformation, KLIK Group is ready to bring AI in Video Analytics to elevate your business!

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