The Continuing Evolution of Video Analytics

The world of video analytics is rapidly changing. Industry professionals in surveillance, information technology, operations and even marketing seek ways to leverage new technologies for loss prevention, safety, operational efficiency and improved sales.

At the same time, many businesses have yet to tap into the full power of video analytics, in some cases, overlooking opportunities to get more out of the equipment they already have.

This article touches on the evolution of video technology, what’s on the horizon, and how your business could possibly get more from video analytics.


Moving from surveillance to video intelligence


Over the past few years, we’ve helped clients leverage video technology as it has evolved from basic surveillance to video intelligence that can do so much more.

Initially, video surveillance was used primarily for security and loss prevention, enabling security teams to expand their watches by monitoring a few feeds in a central location. However, as the need for video surveillance grew, so did the need for massive data storage, and it became impossible for security teams to monitor every video feed 24/7.

Video motion detection helped but was prone to false alarms triggered by trees, animals and other moving objects. Artificial intelligence (AI) and deep learning (DL) were the real game-changers. These technologies make it possible to monitor hundreds of cameras simultaneously and make complex distinctions between people, animals, automobiles and other objects. Driven by AI and DL, intelligent video systems instantly process and react to volumes of data faster than humans can filter, find and decipher video.

The filtering capabilities of these systems continues to improve which dramatically reduces video search time when looking for something specific such as a person with a red jacket or silver SUV.

In addition, the advent of edge analytics and cloud computing has decreased the need to invest significant resources in on-site servers and bandwidth. Cameras can perform analytics on the edge to reduce bandwidth and latency. Analytics can also be performed with an on-site appliance or via cloud computing, further reducing the need for on-site resources.


Going beyond surveillance


Advancements in IP video and digital technology have made video analytics much more accessible and usable for other business areas. Video intelligence has segued video from a surveillance tool to valuable technology employed by security, operations, safety, and marketing professionals.

Just a few practical uses of video today include:

  • Gaining deep insights into customer behavior
  • People counting
  • Alerting store personnel of long lines
  • Reporting traffic patterns of people, vehicles, forklifts, etc.
  • Notifying personnel or authorities of suspicious behavior
  • Triggering audio messages to provide direction, reduce crime or enforce safety protocols
  • Reporting workstation occupancy in a shared office environment
  • License plate recognition

In this new frontier, computer vision technology can make informed decisions, react to real-time situations, and automatically trigger critical measures or responses.


Learn more


Of course, knowing about video technology is one thing; identifying the best way to deploy it for improved business operations, safety and security is another. Ever-evolving technology consistently introduces new opportunities to get more out of video, often with the equipment businesses already use.

Talk to your integrator about what is possible or schedule a visit to the MTG Innovation Lab to see some examples of what video can do for your business.


Q: What is video analytics, and why is it important for businesses?

A: Video analytics is the process of analyzing video data to extract meaningful insights and information. It uses advanced algorithms and computer vision techniques to automatically detect and analyze various aspects of video content, such as objects, events, behaviors, and patterns.

Video analytics is crucial for businesses as it enables them to gain valuable insights, improve security and safety measures, enhance operational efficiency, optimize customer experiences, and make data-driven decisions.

Q: How does video analytics work?

A: Video analytics employs sophisticated software algorithms that utilize artificial intelligence and machine learning techniques. The algorithms analyze video feeds in real-time or after recording, identifying objects, tracking movements, and recognizing patterns and events.

The technology can perform various tasks, including object detection and classification, people counting, crowd analysis, facial recognition, license plate recognition, and anomaly detection. By leveraging these capabilities, businesses can unlock actionable insights and automate previously labor-intensive processes.

Q: What are the key benefits of implementing video analytics?

A: Implementing video analytics offers several significant benefits for businesses. Firstly, it enhances security by providing proactive monitoring, real-time alerts, and threat detection capabilities. It also enables companies to optimize operations by monitoring key performance indicators, identifying bottlenecks, and streamlining processes.

Additionally, video analytics can improve customer experiences by analyzing customer behavior, tracking queues, and optimizing layouts. It also empowers businesses with data-driven decision-making by providing valuable insights and enabling predictive analytics.

Q: What are the challenges associated with video analytics implementation? 

A: While video analytics offers significant advantages, there are a few challenges to consider during implementation. Firstly, ensuring the accuracy of the algorithms is crucial. False positives or false negatives can impact the reliability of the system.

Video analytics may require powerful computing resources, especially for real-time analysis or handling large volumes of video data. Lastly, ensuring compliance with privacy regulations and addressing ethical concerns related to facial recognition or individual tracking is essential.

Q: Is video analytics only applicable to security applications?

A: While video analytics has gained prominence in the realm of security applications, its scope extends far beyond that. While it helps improve security by detecting intrusions, monitoring access control, and identifying suspicious activities, it also has diverse applications in various industries.

For example, video analytics can assist with customer behavior analysis, optimizing store layouts, and managing inventory in retail. In transportation, it can aid with traffic monitoring, vehicle counting, and license plate recognition. Businesses across different sectors can leverage the power of video analytics to improve their operations and unlock valuable insights.


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