John Graff, vice president of corporate marketing, was the emcee for Wednesday’s NIWeek keynote address. He reminded attendees that at an earlier NIWeek several years ago, futurist Paul Saffo had said, “… We’re going to put eyes, ears, and sensory organs on our computers and our networks in absolutely unprecedented ways. We’re going to ask them to observe and manipulate the physical world on our behalf.” This is precisely what the industrial IoT (IIoT) is all about—especially the second half of the statement. Where the IoT may facilitate consumer-related diversions such as Facebook, the IIoT fundamentally will change the way things are made and used.
Having heard from Dr. Truchard on day one, we could look forward to comments from Jeff Kodosky on day two. The father of LabVIEW, as usual, had some thought-provoking insights. Again, the IoT and IIoT were central to Kodosky’s remarks, especially so as the IoT already has an estimated 3.2 billion users, and 50 billion devices are projected to be networked by 2020.
Working with Big Analog Data, according to Kodosky, can be compared to the way the human brain processes vision. Some processing is done directly in the retina even before the 100 million fibers in the optic nerve transport signals to the brain. There, data analysis proceeds in stages, specialized portions of the brain handling different aspects—even with a separate area for facial recognition. The parallel with digital computation is not hard to draw. Specialized algorithms running close to the edge of the system preprocess huge amounts of raw data to reduce the amount of work required at subsequent stages. And, LabVIEW’s dataflow model continues to be the best way to describe these processes.
An example showed more directly how NI technology had been used to solve a big data problem. As Kodosky explained, engineers on London’s Victoria subway line used CompactRIO in a predictive maintenance system. The line has 385 separate segments that facilitate dense but safe train scheduling. Nevertheless, the train sensing circuitry sometimes failed, and although it always failed safe by design, the line shut down until the fault could be found and corrected. With the new system, each section is monitored for fluctuations from its previously benchmarked normal behavior. If a significant deviation occurs, maintenance can be scheduled without disrupting service.
Examples
Keeping with Ni’s overall 2015 themes of 5G, IoT, and Big Analog Data, representatives from nine companies and Dr. Andrea Goldsmith from Stanford University then added their own slant to the themes and their interactions. Goldsmith suggested that with a reliable network, robotic surgery could be carried out remotely. Similarly, with a reliable network, driverless cars will share data and eliminate the accidents caused by human error.
Goldsmith related the usual 5G metrics of 1,000x more sensors, higher speed, and less latency. She said lots of MIMO would be required as well as mm-wave technology to get the bandwidth, and 5G also needed to be more energy efficient. These comments may have been keynote audience specific, however, as several aspects seemed far from certain in a later 5G expert panel session in which Goldsmith also participated.
Dr. Ghosh and Mark Cudak, both from Nokia, discussed their recent mm-wave research success. A year ago, their experimental prototype achieved a 200-m range with a 2.3-GHz bandwidth at 73 GHz—near the middle of the waveguide E band. Today, on stage, they demonstrated a 10-Gb/s data rate with <1ms latency using 2×2 MIMO.
Michael Lee is director of testbeds for the Industrial Internet Consortium—a collection of about 200 companies that benefit from collaboration as well as the consortium’s organized interoperability testing. The members’ products can be subjected to proposed as well as adopted test standards via well-documented testbeds. NI’s technology supports the testbed effort.
Predictive maintenance was the topic of IBM’s Greg Gorman. NI’s InsightCM Enterprise deals with rotating machinery. IBM’s Maximo software application goes further and might be a better solution for more varied assets and where more scalability is needed.
Cisco’s Weston Sylvester addressed the challenge of “connecting the unconnected.” Several micro-grid-related capabilities were described that have been incorporated in an outdoor-rated robust router. These include controlling solar energy storage, peak load shaving, a special “storm mode,” and monitoring to reduce energy theft. The underlying approach to all these functions is to put the necessary algorithms close to the source so data reduction takes place there.
Frank Hanzlik, director of the Wireless Connectivity Group at Dell, confirmed that wireless communications had become ubiquitous within Dell products, extending even to a wireless docking station. And NI’s David Hall, standing in for a Ruckus representative with travel delays, described how that company had provided simultaneous wireless coverage for more than 70,000 fans at a sports stadium. The Ruckus products with BeamFlex + technology are tested on 35 NI systems with VST flexibility.
Have you recently bought some jewelry with “Intel Inside?” The company’s Mino Taoyama described the very small “Curie” module—about the size of a dime—made possible by recent improvements in component size, power, and performance. The module is embedded in the MICA smart bracelet that provides 3G radio and GPS capabilities. Because the fashion industry demands a high mix of styles, test must be flexible. NI’s TestStand is being used for this project because it promotes code reuse and speeds up development.
The GoPro wearable camera is as impressive for the mind-blowing physical exploits its wearers perform—pictures from dirt bikes, ski jumps, and inside of tubular waves—as it is for the exponential growth of the company. From a couple of people 10 years ago, it’s grown to employ more than 1,000 and has $1.4 Bn in annual revenue. NI powers the test setups.
The example receiving the largest spontaneous cheers was Mike Campbell’s description of PTC’s 3D solid modeling CAD system. Using an example of a mountain bike, he showed how the company’s ThingWORX merges sensor data with reality. While imaging the bike from an iPAD, sensor data simultaneously and in real time was superimposed on the image as though it were an engineering drawing, complete with values and arrows. This was by far the most graphical example of connectivity through the IoT.
Finally, Bob O’Donnell from Techanalysis Research discussed his impressions of LabVIEW as an “engineering OS.” Like a software OS, LabVIEW abstracts underlying detail so that you can work within a unified platform of tools.