 Kind of an interesting situation here, we've got a demo coming up. Is this the Silver Spring demo? Okay. Okay, so we've got a demo from Silver Spring. I know Frank Moab is one... I'm sorry, what's your last name? Hmong, M-O-N-G. Hmong, oh sorry. Okay, Frank, Frank Hmong. It's my big name. Mel, how you doing? Hey, nice to meet you. Do you want Mel to sit there or me to sit here? Frank Hmong and Mel? Mel Kiers. Go ahead, Mel Kiers, sit in that seat. Gears, G-E-H-R. Has gears in a car. Gears, great. Okay. So if I'm going to show this meter, what's the... So you've got a colleague who's going to drive a demo at the station. So tell me about Silver Spring and Google and Google Earth and all this cool stuff that you guys are doing. Silver Spring Networks, basically in layman's terms, provides the internet for utilities. I know we all know what the internet's due for us today, but the utilities kind of miss that and now they want their own. And what we provide is the hardware, the software, and the services that enables the utilities to build this thing called the smart grid. And the smart grid, think of it as internet for utilities. We allow the utility to connect directly to the consumer's home and provide services, applications, updates directly to the consumer, much more engaging and proactive. And one of the things we want to show you later on in the demo that Mel's going to provide is that visual. What does that look like? And the benefits of this is huge. For the utility, our customer, they get to be more proactive. They get operational efficiency. And they get to really engage with the customer. From a consumer perspective, our customers that can operate within our network and our smart grid, they get the benefits of energy efficiency. They get to reduce their carbon footprint. And of course, they get to decide for themselves how they want to use energy and how they want to conserve energy. So huge benefits. Do you think we can apply this to healthcare and solve that problem too? I wish we could and maybe we can someday. But the concept applies, right? Allowing the consumer to take control of his or her own consumption and identify ways in which they can optimize their consumption and their use to save energy overall, lower costs, et cetera. Yeah, in Silver Spring, even though we're a quote-unquote start-up, we're doing quite well. We have 16 utilities across five different continents around the world. And we're growing rapidly and having a great time. So what are some of the bigger utilities that you're working with? So for example, Pacific Gas and Electric, Florida Power and Light are two examples of our customers. And we have some customers in Australia as well. Okay, so California obviously, very sensitive to that issue. Very sensitive, yes. Good. Okay, all right, so we've got a demo. That's right. You want to take us through and describe it? Well, first of all, the smart meter story starts with a smart meter. So basically this is an electric meter, but it's a digital electric meter that has a card in it that's a radio transmitter. It's a lot different than my meter. Yeah, probably. Yours is no mechanical meter that sits around. This one doesn't spin. Okay. But it communicates with the utility as many as 96 times a day as opposed to the utility used to read it once a month. So hence big data who would have thought around you is all of this data. So that's little data. So the old meter was little data. This is big data. Okay, yeah. And so some examples of what we do with that, we have some samples in Google Earth. First of all, we deploy these in neighborhoods and in high rises. On the demo here, you'll see a high rise and this high rise is in Chicago. So we're going to tour downtown Chicago flying by the Trump Tower and you'll see two high rises. This is a 150 North Wacker. These buildings have meters scattered throughout the floors. The line show you the RF signal that's propagating across the river and then you'll see all of the meters in the building and the communications up through the center of the building. So this is a mesh. This gives the meter an opportunity to communicate whatever is the best path to send data back to the utility. So it's making those optimization decisions constantly, second by second. Basically you take out your old mechanical meter, you plug this meter in and you hang and run. It discovers all its neighbors and automatically communicates back to the utility. So you're saying the infrastructure is a take out the old, put in the new and... Pretty much. Now you do deploy what's called an access point around about 5,000 meters. That access point uses cellular backhaul. So an ATT or a Verizon or a Sprint backhaul. So once that access point is in place... It's hang and run. Utilities can deploy thousands of these a day. Go down a street or up a high rise. The next thing we did is that once you have these meters in place, the utility can now be proactive as opposed to reactive. So they can look at things like your voltage on the hot summer's day and see how the voltage is. So here we have a mesh of 130,000 meters over this city of Chicago on one of the hottest days of the year. And so the utility can now look at low spots in the grid caused by excessive use of air conditioners and be proactive and go out and fix the infrastructure before it causes problems with the customers. This will also help when electric vehicles are more prominent because electric vehicles will be adding loads that are unexpected loads over time. So that plane there is basically the nominal voltage and you see peaks and valleys based on where the voltage is high or low. So that nominal voltage peak might indicate a threshold of potential problem. Yeah, the lower voltage would indicate that there is excessive load in that particular area or problem in the grid that they didn't know about that they had to go out and fix. It's probably important to note that this data, the magic we're seeing here, is as a result of us using Green Plum. EMC's Green Plum allows us to really aggregate the data, a lot of data all at once and produce some of these fantastic images and reports and the visualization of big data here you see. So compare that to maybe using a traditional data warehouse. Would you be able to do it using a traditional data warehouse? Well, you'd have to have a lot of patience because instead of queries coming back in minutes, they'd come back in days. Okay, so it really couldn't be optimized for that sort of real-time decision-making. Well, and the problem with analytics is sometimes you don't know what you're looking for, so it's an exploratory process. If you have to take hours to get one answer back, you get pretty bored with the exploration process. Yeah, so it's like the old programming days where we used to have to wait for the mainframe. Stick your cards in it back and wait for it to come back tomorrow. I got another 45 minutes before I could solve that bug, so kind of a similar thing going on here. Now, and finally, the other thing these meters can do is when an outage occurs, it will, in effect, ET phone home. They'll send a message saying that they've lost power. Here's an actual outage. You see the green dots coming back. Those are meters that are reporting back. They have power restored, and so the utility had an outage. There's actually a squirrel got across the feeder and tripped the feeder. You see there's one section that's still out. Now all of the customers are back. Squirrel's dead. The squirrel's dead, by the way. So this allows the utility to know exactly all the meters that are out and when they have power back. So it's more accurate as far as they're dispatching of their crews and they don't leave a customer stranded they didn't know about. How much data are we talking about here that you guys brought? So typically each one of these meters has anywhere from four to 30 channels. Those four to 30 channels are read every 15 minutes or every half an hour. Utilities have four to five million customers, so you do the math. A year's worth of data times five million customers times 365 days times 96 readings times anywhere between four and 30 values. That's a lot of data. It's a lot of data. And utilities want to look at long-term trends so they'll do multiple years. How was last year compared to this year from a voltage standpoint? Okay, and you're able with your infrastructure to operate on all those data sets you're not having to... Well with green plumbing, prior to that we were not able to do that. So this is game-changing. It is game-changing. It's changing utility from a reactive state to a proactive state to be active to the customer and call them up ahead of time saying we're fixing a problem you didn't know about. This is with green plumbing. This is definitely the killer app of the smart grid. The benefit goes beyond just utility. Consumers like us, ultimately, get better updates on what's happening. We don't have to call the utility when the power goes out. Utility knows. So where are you guys at? You said you're a startup. Tell us a bit more about Silver Spring now. Sure, we're based in Redwood City and started in 2002. We've got 600 people. You're an Oracle country. You're using Green Plum. That's kind of cool. Oh, we use Oracle also. Oh, okay. So we use both. But Oracle couldn't do this is what you're saying. Everyone's got some positives. Yeah, and fairness. You wouldn't put Green Plum into your Oracle applications. That wouldn't be the right use case for that either, would it? Yeah, well, we're really happy with what we have and Green Plum's done a great job for us on the analytics side. Yeah, okay, so in Redwood City, when did you get started? 2002. So you're up, running fully funded. Yeah, fully funded, doing great. Got lots of customers. Lots more to come. Outstanding. Yeah. Well, Mel, Frank, thanks very much for coming on the Cube. Sharing this great demo with us. Good luck with Silver Spring. You must be working with my friends down at Austin Energy, right? I mean, come on. Those on your shortlist? They are. They're heavy to the smart meters. Have them call us. Andres Carvalho, CIO down there. What do you know him personally? I do. Seriously, I'll give you my card. All right, good. Okay. He'd be all over this. Definitely. All right, good. Thank you. All right, man. Thanks.