DEVNET-1163 Data in Motion APIs

Editor's Notes

• #7: This new fog layer will create a paradigm shift in the network infrastructure. Today, businesses deploy three disparate devices for their networking, computing, and storing. Fog introduces a concept to combine all those devices into a single unified platform—instead of having to manage three things, companies will just worry about one. Fog also shifts how data is processed. Today, data is first transmitted to the cloud and stored. From there, it’s analyzed and commands are sent to act upon that information, then operators are notified. Fog helps overcome the costly need to constantly move data around and allows analysis and notification to occur before the critical information in stored to meet compliance and regulation policies. We believe this is all critical in accelerating the Internet of Things and today we’re excited to share with you our role in making this reality.
• #9: Whether it’s a passenger train in a bustling city or a freight train slithering through the mountainside, news of derailment is a tragic story. You may have heard about the fatal train accident in New York City’s Bronx or the recent incident in Philadelphia where a train hauling crude oil was dangling over a river. The US federal government has seen more oil spilled in rail incidents in 2013 than was spilled in the nearly four decades since it began collecting data. The demand for preventative measures is greater than ever. Train derailment is typically due to equipment failure, specifically in the ball bearings of a wheel. Today, train operators have routine schedules to swap out wheels and engines without fully knowing if the equipment is used beyond repair. Or in worse case scenarios, damaged equipment is not replaced in time to prevent failure and accidents. In addition to performance, train operators face fierce competition from alternative transportation providers and must find ways to offer better amenities and services to retain and attract new passengers. These are just a few of the concerns rail companies are hoping IoT and Cisco will address.
• #10: So if we go back to the examples we shared with you earlier, an 819 router sitting on a freight train can monitor the ball-bearings and monitor the utility of bearing to let you know if its overheating or has worn down to 35% of useful material. An alert can be sent to the train operator notifying him to pull over at the next available station or to stop and repair the wheel. UK Rail, $21B per year to operate
• #11: If oil companies are not stressing over potential spills from train derailments, they fear the damage and lost revenue from a major pipeline spill. In some parts of the world, oil pipelines stretch across thousands of kilometers carrying hundreds of thousands barrels of oil per day. Today, pipeline leaks are discovered days after the initial spill and only because someone in a near by community complains about a foul odor in the air. Pipelines aren’t the only things suffering from undetected leaks. In recent news, a storage unit at a chemical plant spilled 7,500 gallons of toxic substance into the ground, leaving 300,000 West Virginia residents without usable water for days. These are three of many examples we’ve heard from our customers and we believe that they can overcome these challenges by connecting their trains, traffic lights, or pipeline sensors to the network. These companies need more than the ability to connect, they need a way to manage the terabytes of data and send commands to respond to critical alerts without compromising the speed of sending the commands and adding significant costs to move the data around the network. This requires a new way in how data is computed and stored.
• #12: Cisco IOx offers a way to deploy data aggregation and other critical applications across those thousands of kilometers of oil pipelines. Sensors can monitor pressure measurements, flow rates, or video footage of the surrounding area. If pressure were to drop or if the video captures fluid pooling on the ground, commands can be sent right on the pipeline to slow down the pumping of oil and send an alert to dispatch the closest maintenance crew.
• #13: Manufacturing plants use a lot of energy and, when they go above a certain utilization rate, they’re charged more per unit of energy. So if they can figure out how to even out their usage to avoid spikes, they can save money. Right now, most manufacturers have a separate IT set-up and a separate network for the manufacturing plant versus headquarters. To shave those energy peaks you need to know a few things. First, you need to know what’s going to be built when. That information comes from the “Master Execution Scheduler” which is kept on the proprietary manufacturing network. But you also want to know what’s been committed to customers so you don’t save money on energy yet drive away customers in the process. That information is in your ERP system on your corporate network. And then you want to know how changing the schedule might affect labor costs, so you don’t lose all the money you saved on energy, making the whole exercise pointless. For that, you need information from your HR system, also on your corporate network. Then you need to analyze the information.  
• #14: Once you’ve brought all the right systems together, you can build an application with thresholds and policies that alert operators to an approaching peak and show gaps in the schedule—times they could push the production load to. Or they can shift production to another plant with more capacity. But that requires adjusting supply chain, MRP, and the factory build plan to compensate without impacting customer commitments or desired inventory levels. Or they can check the power co-generation system to see if they can keep production high but use co-gen energy to avoid the peak. But something interesting happens, once you’ve created your killer app….