Hassan El-Banna, Business Development Manager, META at Genetec discusses how video analytics can help make sense of the data that our connected security platforms and sensors are already collecting every day.
Organizations of every type and size are always looking to make more informed decisions. In order to do better and plan for the changing world, they want to have access to as much information as possible. And, rather than implementing a new information gathering system, many are looking to mine the data already being collected by their physical security systems.
But it’s not enough to simply access this data. You need to make sense of it, and that’s where video analytics comes in. In general, analytics tools take large amounts of unstructured data and structure it to allow you to unlock its value. When you are able to correlate and extract information, you can gain all manner of insight into your business and environment.
Video analytics has been part of security systems for 10 to 15 years. Traditionally, security departments used video analytics as a reactive tool that could detect something in a live video stream and then create an event that operators could respond to. But, organizations have come to realize that you can use video, as well as other related data from access control and license plate recognition, for more than physical security.
Since then, video analytics, powered by the advances in computing power, has evolved considerably to extract very reliable and powerful data from our video streams.
And the industry itself is getting better at presenting the mined data in more consumable ways. We’re seeing a more end-user-oriented approach towards the development of systems. Instead of just providing all the data that is available, solution providers are looking at what users actually need and how to present that information in the clearest possible way.
With all these advancements, organizations can now visualize their data to optimize resources and to make better business decisions. Currently, there are several major vertical sectors where video analytics is already having a huge impact, including retail, airports, and traffic.
Retail: understanding your customer
One of the main contributing factors to the incredible success that online companies like Amazon have achieved is their ability to collect, analyze, and use the vast amounts of data their customers produce. When a store knows its consumer, it can tailor every shopping experience to suit their needs. Brick and mortar stores are now asking how they can possible compete.
The answer is video analytics. Offline retailers see video analytics as a key tool for gathering information about how many people come into their stores, what they do while there, and which products they are looking at. Using this information displayed in heat maps or in people counting applications, they can analyze merchandising browsing behaviors and calculate conversion rates: how many people go into their stores vs. how many people actually buy products. Then, with greater understanding of their customers’ behavior, they can make informed business decisions, including item placement and staff optimization, to better serve shoppers.
Airports: improve passenger flow
Airports are also looking to make better business decisions that will improve customer traffic and increase revenue. In particular, they are looking for ways to optimize the flow of people through their spaces to make the process of boarding and disembarking as efficient as possible.
Video analytics is a great tool for understanding how long people stand in security lines, where roadblocks occur, and where people gather. With this information, airports can optimize their staffing, reduce known congestion sites, and inform passengers where they should go and how long they can expect to wait in security lines. This will allow people to move through lines and check-points as quickly as possible, which can result in a direct increase in the revenue generated by duty-free shopping.
Traffic: keep everything moving
We are seeing a big push in smart cities to measure traffic in a reliable and flexible way. The data collected and understood through video analytics can provide cities with valuable information about what’s happening on their roads, how many cars are on a given street or how many cars are going through a specific intersection.
This data can be invaluable for city planning, particularly when it comes to traffic coordination. City planners and traffic engineers can use this information, for example, to re-route traffic through alternative routes during rush hour to avoid congestion and to optimize the flow of vehicles through their streets. This would not only make commuters happy, but could also reduce car emissions as vehicles would travel at a more consistent speed.
A means to create value
Ultimately, video analytics is a means of creating value in many different industries through a variety of solutions. With its growing success, video analytics will likely move away from existing as a separate application. Security platforms that come with built-in analytics are speeding up deployment and delivering accurate results. While that’s a relief for many, there’s one question that’s still frequently asked: ‘Should I get server-based video analytics or install them on the edge?’
Server-based or on the edge?
Before we dive into the pros and cons of each option, let’s clarify the terms. When we refer to edge-based analytics, this means that the camera or encoder is processing the image and creating metadata. In a server-based analytics setup, video streams are sent to and processed on the server, independently from the cameras. Each option is viable and effective, but choosing the best option will depend on your environment.
When you process analytics on the camera, the main advantage is that you’re able to reduce bandwidth usage. You can set up a distributed system architecture and lower server costs too. That’s because the camera filters the information, so you avoid having to transfer all video data to the servers.
However, this is only true if you are only storing the video which the analytics solution has classified as relevant. This means that if you want to keep all video for a certain period of time, or just keep all video with motion-detected events, you would not gain much value from this option.
When you opt for server-based analytics, you’re free to choose any cameras you want. This can be particularly advantageous to anyone who is upgrading their security system and want to reduce costs by keeping existing edge devices. While it’s best to check with your analytics provider, server-based analytics usually work with most cameras, regardless of the camera vendor or model.
Another main advantage is that you’ll get better performance. Servers have more processing power and are able to process more video and more analytics applications. In return, leveraging the processing power allows for the development of more advanced analytics.
Server-based analytics can be easier to setup and use as well. If you’re using a security platform with unified analytics, for example, you’ll be able to configure the analytics from the same interface as your video management system. This is also true for various analytics applications, providing the same user experience across all types of video analytics which simplifies configuration and operation. In larger deployments with hundreds or thousands of cameras, this can be a huge time saver.
Choosing the right analytics technology really comes down to your needs. If you’re only looking to do basic analytics or you have a small to medium-sized installation, an edge-based solution might be the right choice for you. If you require high-end analytics or have a larger enterprise system, server-based analytics is the way to go.
Security departments are sitting on a goldmine of data that is being collected by video cameras and other connected physical security devices. Whether on the edge or on the server, analytics can transform this information into smart, actionable insights. This can be used to not only improve security but also improve any number of business functions, including efficiency, operations, customer service, and revenue generation.