There are major economic advantages driving cloud computing in the IT world, but those same economies don’t work with video surveillance. This is glossed over and never mentioned in all the articles and ads that tout cloud computing for video surveillance. Companies just want to use the “cloud computing” label to get attention, when, in fact, if anything, video surveillance is moving in the opposite direction – more and more towards intelligence and storage at the edge.

Why doesn’t cloud computing work for the video surveillance market? After all, video compression and storage are some of the most processor intensive functions in physical security, especially if you try to add video analytics processing. But there are big differences, and once you look at the math, it is clear that someone has their head up in the clouds to be suggesting it be used for surveillance.

There are three big cost advantages coming from cloud computing in the IT world:

First, it is more economical with virtualized services. This means that you can save money running your sales management software tools on the same server as another company’s manufacturing resource planning software, or whatever other kinds of software other companies might want to run. Servers have been doing this for years in data centers. Now, they can do it across the Internet for many companies in one location.

Second, you get added savings because you no one uses their software all of the time, it is usually only needed in spurts. So, you reap the gains by sharing servers with others, by maximizing shared processing power.

Third, bringing  lots of server applications under the roof of one specialist company means they can manage everything more efficiently and take the headaches away from lots of individual companies trying to do it themselves.

For the above reasons, cloud computing service providers are saving IT managers 25% or more. That is significant. This assures that cloud computing will grow fast.

But these benefits don’t fly with video surveillance. Here are the problems:

1. You can’t virtualize NVR storage, because the video is recording continuously. This is the same problem that IP video systems have in the data room. IT managers would like to combine them onto their other servers, but they can’t do it because the video is streaming into the servers continuously. It is being recorded non-stop. In fact, video recording is so processor intensive that traditional servers fail, which is why the industry has introducing new server designs specifically for video surveillance. You can’t virtualize the NVR and run it on another server.
2. Most software applications see people retrieving data about 50% of the time  and storing data 50% of the time, but those applications are generally idle and waiting most of the time. NVR storage is recording 100% of the time, with huge bandwidth demands, while people only play back the video less than 1% of the time. The reason you can only run about 30 cameras (this varies by resolution and frame rate being recorded) on a good server is because you run out of bandwidth and processing power. So, there are no benefits gained from idle time.
3. In fact, it is far more expensive to centralize storage because of the above problems and the huge bandwidth needed by the video. This is why most hosted video services are finding that it makes far more sense to put a DVR or NVR at the site with the cameras, or to use cameras with built-in storage, rather than continuously streaming the video back to a central server. It is far less expensive.

As I said above, the real technology shift in video surveillance is in the opposite direction: Intelligent storage at the edge.

This becomes even clearer when you start talking about video analytics. Some companies offering a hosted video service are trying to stream video back to a central server. They are trying to make it sound as if cloud computing is going to save the end user money. In fact, their solution is more expensive, but if they don’t put in a DVR they can save up front costs for the customer. Unfortunately, they seriously cut back the video resolution and frame rate: You aren’t going to get anything close to high quality video this way. They won’t even be able to offer standard resolution, never mind megapixel video to their customers. It is more expensive, on an ongoing basis, but it does eliminate the cost of the DVR.

But when you try to offer video analytics, you can’t play that game: You need high quality, high frame rate video. That makes the so-called cloud computing video surveillance system a non-starter. You can’t get there from here.

This doesn’t mean that Hosted Video and Security as a Service (SaaS) aren’t growing fast. They are, and for good reasons, but none of those reasons have to do with cloud computing economics. They are growing because of superior ease of use for end users, friendly browser interfaces that they can access from any computer, and by providing remote services for end users. It is an ideal solution for small businesses and small retail stores that want to add security video.

The term “cloud computing” has been hijacked and is being treated as the next big thing for security. It is causing a revolution in the IT industry, so why shouldn’t it for surveillance? Well, because it ends up costing more, not less, to use it with video.

IMS Research placed storage in the camera at #2 of the biggest trends for 2010:

http://www.imsresearch.com/press_release_details.html&press_id=1224

Here’s a link on a recent review at the latest industry trade show in Las Vegas, last month:

http://www.experteditorial.net/securitysquared/2010/04/when-inteligence-moves-to-the-edge-1.html

As you can see, there is a lot of talk about storing video in the camera as a growing trend, and many of the leading companies are getting on the bandwagon. But what isn’t being said is that in almost all these cases, what they are talking about is not the ability to store enough video in your cameras to replace the DVR or NVR in your system.

What they are talking about is simply buffering the video storage. That means storing just a little bit of video, such as hours worth or sometimes a few days worth of video.

Anyone playing video from the Internet uses video buffering. That’s why it says “loading”, since it is creating a buffer in your PC, so that it can play the video smoothly without interruptions. That’s a buffer, not long term storage. You can’t go back the next day to find the video file on your PC, because it is erased. This is the difference between storage and buffering.

There are two main benefits for buffering video in surveillance: First, if your network goes down for a few minutes or a few hours, you don’t lose the video from your cameras. As long as you don’t wait too long, you can go back to that buffered video to see what happened during the network downtime.

Second, when transmitting video through networks, there can be short interruptions or delays. This is especially notorious with wireless networks and the Internet, which is the same reason video streams are buffered from the Internet. Buffering the video helps a lot in overcoming these kinds of issues.

But this is completely different from true storage in the camera, where you can get months or even up to a year’s worth of video storage right in the camera.

I hear strong interest for storage in the camera, since it eliminates the need for an external DVR or NVR, and it also reduces 99% of the bandwidth used by IP cameras, since most of the bandwidth is used while streaming video across the network for storage. Only about 1% of security video is actually used, so that means 99% of the bandwidth is wasted.

There are also in many cases significant storage cost savings, when it is built into the camera.

To get this kind of storage, we at VideoIQ include a full hard drive in the camera. That gives enough for months worth of continuous video storage. In fact, we now have models with up to a year’s worth of storage.

However, I rarely hear much excitement over buffering video. Most integrators realize that losing video during network down-times is a problem, but few want to pay the extra money for this, since it rarely occurs.

So, it looks to me as if most of these companies are jumping onto a bandwagon without realizing what they are jumping onto.

There is one application where cameras with a little bit of recording can make use of the storage in the camera: For applications where the camera is not recording continuously, but only with motion detection or some other kind of detected event. If events are rare, you can get by with a little bit of storage.

But the problem is that motion detection rarely works outdoors, since it cannot distinguish all the pixel changes occurring from changes in the light, trees blowing in the wind, etc., that are happening all the time. So, it will end up recording most of the time, which means you need a lot of storage. That’s why video analytics are needed – they can recognize what a person looks like, for example, and ignore all the kinds of pixel changes and movement in the scene.

One last thing worth mentioning on this subject that is rarely mentioned: Most of these companies selling cameras with what they call storage have no easy way of getting the video off the cameras. In some cases, if you want to retrieve the video, you need to go around to all of the cameras and manually collect the SD cards. Who would ever use such a system?

Frankly, I don’t think anyone is using such systems, but they are being advertised as storage in the camera.

There are a few companies who have software that enables you to access that buffered video, but there hasn’t been support for this with the large Video Management System companies (VMS). So, in large camera systems, where a VMS is usually a requirement, you are up a creek without a paddle, since there is no way to use that software to access the stored video.

Fortunately, this is changing rapidly. Genetec just announced a new update to their software that includes edge storage support. Milestone is going to be releasing something soon. OnSSI is also close.

One company not mentioned in the above video, but who is clearly way ahead of all the other VMS companies in this category is IP Vision Software. They’ve designed a system that was designed from top to bottom for distributed storage. So, they have full integration of storage in the camera capability. They are definitely worth checking out.

So, when is storage in a camera not storage?

First, when it is only buffer storage, for a few hours or days worth of video. It may help cover network failures, but it won’t replace the need for an NVR if you want continuous recording.

Second, when you have no easy way of accessing the video. It should be just as easy to playback video in the camera as it is from your NVR or DVR. It should be no different.

It was eye-catching. Lots of people stood there staring at the analytics detecting people, cars, trucks, motorcycles, sailboats, speedboats, etc. Here’s a picture:

Unfortunately, this blog can’t show the full resolution or video, which you really need to see to appreciate how incredible it looks.

When I say this is the first public display of “true megapixel analytics” I mean the resolution being analyzed is megapixel. There have been cameras with megapixel video that have had analytics processing before. CoVi is a good example, may they rest in peace. They sold a 1 MP camera that ran ObjectVideo analytics. However, the resolution of the analytics was only CIF (320 x 240 pixels), which gave hardly any detection range. It was silly to put CIF analytics on a megapixel camera.

Why hasn’t anyone ever demonstrated megapixel analytics before? Because of the sheer processing power that other technologies need to do this.

VideoIQ’s technology is different. We need about 1/8th the amount of processing power compared to other high quality analytics systems. So, we can run the whole thing in one of the popular low cost DSP processors. But all other analytics technologies need a lot more horsepower.

For example, ObjectVideo on their web site claims they can run up to 4CIF resolution video in the same DSP chip we are using. However, in most cases the users of OV onboard are only running CIF resolution, because there are serious limitations running 4CIF, such as only being able to have one rule running at a time and a limited number of objects that can be detected.

IOimage uses two DSP processors in their cameras to get high quality and avoid compromising detection.

The camera we demonstrated was a 1080p camera, which is 1920 x 1080 pixels. We demonstrated it live at the show, with the analytics all running in the camera. It provides 3X the horizontal coverage of a standard resolution camera, and more than 2X the anaytics detection distance.

For other technologies to run 1080p analytics, they would need more than 6 times as much processing power, compared to 4CIF video. That would mean 6 DSP chips, or some very expensive high end DSP chips.

If you try to run this on a server or a PC, you would need a full dual core processor to run one camera. So, you can see why it’s never been shown before. It is impractical for other technologies.

The other industry first we showed is something we call IQTrack. It uses the video analytics to automatically track and zoom on objects in the field of view. Here’s a picture:

This is different from PTZ camera tracking. If you look at the lower left of the picture, you will see that the whole field of view is still being recorded and it shows where in the scene you are zoomed into. So, you can always go back later and pick another part of the video to look into.

The other unique thing is, if many people are in the area, you can click on one person and it will zoom in on and track just that one person. That’s never been shown before either.

Watching it, you can immediately see that there is no comparison between watching video that is automatically zooming and tracking on important objects, versus static video cameras. It pulls your eyes to exactly what is important. I think this is going to be very popular for megapixel cameras.

The 1080p cameras we sold will also be the first cameras to ship with a new imager from Sony that has some amazing low light performance. We are still testing it, but it looks to be 2X-4X better than any other multi-megapixel imagers used in the security industry.

And of course, the camera we showed included a hard drive so that you can store 1-2 months of high quality 1080p video. This solves the bandwidth problem for megapixel cameras, since it needs no bandwidth to record, and eliminates the need for external storage in most cases.

Now that true megapixel analytics have arrived, I think it is going to set the standard, and I think it offers incredible visual value to megapixel cameras, even if you don’t want the analytics for detecting alarms.

http://ipvideomarket.info/report/sd_cards_video_surveillance_storage

This plays right into my most recent post on intelligent storage in the camera. The webinar I held last week had record attendance, so there seems to be interest in this subject.

I’ve been watching this shift in storage technology for the last few years, and I went through a lot of the same math that John spells out so well. I’d like to add a few added twists to the topic that show why I’ve come to a different conclusion.

The most important comparison that John points out is the cost of a 1 TB hard drive versus an 8 GB or 16 GB SD card. When you look at the cost in $/GB, the SD card is 21X more expensive. So, even though flash memory is dropping in price faster than hard drive memory, how could it ever catch up in the next five years?

Here’s an important piece missing from this comparison: You can’t just plug in your hard drive into the network, you need a storage server. When you get done adding the storage server, which includes all the hardware needed to manage lots of streams from many video cameras onto the hard drives, then the cost per TB is much, much higher. The typical end user price I’m hearing today is around $2,000. There is a wide range in pricing and options here, but this is the average I’ve heard.

That’s 20X more than the price of the 1 TB hard drive. Since the cost of the SD card is the total cost needed, this wipes out most of the cost difference with using SD cards compared to hard drives in a storage server.

If you put the hard drive in the camera directly, as we do in our iCVR, then you don’t need all of that server overhead. That’s why I think that today, putting a hard drive in the camera, ends up being the lowest cost storage solution.

For the next big factor that changes the math, take a look at this whitepaper by Uptime Institute:

http://www.uptimeinstitute.org/wp_pdf/%28TUI3008%29Moore%27sLawWP_080107.pdf

This shows a growing problem with the costs of data centers. It has become a lot more expensive to support servers these days than it used to be. Since the latest servers are far more dense in storage capability, and far more powerful, they also draw a lot more electricity to run, and they generate a lot more heat, which requires more electricity to cool the rooms down and higher support costs. On top of this, the numbers of servers in data centers are growing fast.

Take a look at Table 1 on page 3. It shows there that for every $1,000 you spend today on servers, there is a total cost of $3,510 over three years. That means you now need to pay the cost of your server over again each year, for overhead, power, and replacement of hard drives as they fail, in today’s data center. This is based on conservative electricity costs. In many parts of the world, it is going to be higher.

This includes the costs of hard drives failures, and that’s another big factor here, since flash memory lasts a lot longer. In fact, storage failure in cameras should become rare, while hard drives in DVRs and servers fail after 3-5 years.

While this overhead, electricity, cooling, support and hard drive failure costs aren’t usually calculated into the cost of servers when video surveillance systems are bid, that should change. IT managers realize this is a growing issue and that cost needs to be added into the true total cost of ownership when comparing.

These issues of power consumption and data center overhead, plus failure rates, is one of the reasons that solid state storage is expected to make serious inroads into replacing hard drives in storage data centers. The cost of the overhead and electricity and support has become bigger than the cost of the servers. Solid state storage uses far less power, has longer life expectancy, and can run at higher temperatures reliably.

The use of solid state drives is just now starting to be used in data centers, mainly for special applications, since cost is still higher. But most projections I’ve seen say that in 5 years, this is going to change and SSD will start replacing hard drives.

We can expect to see the same thing happening in laptops, since lower power consumption means longer battery life, and with the rugged abuse that laptops get, solid state storage makes a lot more sense from a reliability standpoint.

In five years, the growth rate of hard drives should start slowing significantly, as solid state memory starts taking over.

These are some big factors that clearly push the equation in the favor of SD cards as they drop in price, and they get large enough to provide 30 days of storage. They aren’t quite there yet.

The latest reports I’ve seen say that 64 GB SDXC cards will be available early next year, and 128 GB cards will be introduced by the end of 2010. If this is true, we could see 1 TB cards being introduced in 5 years, although I think it might take a year or two longer than that, since the rate of advancement will probably slow down a bit as the demand for such large storage cards will not be as high.

I agree completely with a lot of the other points that John raises: That video management software can’t deal with storage in the camera today. This needs to be addressed. Also, the storage on most SD cards in cameras cannot be accessed like you would a DVR (Mobotix is the only exception I know of, besides our own cameras with built-in storage). In fact, some cards need to be removed physically to access the stored video. So, this is a long way from ready for most cameras.

However, the cost impacts above suggest to me that SD cards in IP cameras (or microSD cards) will become the standard in five years. The largest megapixel cameras may require hard drives, but most of the cameras will have plenty of storage capability.

This is of course just a guess, and the thing about technology predictions like this is that you have to always wonder what factors you overlooked. Will a new technology be introduced that changes everything? Or does someone solve the problems with hard drives and server overhead costs?

However, not many realize all of the reasons why it is so compelling.

For example, the whole idea for centralized recording of video comes from the traditional data center. It is natural to think that what makes sense for data centers is also the right solution for video storage.

It turns out, however, that this is not the best architecture for IP surveillance, which is why the industry has run into so many problems with bandwidth, storage costs, system reliability, etc.

Storing video in DVRs from analog cameras is actually closer to the edge of the network than IP cameras with server storage. IP cameras have actually been going the wrong direction. The answer that makes everything far simpler, and overcomes many of the biggest problems, is to go the other way and move storage and intelligence further to the edge, right into the camera itself.

It makes more sense to treat cameras as sensors, not just data sources, because sensing is what they are really about. This becomes much more obvious once you include video analytics in the cameras. Then it becomes much easier to see why sensor systems work better with distributed storage and intelligence. Where do you want to do the sensing? Back at a central location or right there at the sensor? Why send 100% of the video back, when you only access 1% of it? Why waste 100X as much bandwidth as you need?

I just finished a whitepaper that describes why intelligent storage in the camera is going to have a big impact on IP video systems. It’s a look at the future of where technology is going and why.

You can download the whitepaper here:

http://www.videoiq.com/products/resource-center/whitepapers/

I will also be holding a free webinar on the subject in a few weeks. Here is a link to register, if you are interested:

https://event.on24.com/eventRegistration/EventLobbyServlet?target=registration.jsp&eventid=153908&sessionid=1&key=BAB80E0D27E9D00175CACB0907737599&partnerref=july8&sourcepage=register

The leading video management systems companies are beginning to recognize the importance of intelligent storage in the camera, but I think it is going to end up being a much bigger trend than they realize. There are a number of future shifts in technology that are going to make it even more compelling. For example, solid state storage, megapixel cameras and the move to video web services.

Some have suggested that as bandwidth gets easier to find and storage gets cheaper that these will make centralized storage and intelligence more popular, but this is all based on thinking of cameras as if they were data sources, not sensors. Yes, there are lots of PC applications and data that run much more efficiently in the data center, but sensor systems work much better at the edge. Everyone has simply been looking at this the wrong way.

Video intelligence offers a lot more than just detection. It changes the whole system for the better.