Category Archives: Sensors

Apple’s New Big Bet: Augmented Reality

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ARKit platform puts it in a race with Facebook, Alphabet and Snap and fuels industry beliefs that it will eventually develop glasses

A demonstration of Apple’s ARKit technology on an iPad Pro on Monday. The system uses camera data to find horizontal planes in a room and estimate the amount of light available.

A demonstration of Apple’s ARKit technology on an iPad Pro on Monday. The system uses camera data to find horizontal planes in a room and estimate the amount of light available. PHOTO: DAVID PAUL MORRIS/BLOOMBERG NEWS

Apple Inc. AAPL 0.60% set its sights on a new target: becoming the world’s largest platform for augmented reality.

The ambitious announcement, which was overshadowed by the introduction Monday of the HomePod speaker, plunges Apple into a race against Alphabet Inc., Facebook Inc.,FB 0.20% Snap Inc. SNAP -3.93% and others to conquer an emerging technology that uses cameras and computers to overlay digital images on a person’s view of the real world.

It also bolsters the belief among many industry observers that Apple will build new augmented-reality features into its coming 10th-anniversary edition iPhone, and eventually develop glasses that relay information about the world so people can view maps or restaurant menus without pulling out a device.

Augmented reality shot to prominence nearly a year ago following the release of “Pokémon Go,” a game in which players scoured the map of the real world, with the help of location-tracking technology, to find digital monsters superimposed through the smartphone screen. The technology is different from virtual reality, which uses computer headsets to create fully immersive digital worlds.

Roughly 40 million people in the U.S. are expected to use augmented reality this year, up 30% from last year, according to research firm eMarketer. It estimates the total will rise to 54 million in 2019.

In a 2.5-hour keynote, Apple announced a slew of new hardware and software products. WSJ’s Joanna Stern recaps what you need to know about the most important announcements.

Craig Federighi, Apple’s head of software, demonstrated the potential of Apple’s new technology platform, ARKit, at the company’s annual Worldwide Developers Conference keynote Monday.

While viewing a table on stage through an iPhone screen, Mr. Federighi added virtual images of a steaming cup of coffee and lamp. The images appeared to rest directly on the table, recognizing the real-world surface rather than floating above it.

Apple Chief Executive Tim Cook has been a big proponent of augmented reality, saying he believes it will have broader success than virtual reality because it is less isolating.

Several companies are already working on augmented reality, including headsets in development from Microsoft Corp. and Magic Leap Inc. Alphabet’s Google Tango platform has been available on some smartphones for a about a year.

Apple’s ARKit, though, has the potential to democratize the technology by bringing it to roughly a billion devices without requiring separate hardware or software, as some competitors do. The company says the system uses camera data to find horizontal planes in a room and estimate the amount of light available.

“It’s a seminal event in the journey toward AR that Apple’s come out and shipped something,” said Matt Miesnieks, co-founder of 6D.ai, a computer-vision startup. He expects developers to use the software because of its relative simplicity and potential to reach across Apple’s large user base.

IKEA International A/S and Lego A/S are already working on augmented-reality apps using ARKit that could allow people to visualize furniture in their home or a virtual image of Lego Batman, Mr. Federighi said.

Representatives of Wingnut AR, an augmented-reality studio from “Lord Of The Rings” director Peter Jackson, showed an ARKit-based experience, seen through an iPad, in which airships battled in a virtual town square that was digitally dropped on a real table on stage, with the audience visible in the background.

Apple’s announcement came two months after Facebook opened its augmented-reality tools to developers. CEO Mark Zuckerberg said he expects the nascent technology to open the world to a new world of apps and services.

Facebook’s smaller rival, Snap, popularized simple augmented-reality tools that overlay bunny ears or dog noses on users’ faces. It also allows users to add special effects to photos and backgrounds.

By creating an augmented-reality tool kit for developers, Apple could spur its more than 680 million iPhone users to share augmented images through its iMessage service rather through Facebook or Snapchat, developers said.

ARKit indicates Apple solved a difficult technical problem—finding a way to use cameras and sensors in an iPhone to track the outside world, said Mr. Miesnieks. He said the same sensors and algorithms would run a pair of glasses, bolstering his belief that Apple plans to launch eyewear in the future.

Apple declined to comment on whether it could develop glasses.

“They’re clearly getting developers ramped up for this,” said Paul Reynolds, founder of Torch 3D, a startup focused on 3D-app development. “I’m sure for the iPhone launch they’ll have nice content around it.”

The Rise of the Smart City

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Officials are tapping all kinds of data to make their cities safer, healthier and more efficient, in what may be just the start of a sweeping change in how cities are run.

As city officials across the country begin to draw on data about income, traffic, fires, illnesses and more, big changes are already under way in leading smart cities.

Cities have a way to go before they can be considered geniuses. But they’re getting smart pretty fast.

In just the past few years, mayors and other officials in cities across the country have begun to draw on the reams of data at their disposal—about income, burglaries, traffic, fires, illnesses, parking citations and more—to tackle many of the problems of urban life. Whether it’s making it easier for residents to find parking places, or guiding health inspectors to high-risk restaurants or giving smoke alarms to the households that are most likely to suffer fatal fires, big-data technologies are beginning to transform the way cities work.

Cities have just scratched the surface in using data to improve operations, but big changes are already under way in leading smart cities, says Stephen Goldsmith, a professor of government and director of the Innovations in Government Program at the Harvard Kennedy School. “In terms of city governance, we are at one of the most consequential periods in the last century,” he says.

Although cities have been using data in various forms for decades, the modern practice of civic analytics has only begun to take off in the past few years, thanks to a host of technological changes. Among them: the growth of cloud computing, which dramatically lowers the costs of storing information; new developments in machine learning, which put advanced analytical tools in the hands of city officials; the Internet of Things and the rise of inexpensive sensors that can track a vast array of information such as gunshots, traffic or air pollution; and the widespread use of smartphone apps and mobile devices that enable citizens and city workers alike to monitor problems and feed information about them back to city hall.

All this data collection raises understandable privacy concerns. Most cities have policies designed to safeguard citizen privacy and prevent the release of information that might identify any one individual. In theory, anyway. In reality, even when publicly available data is stripped of personally identifiable information, tech-savvy users can combine it with other data sets to figure out an awful lot of information about any individual. Widespread use of sensors and video can also present privacy risks unless precautions are taken. The technology “is forcing cities to confront questions of privacy that they haven’t had to confront before,” says Ben Green, a fellow at Harvard’s Berkman Klein Center for Internet and Society and lead author of a recent report on open-data privacy.

Still, cities are moving ahead, finding more ways to use the considerable amounts of data at their disposal. Here’s a look at some of the ways the information revolution is changing the way cities are run—and the lives of its residents.

Spotting potential problems… before they occur

Perhaps the most innovative way cities are employing data is to anticipate problems.

Consider the risk of death by fire. Although declining nationally, there still were 2,685 civilian deaths in building fires in 2015, the latest year for which data is available. The presence of smoke alarms is critical in preventing these deaths; the National Fire Protection Association, a nonprofit standards group, says a working fire alarm cuts the risk of dying in a home fire in half.

New Orleans, like most cities, has a program run by its Fire Department to distribute smoke detectors. But until recently, the program relied on residents to request an alarm. After a fire in which five people—three children, their mother and grandmother—perished, the department started looking for a way to make sure that they were getting alarms into homes where they could make a difference.

FIRE RISK | With census and other data, New Orleans mapped the combined risk of missing smoke alarms and fire deaths, helping officials target distribution of smoke detectors.
FIRE RISK | With census and other data, New Orleans mapped the combined risk of missing smoke alarms and fire deaths, helping officials target distribution of smoke detectors. PHOTO: CITY OF NEW ORLEANS/OPA

Oliver Wise, director of the city’s Office of Performance and Accountability, had his data team tap two Census Bureau surveys to identify city blocks most likely to contain homes without smoke detectors and at the greatest risk for fire fatalities—those with young children or the elderly. They then used other data to zero in on neighborhoods with a history of house fires. Using advanced machine-learning techniques, Mr. Wise’s office produced a map that showed those blocks where fire deaths were most likely to occur and where the Fire Department could target its smoke-detector distribution.

Since the data program began in early 2015, the department has installed about 18,000 smoke detectors, says Tim McConnell, chief of the New Orleans Fire Department. That compares with no more than 800 detectors a year under the older program. It is too early to tell how effective it has been at preventing fire deaths, Chief McConnell says, since they are so rare. But the program did have an early, notable success.

A few months after the program began, firefighters responded to a call in Central New Orleans. Arriving, the fire crew found three families—11 people in all—huddled on the lawn. The residents had been alerted by smoke detectors recently installed under the outreach program.

“That was just one of those stories where you go, ‘This works,’ ” Chief McConnell says. “For us, it’s a game changer.”

Predictive analytics have also been used to improve restaurant health inspections in Chicago. The Department of Public Health relies on about three dozen inspectors to check for possible violations at more than 15,000 food establishments across the city. It needed a better way to prioritize inspections to make sure that places with potential critical violations—those that carry the greatest risk for the spread of food-borne illness—were examined before someone actually became sick.

The data team in the city’s Department of Innovation and Technology developed an algorithm that looked at 11 variables, including whether the restaurant had previous violations, how long it has been in business (the longer, the better), the weather (violations are more likely when it’s hot), even stats about nearby burglaries (which tells something about the neighborhood, though analysts aren’t sure what).

CHECK, PLEASE | To prioritize restaurant inspections, Chicago developed an algorithm to identify eateries most likely to have violations. The darker the pink, the higher the likelihood.
CHECK, PLEASE | To prioritize restaurant inspections, Chicago developed an algorithm to identify eateries most likely to have violations. The darker the pink, the higher the likelihood. PHOTO: CITY OF CHICAGO

With the tool, the health department could identify establishments that were most likely to have problems and move them up the list for inspection. After the algorithm went into use in 2015, a follow-up analysis found that inspectors were visiting restaurants with possible critical violations seven days sooner than before. Since then, its use has resulted in a 15% rise in the number of critical violations found, though the number of illness complaints—an imperfect measure of violations—has been flat.

Sensors on everything

Just as individuals are flocking to Fitbits and other wearables to monitor their health, cities, too, are turning to sensors to track their own vital signs. Through this Internet of Things, sensor-equipped water pipes can identify leaks, electric meters can track power use, and parking meters can automatically flag violations.

As part of a smart-city initiative, Kansas City, Mo., has installed computer-equipped sensors on streetlights along a 2.2-mile light-rail line that opened in March of last year. The city uses video from the sensors to gather information about traffic and available street parking along the corridor. The data is then made available on a public website that shows the location of streetcars, areas where traffic is moving slowly, and locations with open parking spots. It also provides an hourly traffic count in the corridor for the past day.

PARK HERE | In Kansas City, Mo., sensors on streetlights along a new light-rail line gather information about traffic and available parking that the public can view online.
PARK HERE | In Kansas City, Mo., sensors on streetlights along a new light-rail line gather information about traffic and available parking that the public can view online. PHOTO: XAQT

The sensors can even count foot traffic, which could assist entrepreneurs looking to open a new coffee shop or retail outlet, and help city officials estimate the size of crowds, which is useful in responding to public disturbances or in assigning cleanup crews after events like the city’s 2015 World Series parade. Their ability to detect motion also can be used to adjust the LED streetlights so that they dim if no one is around and automatically brighten if cars or pedestrians pass by. The goal is to use data to “improve our efficiency of service and ascertain what services we ought to be providing,” says Bob Bennett, Kansas City’s chief innovation officer.

Cities are also putting sensors in the hands of citizens. In Louisville, Ky., a coalition of public, private and philanthropic organizations has provided more than 1,000 sensor-equipped inhalers to asthma sufferers to map where in the city poor air quality is triggering breathing problems. The tiny sensors, from Propeller Health, a Madison, Wis., medical-device company, have built-in GPS that collects time and location data with each puff of the inhaler.

The city is still completing its analysis of the data, but early findings were impressive, says Grace Simrall, Louisville’s chief of civic innovation. For one thing, patients in the program saw measurable improvement, in part by giving them a better understanding of their disease, and their physicians more information to devise treatment plans. And as expected, the data made it possible to show clusters of inhaler use and link it with air pollution.

In one case, sensor data spotlighted a congested road on the east side of town where inhaler use was three times as high as in other parts of the city. In response, the city planted a belt of trees separating the road from a nearby residential neighborhood; the plantings have resulted in a 60% reduction in particulate matter (which can aggravate breathing problems) behind the green belt.

Citizens as data collectors

Using the public as data collectors isn’t new—it’s the idea behind 911 and 311 systems. But smartphone apps, in the hands of residents and city workers, give cities new and more powerful ways to expand their data-collection efforts.

In Mobile, Ala., building-code inspectors armed with smartphones and Facebook Inc.’sInstagram photo-sharing app were able to inventory the city’s 1,200 blighted properties in just eight days—a task that enforcement officers had previously considered impossible with the older paper-based systems of tracking blight. With Instagram, inspectors could snap a photo of a property and have it appear on a map, showing officials where dilapidated, abandoned or other problem properties are clustered.

AIR TRIGGER | Sensor-equipped asthma inhalers in Louisville that collect data on time and place of use have improved care for individuals and helped the city address problem areas.
AIR TRIGGER | Sensor-equipped asthma inhalers in Louisville that collect data on time and place of use have improved care for individuals and helped the city address problem areas. PHOTO: PROPELLER HEALTH

The inventory was just the first step. Mobile’s two-year-old Innovation Team, funded with a grant from Bloomberg Philanthropies, cross-referenced the data with other available property information—tax records, landmark status, out-of-state ownership—to compile a “blight index,” a master profile of every problem property in the city. This made it possible to identify which property owners might need assistance in rehabbing their properties and which ones to cite for code violations. The city is wrapping up a second survey of blighted properties to measure the net change over the past year, says Jeff Carter, Innovation Team’s executive director. “Instagram was phase one, and we would never have made it to phase two without it,” Mr. Carter says.

Mobile data collection is also helping Los Angeles to clean up city streets. Teams from the city sanitation department use video and smartphones to document illegal dumping, abandoned bulky items and other trash problems. The teams can use an app to report problems needing immediate attention, but what was really noteworthy—especially for a city the size of L.A.—was that they were able to view and grade all 22,000 miles of the city’s streets and alleyways.

The result has been to give officials and the public a better picture of garbage-plagued areas that can be targeted under Mayor Eric Garcetti’s Clean Streets program. Data collected by the mobile teams is compiled in a detailed map of the city, with each street segment rated as being clean, somewhat clean and not clean. The city publishes the map online so that anyone can get a color-coded view of how streets rank for cleanliness.

STATE OF THE STREETS | This online map tracks the progress of Los Angeles’s Clean Streets program. Green means ‘clean,’ yellow ‘somewhat clean,’ and red ‘not clean.’
STATE OF THE STREETS | This online map tracks the progress of Los Angeles’s Clean Streets program. Green means ‘clean,’ yellow ‘somewhat clean,’ and red ‘not clean.’ PHOTO: CLEAN STREETS LA

The program, which recently finished its first full year, has resulted in an 80% reduction in the number of areas scored “not clean,” says Lilian Coral, Los Angeles’s chief data officer. The new data-driven approach not only has made it possible to better identify problem areas, Ms. Coral says, but it also has helped to reduce disparities in the city’s cleanup efforts, which previously depended mainly on complaints to identify locations needing attention.

In Boston, meanwhile, the city has joined with Waze, a navigation app from Google that enables drivers to share traffic and road conditions in real time.

The Boston traffic-management center uses Waze data to supplement live feeds from its network of traffic cameras and sensors, getting a more detailed picture of what’s happening on city streets. Messages from Waze users can alert the center to traffic problems—a double-parked truck or a fender-bender—as soon as they develop, allowing officials to respond more quickly.

Waze data also has helped the city to run low-cost experiments on possible traffic changes. For instance, to test how to best enforce “don’t block the box” at congested intersections, the center took more than 20 problem intersections and assigned each one either a changing message sign, a police officer or no intervention at all. Using Waze data, analysts would then see which enforcement approach was most effective at reducing congestion. As it turns out, Waze’s traffic-jam data didn’t show that either approach made much difference in reducing congestion (which may reinforce the view of those who believe little can be done to eliminate traffic headaches).

The partnership, one of 250 that Waze has signed with cities around the world, also enables the city to feed street-closure and similar information into the Waze app, making it easier for drivers to reroute trips before they get stuck in traffic.

“When residents see a problem, sometimes their reaction is to call us, but more these days their instinct is to report it through an app like Waze or Yelp , ” says Andrew Therriault, Boston’s chief data officer. “To be as responsive as possible to the public’s needs, we need to listen to their input through whichever medium they choose to share it.”

Mr. Totty, a former news editor for The Journal Report in San Francisco, can be reached atreports@wsj.com.

Appeared in the Apr. 17, 2017, print edition.

The coming revolution in insurance

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Technological change and competition disrupt a complacent industry

IN THE stormy and ever-changing world of global finance, insurance has remained a relatively placid backwater. With the notable exception of AIG, an American insurer bailed out by the taxpayer in 2008, the industry rode out the financial crisis largely unscathed. Now, however, insurers face unprecedented competitive pressure owing to technological change. This pressure is demanding not just adaptation, but transformation.

The essential product of insurance—protection, usually in the form of money, when things go wrong—has few obvious substitutes. Insurers have built huge customer bases as a result. Investment revenue has provided a reliable boost to profits. This easy life led to a complacent refusal to modernise. The industry is still astonishingly reliant on human labour. Underwriters look at data but plenty still rely on human judgment to evaluate risks and set premiums. Claims are often reviewed manually.

The march of automation and technology is an opportunity for new entrants. Although starting a new soup-to-nuts insurer from scratch is rare (see article), many companies are taking aim at parts of the insurance process. Two Sigma, a large American “quant” hedge fund, for example, is betting its number-crunching algorithms can gauge risks and set prices for insurance better and faster than any human could. Other upstarts have developed alternative sales channels. Simplesurance, a German firm, for example, has integrated product-warranty insurance into e-commerce sites.

Insurers are responding to technological disruption in a variety of ways. Two Sigma contributes its analytical prowess to a joint venture with Hamilton, a Bermudian insurer, and AIG, which actually issues the policies (currently only for small-business insurance in America). Allianz, a German insurer, simply bought into Simplesurance; many insurers have internal venture-capital arms for this purpose. A third approach is to try to foster internal innovation, as Aviva, a British insurer, has done by building a “digital garage” in Hoxton, a trendy part of London.

The biggest threat that incumbents face is to their bottom line. Life insurers, reliant on investment returns to meet guaranteed payouts, have been stung by a prolonged period of low interest rates. The tough environment has accelerated a shift in life insurance towards products that pass more of the risk to investors. Standard Life, a British firm, made the transition earlier than most, for example, and has long been primarily an asset manager (see article).

Meanwhile, providers of property-and-casualty (P&C) insurance, such as policies to protect cars or homes, have seen their pricing power come under relentless pressure, notably from price-comparison websites. In combination with the stubbornly high costs of maintaining their old systems, this has meant that profitability has steadily deteriorated. The American P&C industry, for instance, has seen its “combined ratio”, which expresses claims and costs as a percentage of premium revenue, steadily creep up from 96.2% in 2013 to 97.8% in 2015, and to an estimated 100.3% for 2016 (ie, a net underwriting loss). Henrik Naujoks of Bain & Company, a consultancy, says this has left such insurers facing a stark choice: become low-cost providers, or differentiate themselves through the services they provide.

One fairly simple way to offer distinctive services is to use existing data in new ways. Insurers have long drawn up worst-case scenarios to estimate the losses they would incur from, say, a natural catastrophe. But some have started working with clients and local authorities on preparing for such events; they are becoming, in effect, risk-prevention consultants. AXA, a French insurer, has recently started using its models on the flooding of the Seine to prepare contingency plans. Gaëlle Olivier of AXA’s P&C unit says the plans proved helpful in responding to floods in June 2016, reducing the damage.

Damage control

Tech-savvy insurers are going one step further, exploiting entirely new sources of data. Some are using sensors to track everything from boiler temperatures to health data to driving styles, and then offering policies with pricing and coverage calibrated accordingly. Data from sensors also open the door to offering new kinds of risk-prevention services. As part of Aviva’s partnership with HomeServe, a British home-services company, the insurer pays to have a sensor (“LeakBot”) installed on its customers’ incoming water pipes that can detect even minuscule leaks. HomeServe can then repair these before a pipe floods a home, causing serious damage.

The shift towards providing more services fosters competition on factors beyond price. Porto Seguros, a Brazilian insurer, offers services ranging from roadside assistance to scheduling doctor’s appointments. In France AXA provides coverage for users of BlaBlaCar, a long-distance ride-sharing app. The main aim of the policy is to guarantee that customers can still reach their destination. If, say, the car breaks down, it offers services ranging from roadside car-repair to alternative transport (eg, calling a taxi).

Insurers face many hurdles, however, to becoming service providers and risk consultants. Maurice Tulloch, head of the general-insurance arm of Aviva, admits that such services are yet to catch on with most customers. So far, his firm, like its peers, has focused on enticing them to adopt the new offerings by cutting insurance premiums, rather than on making money directly from them. It reckons it can recoup the cost of, say, the HomeServe sensors and repairs from the reduction in claims.

One example of what the future may hold comes from the car industry. Carmakers have traditionally bought product-liability insurance to cover manufacturing defects. But Volvo and Mercedes are so confident of their self-driving cars that last year they said they will not buy insurance at all. They will “self-insure”—ie, directly bear any losses from crashes.

Some think that such trends threaten the very existence of insurance. Even if they do not, Bain’s Mr Naujoks is not alone in expecting the next five years to bring more change to the insurance industry than he has seen in the past 20.

This article appeared in the Finance and economics section of the print edition under the headline “Counsel of protection”

Did You Hear That? Robots Are Learning The Subtle Sounds Of Mechanical Breakdown

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Fast Company
STEVEN MELENDEZ 02.16.17

Expert mechanics can detect what’s wrong with a car without lifting the hood. So can deep learning robots, says startup 3DSignals.

Did You Hear That? Robots Are Learning The Subtle Sounds Of Mechanical Breakdown
[Photo: Flickr user David Hodgson]

Sometimes, machines just don’t sound right.

Brakes squeal, hard drives crunch, air conditioners rattle, and their owners know it’s time for a service call. But some of the most valuable machinery in the world often operates with nobody around to hear the mechanical breakdowns, from the chillers and pumps that drive big-building climate control systems to the massive turbines at hydroelectric power plants.

That’s why a number of startups are working to train computers to pick up on changes in the sounds, vibrations, heat emissions, and other signals that machines give off as they’re working or failing. The hope is that the computers can catch mechanical failures before they happen, saving on repair costs and reducing downtime.

“We’re developing an expert mechanic’s brain that identifies exactly what is happening to a machine by the way that it sounds,” says Amnon Shenfeld, founder and CEO of 3DSignals, a startup based in Kfar Saba, Israel, that is using machine learning to train computers to listen to machinery and diagnose problems at facilities like hydroelectric plants and steel mills

And while most current efforts are currently focused on large-scale machinery, Shenfeld says the same sort of technology might one day help detect failures in home appliances or in devices like self-driving cars or rental vehicles that don’t spend much time in the hands of an owner who’s used to their usual sounds.

“When you have car-as-a-service, the person in the car doesn’t know the car,” he says. “If it sounds strange, you’re losing this link with the human in the car deciding it’s time to take it to the mechanic.”

Initially, 3DSignals’ systems can detect anomalous sounds based on physical modeling of particular types of equipment, notifying an expert mechanic to diagnose the problem. And once the problem is fixed, the mechanic’s diagnosis is added to 3DSignals’ database, which it uses to train its algorithms to not only detect unusual sounds, but also interpret them to understand what kind of repair is needed.

“The next time we hit this signature on the same machine for the same customer or another customer using the same type of machine, it will not just be anomaly detection,” says Shenfeld.

And while 3DSignals focuses entirely on using its machine learning tools to process acoustic data—an area Shenfeld says is surprisingly neglected outside of speech recognition—other companies are using a variety of other types of data to detect and diagnose mechanical problems.

[Photo: Flickr user Sue Clark]

Systems from Augury, a startup with offices in New York and Haifa, Israel, monitor vibrations, temperature ultrasound, and electromagnetic emissions from machinery, typically large-scale heating and cooling systems. The company offers a portable tool a technician can use to capture a reading to an iPhone or Android device, where an app offers a real-time diagnosis as well as a continuous monitoring system, says cofounder and CEO Saar Yoskovitz.

“One of our customers, located in Ohio, had a thunderstorm at 2 a.m., and the whole building went dark,” he says. “The generator was supposed to pick up automatically but it didn’t, and the way that they learned about it was through an alert they got from Augury.”

In more complicated situations, the system uses machine learning-based algorithms and a growing library of signals of different types of errors to suggest what’s wrong and what technicians can do to repair the machine, he says.

“Over time, we’ve collected probably the largest malfunction dictionary in the world for our types of machines,” says Yoskovitz.

For another startup, called Presenso, also based in Haifa, the exact type of data being monitored is less important than how it changes over time and what that signals about the machine’s operation. The company’s systems record data from sensors already installed in industrial equipment as part of existing control processes, streaming readings to Presenso’s cloud servers.

“We don’t care, or we don’t need to know, if the sensor we’re analyzing now measures temperature or voltage or flow,” says CEO and cofounder Eitan Vesely.

Presenso’s software tools use a variety of machine learning techniques to effectively build a model of a machine’s operations based on the sensor data it receives. The tools provide visualizations of unusual readings, and how different they are from normal operations.

“They don’t need any human guidance or [to] know what the physical attributes are that are being measured,” Vesely says. “The goal is for them to learn by themselves how the machine operates.”

And while real-time breakdown detection is obviously useful for companies operating machines in their own facilities, experts say it could also be useful to equipment vendors or insurance companies providing financial coverage in the case of downtime.

“If a company has downtime or business interruption insurance, that’s something where it becomes incredibly relevant and also a money saver,” says Ryan Martin, a senior analyst at ABI Research.

Having more reliable predictions of when machines need maintenance could also spur equipment makers to effectively offer time as a service, charging industrial users either extended warranties or even charging by the hour for the guaranteed use of their equipment without incurring too much risk to themselves, says Augury’s Yoskovitz.

“One of the problems with this business model is they hold all the risk,” he says. “If anything goes wrong, they pay for it, and they’re looking for ways to lower this risk.”

The age of analytics: Competing in a data-driven world

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McKinsey Global Institute

By Nicolaus Henke, Jacques Bughin, Michael Chui, James Manyika, Tamim Saleh, Bill Wiseman, and Guru Sethupathy

Big data’s potential just keeps growing. Taking full advantage means companies must incorporate analytics into their strategic vision and use it to make better, faster decisions.

Is big data all hype? To the contrary: earlier research may have given only a partial view of the ultimate impact. A new report from the McKinsey Global Institute (MGI), The age of analytics: Competing in a data-driven world, suggests that the range of applications and opportunities has grown and will continue to expand. Given rapid technological advances, the question for companies now is how to integrate new capabilities into their operations and strategies—and position themselves in a world where analytics can upend entire industries.

The age of analytics
The age of analytics
Big data continues to grow; if anything, earlier estimates understated its potential.

A 2011 MGI report highlighted the transformational potential of big data. Five years later, we remain convinced that this potential has not been oversold. In fact, the convergence of several technology trends is accelerating progress. The volume of data continues to double every three years as information pours in from digital platforms, wireless sensors, virtual-reality applications, and billions of mobile phones. Data-storage capacity has increased, while its cost has plummeted. Data scientists now have unprecedented computing power at their disposal, and they are devising algorithms that are ever more sophisticated.

Earlier, we estimated the potential for big data and analytics to create value in five specific domains. Revisiting them today shows uneven progress and a great deal of that value still on the table (exhibit). The greatest advances have occurred in location-based services and in US retail, both areas with competitors that are digital natives. In contrast, manufacturing, the EU public sector, and healthcare have captured less than 30 percent of the potential value we highlighted five years ago. And new opportunities have arisen since 2011, further widening the gap between the leaders and laggards.

Progress in capturing value from data and analytics has been uneven.

Leading companies are using their capabilities not only to improve their core operations but also to launch entirely new business models. The network effects of digital platforms are creating a winner-take-most situation in some markets. The leading firms have remarkably deep analytical talent taking on various problems—and they are actively looking for ways to enter other industries. These companies can take advantage of their scale and data insights to add new business lines, and those expansions are increasingly blurring traditional sector boundaries.

Where digital natives were built for analytics, legacy companies have to do the hard work of overhauling or changing existing systems. Adapting to an era of data-driven decision making is not always a simple proposition. Some companies have invested heavily in technology but have not yet changed their organizations so they can make the most of these investments. Many are struggling to develop the talent, business processes, and organizational muscle to capture real value from analytics.

The first challenge is incorporating data and analytics into a core strategic vision. The next step is developing the right business processes and building capabilities, including both data infrastructure and talent. It is not enough simply to layer powerful technology systems on top of existing business operations. All these aspects of transformation need to come together to realize the full potential of data and analytics. The challenges incumbents face in pulling this off are precisely why much of the value we highlighted in 2011 is still unclaimed.

The urgency for incumbents is growing, since leaders are staking out large advantages, and hesitating increases the risk of being disrupted. Disruption is already happening, and it takes multiple forms. Introducing new types of data sets (“orthogonal data”) can confer a competitive advantage, for instance, while massive integration capabilities can break through organizational silos, enabling new insights and models. Hyperscale digital platforms can match buyers and sellers in real time, transforming inefficient markets. Granular data can be used to personalize products and services—including, most intriguingly, healthcare. New analytical techniques can fuel discovery and innovation. Above all, businesses no longer have to go on gut instinct; they can use data and analytics to make faster decisions and more accurate forecasts supported by a mountain of evidence.

The next generation of tools could unleash even bigger changes. New machine-learning and deep-learning capabilities have an enormous variety of applications that stretch into many sectors of the economy. Systems enabled by machine learning can provide customer service, manage logistics, analyze medical records, or even write news stories.

These technologies could generate productivity gains and an improved quality of life, but they carry the risk of causing job losses and dislocations. Previous MGI research found that 45 percent of work activities could be automated using current technologies; some 80 percent of that is attributable to existing machine-learning capabilities. Breakthroughs in natural-language processing could expand that impact.

Data and analytics are already shaking up multiple industries, and the effects will only become more pronounced as adoption reaches critical mass—and as machines gain unprecedented capabilities to solve problems and understand language. Organizations that can harness these capabilities effectively will be able to create significant value and differentiate themselves, while others will find themselves increasingly at a disadvantage.

Technology changes in food/beverage. HOW GATORADE PLANS TO REINVENT SPORTS DRINKS—AGAIN

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in Fast Company

January 11, 2016

AN EXCLUSIVE LOOK AT HOW GATORADE, THE ULTIMATE HANGOVER COMPANION, IS ATTEMPTING TO BECOME, ONCE AGAIN, THE FUTURE OF SPORTS FUEL.

On a hot, swampy November afternoon at IMG Academy in Bradenton, Florida, the private school’s boys’ lacrosse team is huddling around the bench draining water bottles after a round of drills. It’s a scene like any other on high school fields around the country . . . except here there’s a small crew of men sitting off to the side with laptops, running diagnostics on the team’s fluid intake, tracking each player individually through smart chip–enabled refillable water bottles.

Each “smart cap” bottle is digitally linked to a specific player. It works with an app to calculate how much he sweats in an average practice, how much sodium he loses, and how much he needs to drink to maintain optimal performance. Each bottle is filled with a drink formula that corresponds to an individual player’s sweat type. A microchip and a small turbine in the spout measure how much he takes with every sip. LED lights on the cap help him pace his drinking, showing whether he’s ahead of or behind his target. This is the future of athletic hydration. It’s also the future of Gatorade.

The brand’s new high-tech focus can be traced back to senior vice president and general manager Brett O’Brien’s decision in 2014 to build an internal innovation unit to look beyond bottle shapes and new flavors and toward a higher mission. After all, something had to be done. Gatorade sales in the first half of 2009 had fallen 18% year over year; new competitors such as VitaminWater, Red Bull, and Monster had gained influence and market share; and the product, born 50 years ago in a University of Florida lab as the original sports specialty drink, had become known more as a hangover helper than a high-performance elixir. O’Brien and the innovation group set about getting Gatorade back into shape, transforming it into an elite sports brand on par with Nike and Under Armour. “It’s not just about capturing a bigger part of a marketplace,” O’Brien says. “It’s about filling a void for your consumer, and ours are athletes.”

Gatorade started by looking at how athletes were already using its products. For instance, pro athletes had long been mixing sodium powder packs and other additives into their Gatorade (the brand even makes its own, called Gatorlytes). Now the company is looking to cut out the extra steps by creating 12 different formulas served in small egg-shaped pods that mix with water—to be used in new bottles featuring the smart-cap design. The formulas will range in carb, calorie, and electrolyte levels to optimize fluid recovery. To know which formula is right for which athlete, the brand has developed a suite of products and technologies that work together to measure and track individuals’ data. A smart scale linked to a tablet and software, for example, catalogs a player’s weight, along with training time and intensity, to make fluid and carb-intake recommendations. A patch, like a near-field communication chip-enabled Band-Aid, will analyze a player’s sweat and communicate with the digital platform to identify his sweat type—which will determine sodium, electrolyte, and additional fluid-intake needs.

All of this technology was developed in conjunction with the brand’s nutrition-minded Gatorade Sports Science Institute, fueled by PepsiCo’s 40% increase in R&D spending between 2011 and 2014. Now Gatorade is testing it on the field with top high school, college, and pro athletes, including the Brazilian national soccer team, the Kansas City Chiefs, the Boston Celtics, FC Barcelona, and the University of Florida. For Kansas City Chiefs wide receiver Jeremy Maclin, the idea of customized hydration is intriguing. “I don’t think there’s any athlete on this earth who wouldn’t take an advantage if proven to work,” he says.

Xavi Cortadellas, Gatorade’s global innovation and design senior director (who joined the brand in 2011 after 11 years at Nike), believes the move into customization and personalization was inevitable, given the rise of data-driven insight in sports in general. “It’s about whether you want to be a premium brand or not,” he says. “If you want to play in the premium space, then you have to be delivering personalization.” As part of Cortadellas’s plan to scale these new ideas, a simple version of the bottle will be available to the public by mid-2016—it can be customized with digitally printed cap graphics including team and player names, numbers, and logos. “Here at IMG, one of the things the kids were really excited about was having the ability to customize the bottle ‘just like NikeID personalized my shoes,’ ” says Cortadellas. “That’s what you want to hear.”

Ultimately, Gatorade wants to move beyond the field. The brand is developing and testing a new line of food products expected to hit shelves over the next several years—protein bars, vegetable-based nitrate boosts, protein-enriched yogurt—that will embody what nutritionists have long been preaching to athletes: that they are athletes all day, even at rest. “In all these spaces where we have no or minimal share, the potential for growth is gigantic,” Cortadellas says.

Not long ago, a Gatorade ad tagline asked, “Is it in you?” If Cortadellas and his colleagues are right, the question will soon become moot. They’ll already know.

Roll With It. “Hoverboards the new electric rides.

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What It’s Like to Have Wheels for Feet: Test Driving the Latest ‘Hoverboards’

With smarts to keep you upright, these electric rides are swiftly becoming a thrilling alternative to walking. We test ride the IO Hawk, OneWheel and RocketSkates

Using sensors and electric motors, the OneWheel, IO Hawk and RocketSkates let you zip around, steering with what feels like mind control.

WHY WALK WHEN you can glide? With the help of motion sensors, tiny computers and electric motors, a new breed of personal-transportation devices (sometimes misleadingly called hoverboards) is creating more efficient and thrilling ways to travel.

These electric-powered devices, which charge via a household outlet, have no clunky steering mechanisms or easy-to-lose remote controls. You pilot them by shifting your weight. Once you get the hang of them, it’s almost as if they’re reading your mind. Look toward your desired destination, lean in that direction and whoooosh.

The OneWheel in actionENLARGE
The OneWheel in action PHOTO: F. MARTIN RAMIN/THE WALL STREET JOURNAL

To help you stay upright, motion sensors feed data to a computer that figures out how to engage the motor. They can sense when a wheel needs to pivot just enough to keep you steady—and when to accelerate.

Learning to ride these is easier than mastering a bike, but good balance is required. Unless you’re a seasoned skateboarder or Rollerblader, plan on inching around your driveway like Bambi taking his first steps. A helmet, as well as elbow, knee and wrist pads, are recommended.

The legality of these devices, such as the three featured here, is murky. Although no law currently prohibits the use of the OneWheel in California, for example, the company lobbied to pass a law, going into effect next year, that explicitly allows it to be ridden wherever bicycles are permitted. The U.K. has banned the IO Hawk, but it’s legal in most of the U.S.

The only other caveat is that these devices are heavy. Lugging them through a train station or the lobby of an office building can be a drag. (The IO Hawk weighs 22 pounds, the OneWheel 3 pounds more; each RocketSkate weighs 7.5 pounds.)

But these gadgets are not meant to be carried. They’re designed to fly. Here are three especially smooth rides.

For Carving Turns | OneWheel

OneWheelENLARGE
OneWheel PHOTO: F. MARTIN RAMIN/THE WALL STREET JOURNAL, STYLING BY ANNE CARDENAS

Top Speed: 15 mph

Range: 7 miles

Charging Time: 20 minutes

This 30-inch-long board with a huge wheel suspended in the middle might seem like an accident waiting to happen. But cruising on the OneWheel is not as daunting as it might look, thanks to a gyroscope and accelerometer embedded in the platform. The system not only controls acceleration and braking based on how your weight is distributed—it also helps you stay upright. A smartphone app lets you dial back top speed and acceleration rate.

That said, the OneWheel is challenging to get the hang of. To engage the device, place your back foot on one side and set your dominant foot on a spot marked on the other platform. You’ll feel the system kick in. Then lean in either direction to roll forward or backward.

It took me about two very fraught minutes to get comfortable enough to inch forward on my own. Ten minutes later I was able to make tentative wide turns. Before long, though, I got it. The 11-inch air-filled tire, I discovered, flies over rough road and sand with barely a hiccup. $1,499, rideonewheel.com

For Ease of Use | IO Hawk

IO HawkENLARGE
IO Hawk PHOTO: IO HAWK

Top Speed: 6.2 mph

Range: 12 miles

Charging Time: 3 hours

The IO Hawk is as easy to master as a Segway—just stand and lean—but you don’t look as dorky on one. Unlike a Segway, the IO Hawk has no dignity-abusing handle poking up. It’s also a lot smaller. (It has celebrity cred, too, for what that’s worth: Justin Bieber and other boldfaced names have been spotted on it.)

A few seconds after hopping on, I was whizzing around with confidence as the electric motor whirred beneath me. Each wheel can be controlled separately (it’s like having two gas pedals), so I had no trouble making tight turns. And since the wheels can spin forward and backward, twirling in place is a cinch. This is what it would feel like to have wheels for feet.

The LED lights in front are bright enough to illuminate any divots in the road. They also draw attention to your futuristic ride. Before long, I was hooked. I’d even look for excuses to roam the office with it. It’s a great way to get to the water cooler and back. $1,800,iohawk.com

For Skating | RocketSkates R10

RocketSkates R10ENLARGE
RocketSkates R10 PHOTO: F. MARTIN RAMIN/THE WALL STREET JOURNAL, STYLING BY ANNE CARDENAS

Top Speed: 12 mph

Range: 10 miles

Charging Time: 2.5 hours

Yes, these self-propelled roller skates were inspired by Road Runner cartoons in which Wile E. Coyote supercharges his roller skates using dynamite. Thankfully, these use 55-watt motors.

After you step into the RocketSkates and buckle them over your shoes, you begin as you would with traditional skates: Push off on your dominant foot. Once both skates are rolling, you can activate their motors by tilting your foot forward. To brake, lean back on your heels.

Sounds easy enough, but it took me about an hour to feel steady on my motorized feet. Two motors is a lot to keep track of—which I realized when my feet would pull in different directions if I went duck-toed. You don’t need skating experience, but it’s definitely helpful to have clocked time at the roller rink.

Like the OneWheel, these have an app that lets you adjust the riding mode from beginner to expert. It’ll also let you tailor the skates’ performance by taking into account your weight and height. $699, actonglobal.com

Corrections & Amplifications

The OneWheel is legal to ride in California. An earlier version of this article incorrectly said its use is illegal in the state.

“Soft” Sensors Are Breaking Into Four Major Industries

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CRUNCH NETWORK

 

 

 

From something as simple as a door sensor at a store to the new age of “smart” sensors in a rapidly emerging wearables market, the application of sensors has already permeated many parts of our everyday lives.

But the future of dynamic sensor applications goes beyond just measuring your heart rate through the new Apple Watch; it is about how readily available sensor technology can be seamlessly intertwined with our daily activities to give us continuous insight into our own health and the way we interact with the world around us.

This is not just about wearables. Companies within the medicine, military and sport industries have all been increasing the connectivity of their respective products and workflows to the Internet of Things (IoT), and have used this connectivity and awareness to create powerful tools that enable better understanding, better analyses and better decisions.

Sensors fuel this process. But like all tools, it’s important to use the right one for the job. Not every type of sensor is fit to measure the range of lifestyles that we lead, or how our environment affects us. People are dynamic beings with soft bodies that react differently when we interact with the different situations and products around us.

A Step Up With Soft Sensors

Unlike conventional sensors that focus on the movement and characteristics of hard objects, soft sensors have been developed with the body and other “soft” structures in mind. Whether they are a few millimeters in diameter or the size of a sheet of paper, these sensors provide highly accurate and repeatable data about any change in the shape of these soft structures.

Technology should enhance our life, not distract us from it.

Soft and stretchy sensors can be used to measure human movement directly without interfering with that movement. They can be placed on the body, discreetly integrated into our clothes or otherwise glued, sewn or moulded into anything soft. This enables products to be designed to fit the way our bodies and other soft structures work, not the other way around.

The opportunities are limitless. Stretch sensors have massive potential to disrupt much more than just the realm of consumer wearables.

Sports

The most obvious application for soft sensors is in the sports sphere. The connected athlete already has a suite of wearable tech tools at their disposal, such as armbands and wristbands that measure distance, time and routes. However, many of these products are focused purely on monitoring biometric data.

By contrast, barely-there soft sensors add a level of bio-mechanical data that gives athletes and coaches a better understanding of body motion, muscle contraction, breathing rates, movement techniques, posture and risk of injury for each individual.

Companies such as Heddoko have already started integrating StretchSense’s fabric stretch sensor into compression clothing to continuously track body movement and guide athletes toward optimal performance and precision. The flexibility of the sensors means that they can be applied to any item of clothing or footwear without restricting any part of the athlete’s natural movement and performance.

Paired with wireless technology, athletes can break down and analyse every part of their performance without leaving the sporting venue.

Healthcare

Hospitals and specialist clinics have already benefited greatly from the use of sensors to measure a range of health metrics, like heart rate, blood pressure, glucose levels and much more. However, the healthcare industry still lacks a wide integration of available technologies that could produce better results.

Wireless and wearable soft sensors enable low-level care to be shifted out of the hospital and into the home, allowing accurate self-assessment and ongoing monitoring of patients during home recovery time periods.

For patients who require ongoing physiotherapy, soft sensors allow for the individual monitoring of exercise movements, improving the accuracy of technique and tracking of the recovery progress. Patients can share their data in real time with their specialist, from home or work, saving everyone the time and opportunity cost involved in making a special trip.

At MIT, researchers have created a “7 finger robot” that enhances the grasping mechanism of the human hand by adding two extra “fingers” adjacent to the thumb and pinky finger. The grasping assistance of the robot has potential to help elderly and disabled patients expand their independence capabilities over greater periods of time.

Cars

The automobile sector already uses more than 100 sensors (depending on the model) to measure brakes, tire pressure, temperature and if you’re too close to a car. The majority of these sensors focus on the condition and safety of the car. Soft sensors open new ways to monitor and enhance the safety and comfort of the people within the car.

Embedded within a car seat, soft sensors can be used to analyze how people are sitting, showing clearly the weight distribution and posture of the driver or passengers.

The seat can automatically adjust to the personal preference of the person sitting in it and ensure they stay comfortable throughout their journey. Safety features, such as an airbag, can be dynamically geared toward the individual sitting in the seat — whether it’s an adult or a child — enabling the car to deploy the airbag with appropriate pressure and height in the event of an accident.

Virtual, Augmented Reality

Although large companies like Google have sparked a resurgence in the interest on virtual reality, it is interesting to see the limiting factors that hold back virtual reality from being a truly immersive experience — namely, the lack of input methods for interacting with the digital universe.

Keyboards and touchscreens simply do not work. Unfortunately for the industry, these are still the critical elements that, apart from the visual aspect, largely connect the user to the experience.

Precisely tracking how a person moves in a simple, untethered way not only plugs a major gap in the VR/AR experience, it paves the way for the whole body to become an input device. Soft sensors can make games responsive through the natural movements of a player.

Motion and body language data can be combined with other biometric data to measure a person’s neurological reactions in nearly real-life situations. Now developers can create a truly immersive and truly interactive experience that responds to the people in it.

A Simple Solution

These examples are just the tip of the iceberg. For too long we have focused on  repurposing sensor technology created for rigid and precise machines and putting them on soft bodies. However, people are soft and precise — and hard sensors simply cannot tell the whole story.

With soft, precise sensing we now have a way of capturing so much more of the non-verbal communication we take for granted when we interact with each other. Mastering this new contextual awareness will take us one giant leap closer toward a world where technology is smarter, less intrusive and more seamlessly embedded in the fabric of our lives. Because, at the end of the day, technology should enhance our life, not distract us from it.

 

Hospital Looks to Virtual Reality in Emergency Situations

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LEO LUTERO in PSFK
11 MAY 2015
Hospital Looks to Virtual Reality in Emergency Situations

Patients and medical professionals will soon be setting aside diagrams and photos in exchange for VR goggles. Content developer Next Galaxy Corporation and the Miami Children’s Hospital has recently forged a multi-year deal for creating immersive virtual reality (VR) instructional content.

Virtual emergency situations will help train individuals in executing procedures such as cardiopulmonary resuscitation (CPR) that could potentially save lives. With the technology, learners will have a more realistic exposure to emergency situations.

Using eye-gaze control, gestures and voice commands, the system aims to provide real-time feedback that will give participants corrective pointers to help them carry out procedures more accurately. The system will even congratulate learners who do well during the lessons.

The training modules will be released as an application for smartphones and will be compatible with Current VR devices such as the Google Cardboard, Gear VR, VRONE and the Oculus Rift.

Next Galaxy‘s Founder and President Mary Spio shares:

In addition to being one of the nation’s most esteemed hospitals for its clinical outcomes, MCH is building a legacy as a pioneer in healthcare with its unabated efforts to connect, educate and reinvent the healthcare experience.

ceek next galaxy corp.jpg

Next Galaxy Corporation develops a wide assortment of VR content for the future. The company’s flagship product, CEEK, is a social VR hub that aims to become the epicenter of VR experience.

The Miami Children’s Hospital is a 289-bed nonprofit facility and is South Florida’s only licensed hospital specialized for children. Miami Children’s Hospital’s President and CEO Dr. Narendra Kini shares:

We are very excited about the new partnership with Next Galaxy to leverage the power of Virtual Reality to create innovative and impactful medical learning experiences. Through our MCH Virtual Reality education, we are breaking new ground with leading technologies and look forward to transitioning our extensive training library from two-dimensional to three-dimensional immersive content for the benefit of patients and the entire healthcare community.

VR Hospital image from Next Galaxy

The future is here today: How GE is using the Internet of Things, big data and robotics to power its business

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By Danny Pal in Computing
12 Mar 2015
bill-ruh-ge-vp-of-global-software-services

When your business supplies over 30 per cent of the planet’s power and produces engines for everything from cars to aircraft, it’s important to ensure that both the means of production and the products themselves operate as efficiently as possible.

That’s why General Electric (GE) – the fourth largest company in the world – has invested heavily in the Internet of Things and analytics technologies. As Bill Ruh, GE VP of global software services, told Computing: “It’s about getting better outcomes out of the machines we produce … the most profitable thing we can get to is zero unscheduled downtime.

“If you can make sure your power generation doesn’t go down, you don’t have brownouts, you can change the world and substantially improve industry.”

GE Aviation, the world’s second largest engine manufacturer, is using Internet of Things (IoT) technology to manage and repair jet engines pre-emptively, detecting tiny faults before they have a chance to grow into big ones.

“We’re finding that we can drive huge productivity increases in our teams because we can look at historical data across the fleet and begin to identify problems before they really happen,” Ruh explained

“We’ve had huge productivity increases because we’re automating how we think about maintaining an aircraft engine,” he continued. “We’re using big data analytics to help drive the maintenance schedule.”

By using sensors to collect engine data, GE is able to perform short bursts of maintenance much earlier on, meaning that over an entire lifecycle the engine spends less time in repairs.

Ruh likened it to getting a car repaired, but then discovering something hadn’t been spotted and having to return it to the garage shortly afterwards.

“The thing you hate when taking your car in is when in two months you have to take it back in. If they’d fixed it the first time, then they’d save you money and time,” he said.

“We can do that now. This is going to drive satisfaction rates and time on wing.”

But jet engine maintenance isn’t the only area where GE has harnessed the power of the IoT and big data analytics. Another is what the company calls its “Brilliant Factories Initiative”, which, according to Ruh, is “rethinking what a factory is”.

“Analytics in a factory has probably been underutilised, the data is mostly thrown away,” he explained.

“But we’re not doing that. We’re keeping every piece of data about how the machines operate and we’re using that to continue to identify types of analytics that could drive efficiency in our factory.”

Ruh added that GE is aiming for a “huge” 40 per cent improvement in factory efficiency.

‘If I could do analytics without IoT, I would’

But while connected devices and the Internet of Things are helping to drive improvements, for Ruh, they’re not the most interesting part of factory set-up; that would be the data and what can be mined from it.

“If I could do the analytics without IoT, I would, but I can’t because I need the machine data and machines are chatty. So for us, the IoT is necessary but it’s not the most interesting part. The analytics, the insight you gain: that’s where the value is. It’s just that you need the data in order to gain the insight,” he said.

For a company the size of GE, there’s a lot of data to gain insight from.

“Our current jet aircraft engines produce one terabyte of data per flight,” Ruh said, to illustrate the scale of GE’s data trove. “On average an airline is doing anywhere from five to 10 flights a day, so that’s five to 10 terabytes per plane, so when you’re talking about 20,000 planes in the air you’re talking about an enormous amount of data per day.”

Apart from the sheer volume of data, Ruh estimated that the firm analyses 50 million variables from 10 million sensors. These are the sorts of numbers that most industries could not conceive of managing. So when is IoT going to become useful to the mainstream?

Ruh believes that IoT going mainstream may be three to five years away. However, he warned that “if you’re not starting today you won’t be mainstream”. It is especially challenging, he argued, because operations teams rather than IT teams are the ones leading the change.

“The people who run power plants? They’re working with IT, don’t get me wrong, but they’re putting their own operations structure in place that is parallel to the IT structure,” he said.

“They’re already putting sensors in power plants, airlines and oil rigs. The number of sensors, the amount of data and the collection of that is already there,” Ruh continued. The trouble is, he added, the operations teams tend not to link this to analytics, which is where IT needs to get involved.

“The magic has to occur when the IT and the operations teams come together and that’s really where in five years the mainstream will be driven, when these guys are working in tandem,” he said. “GE does that today, but it took us four years to get there and it’s going to take other organisations that long.”

Despite being relatively advanced in its use of IoT and big data processing, GE isn’t resting on its laurels. Rather, it is exploring new areas to deploy the technology, including power generation.

“We’re changing the way we do remote monitoring and diagnostics. GE generates over 30 per cent of electricity in the world on our machines. So we monitor those machines remotely, then we try to proactively understand their behaviour and how to fix them,” Ruh said.

Ultimately, as with the jet engines, use of this technology will allow predictive maintenance, “telling our customers what they should be doing as opposed to what has happened”. This approach represents “the cornerstone of modernisation”, for GE.

‘An R2-D2 for every field worker’

But sensors are just the start. Ruh described how GE is looking to exploit the power of internet-connected robots to carry out “dirty, dull and dangerous tasks”. The firm has already experimented with this in the railway industry.

“We’re testing robotic rail inspectors that will go along and look for problems in rail yards, looking to see if there’s anything broken,” said Ruh. “The nice thing about that is they work 24 hours a day and they can work in the dark as well.”

GE called its first robotic inspector “The Guardian”, because as Ruh pointed out, it’s there to help people, not replace them.

“It’s something which actually works with a human,” he said, adding that GE got inspiration for this model from the film Star Wars.

“Most people think robotics is separate from humans but I look at something like Star Wars, where the robots weren’t there to replace humans, but to help them. So the question is: how do you create an R2-D2 for every field worker?”

Ruh went on to describe how this could raise some interesting questions in the future: as robots get more intelligent people could potentially start treating them on a more equal level.

“People are treating their robots like pets or members of the family. People are giving robot vacuum cleaners names, but not only that – and I think this is strange – but people take them on vacation,” he said.

“The fact is that we’re now seeing the Turing Test being passed every day, with people having no idea that they’re talking to a computer,” Ruh said. By extension, if the trend continues, robots will become widely accepted in homes and workplaces.

“Once robots take on human qualities – and I think that’s what’s going to happen -we’re going to find these things are playing a role in our lives as part of the family,” he concluded.