Your Complete Guide to Intelligent Video Analytics

image: Intelligent Video

Video analytics converts raw data into useful information to display in real-time, allowing companies to make strategic decisions and gather insights regarding behavior.

Advancements in deep and machine learning have breathed new life into video analytics, automating tasks that were once the sole purview of humans. In the same way that digitalization makes business communications a competitive advantage, Artificial Intelligence (AI) can improve your video analytics to rise ahead of your rivals.

But how exactly does it help you? We’ll go over what video analytics are, how they work and why you should be using them for your business.

What is video analytics?

Video analytics, or video content analytics, is a technology that automatically analyzes video content.

Usually, video analytics perform real-time monitoring to detect objects, object attributes, or movement patterns from the monitored environment. Also, they can additionally gain insights from historical data, which can be essential to find trends for business improvements. This is similar to voice analytics. Understanding what is voice analytics might be a wise first move.

Intelligent video analytics

Intelligent video analytics goes one step further and uses machine learning to analyze video content. Humans can make errors, and basic algorithms aren’t complex enough to execute the task. AI has several benefits, including analyzing video content faster and more efficiently than humans.

As AI never needs to sleep or take a break, it’s ideal for consistently analyzing multiple data streams. The more data you expose to AI, the better it will identify and track objects, leading to more accurate insights.

For example, imagine you want to count the number of customers in a store and their ages. Training AI to understand what a human looks like and accurately identify their age will enable reliability and speed over humans.

Therefore, intelligent video analytics can be essential to prevent errors and improve productivity in your business. Video analytics are already used in multiple industries, such as security and retail. But, the possibilities of these systems are always growing due to the capability of what they can detect.

How do video analytics work?

Intelligent video analytics solutions will vary depending on the particular use case. Another consideration is whether the analysis is in real-time or post-processing, where it analyzes historical content.

Feed the system

AI excels at processing large volumes of data securely, like with AI website security. Multiple video streams from various sources, such as online video or CCTV cameras, can integrate into the solution. One important consideration is having comprehensive coverage of the area that needs monitoring.

Central vs edge processing

There are multiple ways to run video analytics software, depending on the use case:

• Central processing - software runs on servers. It can provide several analytics tools and options, making it ideal for post-processing.
• Edge processing - software is embedded in cameras. It can assist real-time identification and detection but has fewer tools available.

One limitation of AI is hardware. This can impact the detection performance for edge processing. While legacy hardware is affordable, it won't provide the fastest results compared to newer hardware options.

Newer options additionally provide scalability, which is vital to integrate new cameras and server technologies. For example, VoIP is a newer option to the POTS line meaning it's cost-effective to scale up.

Hybrid options are available to bring the best of both processing options. It can be advantageous for real-time monitoring, as it can provide fast detection and multiple analysis tools.

Defining scenarios and training models

What events do you want to target and identify? Crowd flow? Queuing? Shoplifters? Traffic incidents?

Once you have the physical technology in place, it’s time to train AI to carry out basic tasks. While commercial options are available, tailoring AI for specific scenarios is essential to focus on your needs. Some basic training tasks include:

• Image classification
• Localization
• Object detection
• Object identification
• Object tracking

Training AI models from scratch are time-consuming, but datasets are available online to simplify this. While you can fine-tune pre-trained models, open-source projects have increased in recent years, allowing custom video analytics solutions.

Human review

Humans are necessary for any video analysis system. While AI provides fast and reliable insights, these insights need verification, and alerts need monitoring to ensure the right action.

Reviewing AI is essential to keep its training on track and improve the video analytics solution.

Why should you use video analytics?

The main advantage of video analytics software is its ability to automatically identify events in real-time. It relieves the pressure on human operators, such as security staff. The advantages of this system are similar when looking at what is speech analytics benefits:

1. Increased speed and efficiency

Monitoring and analyzing video streams in real-time can be as challenging as creating compelling content.

For example, security employees have to monitor several screens simultaneously. Slight movements or changes could indicate suspicious activity, so they have to be constantly alert. It can lead to false alarms and missed events if they get distracted.

Intelligent video analytics can resolve this issue. AI simultaneously analyzes several video streams faster than humans. It increases productivity and relieves the burden on human operators, like security staff. Instead of worrying about every little detail, they can focus on the events that matter.

It's additionally helpful when analyzing historical content for insights. Rather than humans poring over videos for several hours, AI analysis can go through them in minutes. Its time-saving nature increases efficiency, lowers costs, and increases productivity as employees aren’t wasting time on mundane tasks.

2. Accurate and reliable

Humans are well-suited to analyzing videos accurately under optimal conditions. But, if they're distracted, overworked, or tired, their accuracy and decision-making are threatened.

For example, when monitoring elderly patients in a care home, humans can quickly identify when a patient needs help. But, if they shift their focus for a second, the patient could be overlooked.

Unlike humans, AI never loses focus or tires. It works consistently for as long as it is needed.

AI can assist human operators in analyzing and detecting crucial elements of real-time and historical video. It allows it to focus on making decisions with the data and insights that AI provides.

Human operators can be supported and avoid burnout knowing that AI will provide them with continuous and uninterrupted support.

3. Continuous learning and improvement

If an algorithm isn’t accurate, it won’t provide correct data, leading to the wrong insights.

For example, if AI inaccurately analyzed the age and number of customers at peak times, the store may invest in the wrong customer-targeting strategy. Therefore AI accuracy is paramount. Fortunately, AI is a machine learning algorithm. The more data or video content you expose AI to, the greater accuracy its analysis and insights will have.

AI can be trained for specific situations and industries, making tailored solutions possible for various purposes, such as gathering video marketing data, security, healthcare, or behavior tracking. This can help provide better experiences for business clients, like dynamic website personalisation.

Intelligent and reliable analytics

The use of AI is increasing, and intelligent video analytics is another area where it can be invaluable to help with daily tasks. Several industries can benefit from using this technology, like retail, security, or hospitals.

AI video analytics increases efficiency and undertakes repetitive tasks, such as in SaaS marketing automation, reducing workloads for human employees. It saves companies time and money in the long run.

A key consideration before choosing an intelligent video analytics system is the particular use case as it can determine your AI approach. Using central processing, edge processing, or a hybrid system can be vital for effective real-time or post-processing analysis.

Your need for intelligent video analytics will depend on your business requirements. But, if you’re looking for a consistent, accurate, efficient, and reliable system to assist your human employees, then you’re looking in the right place.