Applying video analytics solutions to your business can improve customer experience, reduce costs, and provide valuable insight into your operations that can help you improve what you’re doing. However, there are a few challenges that every organization should be aware of before they begin using video analytics to make their workflows more efficient and profitable. Here are the most common challenges and their solutions.

What are the Video Metrics?

Video Analytics is actually a revolutionary way to bring efficiency to your operations. There have been many advances in technology, but one area that was untouched for quite some time was video surveillance. It can feel very old school you put up cameras, they record what they see, you keep them all going and hope that no one tries to vandalize or steal your property. But there is a newer approach called Video Metrics, which takes things up a notch. It requires less manpower; therefore reducing costs.

Benefits of using Analytics

Businesses have a lot of tools to understand their website traffic, but in order to fully take advantage of all these data you will need a tool to help you interpret them. Statistics such as visits, page views, bounce rate or exit rate only tell part of your story. It is important to see how people interact with your website on a deeper level - what they do while they are on your site and when they leave.

1. General Availability

Making a solution available for everyone means it has to be documented well enough that no matter who walks in to use it, they’ll be able to figure it out. That said, some organizations make their analytics solutions available for a select few (like employees) at first, with plans to generalize later. Either way, you want something your customers can easily access—or you want them to know how best to do so.

The goal is seamless customer engagement with your video analytics solutions one step beyond an initial point-and-click welcome screen or help page will get you there. Documented customer success stories are also valuable; these need not just showcase successes but should provide specific insights into user behavior so other users can apply similar strategies.

2. Predictive Analytics

How Do They Work? Predictive analytics are powerful tools that can enhance your understanding of customers and help optimize operations. However, many companies don’t understand how predictive analytics work or where to begin with them. In a recent survey, we found that two-thirds of respondents struggled with visualizing how AI works, whether it’s face recognition or predictive analytics. Here’s an explanation of how video analytics work for some common use cases. For example, retailers can use cameras to predict which items shoppers pick up off shelves based on what they look at and which products they leave behind. In another example, retail stores can automatically identify faces in crowds and determine their gender as well as age group.

Retailers also monitor social media feeds to get real-time insights into customer behavior from online sources such as Twitter feeds. These advanced analytics offer businesses critical insights into their operations so they can make better decisions about staffing levels and product pricing for maximum profit margins. Many video analytic solutions also have other business applications outside of retail environments from predicting if customers will leave without paying in restaurants to identifying hostile individuals in casinos before they become disruptive problems.

3. Cost

According to a recent report from BI Intelligence, about 85% of businesses currently have video content that isn’t monitored in any way. For companies looking to bolster their analytics capabilities, video analysis is a logical choice. However, with video content coming from a wide range of devices – everything from mobile phones to security cameras to webcams – there are plenty of opportunities for these systems to break down. Here are some common issues with video analytics solutions, along with possible fixes.

4. Data Storage

Storing raw video data is extremely expensive, so most organizations store snapshots instead. Snapshots can take up a lot of storage space (2 to 3 days of 8K video can easily amount to 40 TB), but they’re easy to index because they include information on when each frame was captured. The downside: If you want to search for a specific event, it might be difficult or impossible without first going through every frame in chronological order.

Indexing times can vary wildly depending on how much processing power is available, which means that searching for an event with only partial information could leave you waiting weeks or months before getting results from searches. Storage can be a challenge for any video analytics system.

A good video storage platform will provide you with unlimited DVR storage, real-time search of recorded footage, analytics visualizations in real time, integration with cloud software like Salesforce and be very scalable. The best way to store your videos is either on a cloud based server or an object based storage such as EMC ScaleIO.

With object based storage you’ll have multiple servers connected that act as one unit meaning it doesn’t matter if one server crashes or goes down, you still have access to all your data across all your servers giving you a much higher amount of uptime for your surveillance systems.

5. Accuracy and Reliability

A lot of cameras are far less accurate than you might think. When running analytics on footage, it’s important to take in to account a few factors, like image quality (the resolution), frame rate (the number of frames per second) and exposure.

Exposure has particular significance because high exposure settings can create a lot of motion blur, making it hard for analytics software to separate objects from their background. On top of that, most video files store additional metadata about each shot—but some manufacturers may do so differently or not at all. For example, some sensors create an alpha channel that describes how bright areas within a shot are; others don’t.

6. Customer Support

A number of factors can affect video quality, including bandwidth, type of device and compression settings. Thus, customer support is a critical part of any analytics solution. Some of these challenges will be unique to certain industry verticals. For example, if you’re streaming video for healthcare professionals or caregivers, you may need your analytics solution to have HIPAA compliance. But regardless of industry requirements, strong customer support is crucial for any analytics provider. Without it, your product isn’t likely to be effective in helping users monitor their customers/patients/student needs at all—regardless of how robust or powerful it might otherwise be. 

7. Integration with Existing Workflows

As more businesses are adopting video surveillance, many have adopted enterprise-grade cameras. These cameras record massive amounts of data (think terabytes per day) in a proprietary format that's native to each manufacturer.

In these cases, vendors will either develop their own analytics software or open up APIs for third-party development teams to create applications for them. If your business has already invested in expensive camera hardware or is looking at a particular vendor, integration with existing tools is key. Many users try video analytics for a single location, such as an ATM or retail store.

But these systems are most effective when they’re deployed at several locations with a central management platform. This lets you see how users across your company are using mobile devices or interacting with in-store touchscreens, see if there are any new trends in employee behavior that could make you more efficient, and spot theft (or non-theft) before it becomes too costly. If you have different business units working independently on their own locations, getting them to work together on video analytics will be difficult, if not impossible.

It's crucial that video analytics are integrated into existing IT environments without needing brand new infrastructure—including security protocols for sensitive data which is easier said than done. In many cases, a vendor will provide solutions for integrating their system with other popular platforms like Google Apps and Salesforce.

8. Mobile Streaming

The analysis of video can be complex. There are dozens of ways to take a look at a video stream – by people, objects, colour, light intensity and more. This can create headaches for organisations looking to identify patterns in their videos that may indicate fraudulent behaviour or other issues. What’s more, each way of analysing videos – known as a dimension – has its own challenges and issues. For example, two people standing close together may appear as one person if you analyse a video on dimensions such as colour or shape. As such, tools should be flexible enough to allow you to define your own dimensions along with those provided by default.

9. Scalability, Complexity and Geography

For many companies, scalability is a particularly common challenge when it comes to video analytics. Not only does video data create a higher volume of information for you to track than other types of data, but that information may be coming from anywhere in your organization, from sites across multiple geographies, or from thousands of sources within a single geography. In addition to monitoring massive amounts of video data at scale, companies will also need to process both legacy files as well as new formats. Ultimately, customers should be able to easily scale their video analytics platform no matter how much data they are tracking in order to ensure complete coverage throughout their organization.

10. Data Drift

As videos age, it's hard to ensure that metadata remains current. Even if an organization has gone to great lengths to ensure its video data is always up-to-date, that strategy can easily be foiled by human error or unexpected events like server outages. To solve for data drift, implement a system of video cataloging in which you update a video asset's metadata anytime new footage is captured, regardless of whether it actually changes anything.

That way, you'll always have a full history of every single video you've ever produced; because who knows when what might come in handy? Did you know that data can drift? It’s an easy problem to run into if you’re not carefully managing how your cameras are placed. In a retail space, for example, one camera might be looking at a cash register. That’s fine - but another camera needs to be placed so it can view those same transactions from another angle!

With cameras drifting, security professionals risk losing track of some transactions - which means they could miss a crime or theft in progress. To prevent data drift, make sure all cameras in your security system have a standardized placement and zoom level when possible. If there isn’t room for that kind of organization on your end, consider using multiple systems instead of one large one. For example, use two different cameras to capture both sides of a transaction. This will help keep things more organized and give you a wider range of coverage overall.

11. Complexity of video processing tool

These days, video analytics is a complex technology that can analyze faces in real time and identify thousands of moving objects. But companies should be wary: these capabilities come with caveats that limit their usefulness for certain businesses. For example, face detection systems work only when there’s enough light to make out faces. So companies need to check whether a particular system works in low-light settings or whether it can be used only during certain times of day or year.

Also, some analytics tools require software installation on all clients; others use cloud services (which are more prone to errors). Still other tools lack a user interface, which means users must spend time learning how to operate them before they can get started using them effectively. Most video analytics tools have been designed with an intuitive user interface that allows operators or administrators with basic video processing knowledge to easily handle most of their work without assistance. More advanced users might find these tools useful, but they will definitely need assistance to utilize them correctly.

Smaller companies with fewer resources may find it more difficult for a novice user to learn how to manage such a sophisticated system, since there are so many other things to handle. The good news is that there are many simple systems that can be operated by even inexperienced users.

Conclusion

In conclusion, when deciding which video analytics solution is right for your organization it is important to take a number of factors into consideration. Understanding your goals, resources, and abilities will help you determine which solution is best for you. While there are many different solutions available in terms of price, hardware capabilities, software functionality, etc., they all share one common goal: improved safety in public spaces. Video analytics can help you achieve your safety goals by providing you with valuable information that can lead to safer work environments. Once you have an understanding of what type of system works best for your needs it’s time to get started! Setting up an efficient video surveillance network isn’t difficult if approached properly.