“Me Too” Products - Being wise about the products you present to end users

“Me Too” Products

Being wise about the products you present to end users

For manufacturers to play within the commodity space, they need to provide the most features, ease-of-use and the best reliability, camera versus camera. If that is accomplished at the going price, you have everything you need to compete in that arena.

Leadership comes from recognizing the specific needs of an end user and innovating better ways to meet those needs affordably. An example of potential industry leadership is the practical application of what have become known as “edge surveillance products.”

Understanding “Edge”

I think that my definition and concept of edge is very different than anyone else. I loathe the phrase “edge now;” it’s been perverted and abused into being something that is so constrained and limiting that it’s become useless as a definition of what I think edge can be.

The current structure of how IP video is generated, managed and consumed is backwards and behind the curve when viewed in context to other analog, digital transitions. All the security industry has created thus far is a faster, more expensive VCR and a higher resolution CCTV camera. The paradigm of how everything works and knits together still intrinsically follows that same tired, wholly-broken 1970s model. In order to progress and step into the 21st century, this must stop.

A camera is simply a sensor that collects video, but a modern IP camera has a full 32-bit server with more memory and computing power than the personal computer I had when I was studying at a university. Imagine if we said that a mobile phone could only be used for phone calls simply because it was called a phone? The same concept and restriction is being pushed onto cameras.

Edge, for me, means autonomy. Personally, I prefer the term “hive” rather than edge since it has a better connotation of a system of individual elements that are all working autonomously, yet collectively, to get a job done. Please note that my vision is impossible if I’m constrained to just a camera; the right VMS is a canvas on which to paint. My concept may still be a bit too far ahead of the curve in terms of what the security industry can digest, so it’s best to lay out the edge in steps and as a roadmap of what will come:

Storage. If a camera needs storage for the video it is collecting, there are many assets it can use. The one that has been pushed by most vendors today is using local or edge storage in the form of an SD card, or in our case, multiple SD cards. That’s great, especially given the fact that we at ISD/Digital Watchdog (ISD/DW) can put up to a full Terabyte of storage on a camera and that’s only one possible destination. Other popular destinations would be a conventional PC server, nosql ORACLE database, NAS box or Amazon EC3 cloud storage. Fundamentally, it doesn’t matter what or where it is; what does matter is the size of the data that you’re trying to move around and making smart choices about bandwidth management. Data shouldn’t be constrained to a single repository or a single function, and all devices need to work together to ensure that everything is taken care of and that no single entity fails or is a point of failure.

One of the jobs of a camera is to make sure that the video it is generating gets stored. It should be empowered to use any asset that it has access to in order to fulfill that role. An edge camera sending video to a standard PC is perfectly legitimate, but if that connection fails, it has an obligation to switch to its local repository. If that fills up or breaks, then it should switch to another camera and use its SD card instead. Arguably, if the device is in a critical area, it should be doing this all the time and sending the video to all destinations simultaneously. It has the responsibility of checking in with its hive mates periodically to make sure they aren’t having problems and are still visible on the network.

The point is that cameras should no longer be devices that blindly spew out video in a fire-and-forget mechanism. Instead, they should be given the responsibility to ensure that their payload is delivered reliably. Think more of an asynchronous, peer-to-peer architecture where cameras and servers have equal footing and a responsibility to cry if any of them are unhealthy.

None of that exists today, except in our lab.

“Army-of-one” model. All implementations for the moment are in a relatively conservative manner, but that will blossom and flourish with better IPVMS platforms. The camera hosts some form of the server on itself and uses local storage to write video. Current systems have this as an army of one, meaning there’s no interaction between the cameras, nor is there any interaction with a conventional server.

The army-of-one issue is where most consumers have a significant amount of heartburn about deploying edge:

  • What happens if the camera gets stolen?
  • What happens if the SD card breaks?
  • What happens if things stop?
  • How do I know that it failed if the camera fails silently?

All are good questions and consumers are smart to think about such things, except for the fact that if a camera is replaced with a server and it breaks, now multiple cameras aren’t recording.

While it’s limited, this model is useful for applications where you don’t have the ability to have a relatively high power server running in a remote installation. Construction site monitoring or remote/covert surveillance are great applications. The fact that ISD/DW cameras are low power (2 watts) makes it easy to deploy cameras using battery/ solar power. These days, a 64GB card can provide almost a week of storage, if recorded on motion.

A properly designed edge system is more scalable, fault-tolerant and has the ability to adapt to other requirements. It doesn’t have to be more expensive than a conventional “head only” system since most of the concepts I’m talking about are largely software based, using a different paradigm of how the security system gets deployed.

Applications. This is where edge cameras have an immediate advantage over their acrophobic brethren. It is summed up with one word: scalability.

Analytics have traditionally been run on conventional PC servers and have had a tendency to over promise and under deliver. Smart folks have long figured out how to use some clever math to determine what the camera is looking at. They’re usually prototyping with a single camera running on a big iron PC with tons of RAM. Those same people demo it to their sales team who immediately say, “Wow! I can sell that!” Then, they get venture capital funds to sell it to the world. Everyone’s happy; they do demos to potential customers and install test deployments. All is good. The challenge comes when their customer wants to use more than a few cameras on the same PC. Here is the awkward conversation about having to buy more big iron servers; it’s just not scalable.

As a good friend of mine, who lead the engineering team of a leading analytics company, said, “You can’t go out of business fast enough being an analytics company.” Most have become VMS companies with optional analytics to keep alive the dream of what they started. The critical flaw, with the possible exception of a select few companies: Analytics companies all wanted to run on generic cameras, hoping that the various camera companies would help sell their solution. It never happens. Bad things happen.

Change the Rules

The consumer electronics industry has led to some stunning innovations and advancements in mobile computing. The fact that you can play Angry Birds on your phone is a prime example. As for the security industry, as a whole, they’re focusing on making the camera equivalent of a No. 2 pencil, so they’re unwilling to put any meaningful investment of technology into the cameras. This means they can’t do anything intelligent at the edge and no one is able to escape the black hole that is commoditization and consolidation.

With modern CPUs that are targeted for mobile devices, it is possible to run meaningful analytics at the edge. Right now, business analytics and intelligence for marketing applications are all the rage.

We announced at the 2014 ISC West show a partnership with Prism Skylabs, and at the ASIS 2014 show, deployment with their analytic fully running inside our next generation cameras without any compromises. Why is this important? Why do I feel this is critical to their success? Scalability and the elimination of servers.

With the kind of deployments I have described, every camera has the processing power it needs to be successful. Whether deploying three or 3,000 cameras, it doesn’t matter. It’s scalable, deterministic and eliminates the need for expensive servers. It is a win for everyone, even IT departments that tend to be suspicious of any third-party servers installed on their networks. They are correct to be nervous, given the threat of malware that inevitably gets uploaded, not to mention inappropriate activity that often coincides with a PC that has a screen, keyboard and network connection.

The camera is an appliance. It has everything it needs to automatically configure and deploy itself when attached to the network by integrators. That user experience can be simplified to a “lick-and-stick,” analog-like deployment. It is simplicity that just works.

This article originally appeared in the December 2014 issue of Security Today.


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