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The Best Tools for Real-Time Alerts in Video Monitoring Systems

When they first emerged video monitoring systems were simply as a system of record. Important events were saved and users could go back to examine them forensically. Some systems still work this way, but the best don’t just record important events anymore – they notify you about them in real time. With real-time alerts, you can respond to crimes, traffic problems, and other issues in your city or business.

But real-time alerts aren’t always effective. In fact, they’re often inaccurate and far too frequent to be effective. Many systems give off dozens, even hundreds of alerts every day for footage that’s completely normal.

For real-time alerts to be useful, you need technology that cuts down on false alerts and improves accuracy. Here are three tools to look for when evaluating real-time alerting capabilities for your video system that will help ensure you get only the alerts you want.

1. Artificial Intelligence

A hot topic in many fields, AI is being used more and more in video monitoring. You can now find tools with machine learning and deep learning built into them, processing large amounts of data to learn what’s normal and what isn’t in video footage.

At first, these AI tools may give off similar alerts as less sophisticated systems. That means you’ll deal with large quantities of false alerts for several days, but their frequency will quickly decrease as the system processes more data. As the AI tools learn what’s normal in a video scene and what isn’t, you’ll get fewer, more accurate real-time alerts that improve your reactivity and efficiency.

AI is often built into emerging video platforms, including those that work with IoT devices. The IoT turns cameras into sensors, and the AI interprets the data they send back, becoming more and more accurate over time.

2. Statistical Algorithms

While less exciting than AI, statistical algorithms are a practical way to customize what real-time alerts show you. Many video systems use statistical algorithms as a mathematical instruction book explaining what’s important in a video scene and what isn’t.

Like AI, statistical algorithms can drastically reduce the amount of real-time alerts you get and increase the accuracy of the ones that come through. It does this by filtering through ordinary footage and sending out alerts only when scenes don’t fit the algorithm’s parameters.

You can often find statistical algorithms in camera hardware that has intelligence built in, as well as more in-depth video systems that combine statistical algorithms with other tools.

3. Video Analytics Software

Not all video analytics software includes real-time alerts, but systems that do typically use multiple tactics to provide higher-quality notifications. For example, a video analytics platform could combine AI, statistical algorithms, and edge computing capabilities to identify anomalies in video footage and flag them for human review.

By using video analytics software, you get a complete toolset that informs and improves your real-time alerts. You may even be able to build your own algorithm or application, as well as customize other settings to further refine how your system alerts you to important events.

The Quality of Your Real-Time Alerts Depends on the Tools You Use

Not all video systems are created equal, and even emerging technology like AI doesn’t guarantee you’ll get an effective system. To improve your real-time alerts, you need to determine what your goals are and what you want to get alerts for. Then, look into whether a simple statistical algorithm can do the job or if you need to build your own algorithm and application to get the best results.

Once you’ve identified the tools you need, look for established vendors who have a reputation for keeping up their products. These vendors are more likely to continue to develop their product as technology improves, ensuring you’ll have high-quality tools and effective real-time alerts years after you purchase a product.

Turn cameras into IoT sensors with real-time video analytics software.

Case Study: IoT is redefining the customer experience. Nokia case study.

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