On February 9, 2017, a catastrophic unplanned outage occurred at the 32-acre West Point Treatment Plant in Seattle, Washington. The plant was built in 1965, and is located next to Seattle’s largest public park, and as well as on the second biggest marine estuary in the United States.

An electrical outage caused two sets of discharge pumps to go offline. The float switches that detect high water levels in the tanks failed, causing massive and rapid flooding at the plant. It was sheer luck that the flooding occurred outside of business hours when workers were not in the tunnels, or lives would have been lost.

The incident took the plant’s secondary treatment capacity offline for more than two months, leading to $25 million in infrastructure damage. All but $5 million of the damage was uninsured. Ultimately, the plant was forced to replace or repair a mile of tunnel, 151 electrical motors, 125 electrical panels, and more than 1,000 outlets and switches. It was also fined $361,000 for violating clean water regulations.

While repairs were underway, 235 million tons of wastewater entered the nearby estuary. Beaches were closed temporarily, and the incident made local, national, and even international news headlines.

Aging Infrastructure

The West Point incident is dramatic — close to a worst-case scenario, yet it highlights the growing risk exposure that all wastewater treatment plants face as infrastructure ages, and capital to finance upgrade projects remains scarce.

Roughly 240 million Americans rely on the nation’s 14,748 wastewater treatment plants for wastewater sanitation. By 2032, 56 million more will migrate from private septic systems to centrally managed wastewater treatment plants. At the same time, operating costs are rising as regulations become stricter, and treatment plants become older, and therefore costlier to maintain.

The Environmental Protection Agency (EPA) estimates that roughly $271 billion in wastewater infrastructure is needed in the next 25 years to maintain and improve our country’s ailing water facilities. Yet it’s estimated that the federal government will provide only 5% of total infrastructure funds, leaving the financial burden for wastewater facility upgrades up to local taxpayers.

Meanwhile, as many as 75,000 sanitary sewer overflow events occur each year in the United States. That number, and the financial risk exposure it represents for treatment plants, is increasing due to aging infrastructure.

Cutting Costs While Facing Greater Demand

So how can wastewater utilities reduce their operating costs and downtime risks, while freeing up capital for infrastructure upgrades?

As wastewater treatment utilities grapple with rising demand and cost, as well as limited capital for upgrades, new technologies from the Industrial Internet of Things (IIoT) are helping to relieve some of the pressure.

IIoT solutions are sold as a service and therefore do not require up-front capital investment. Long term, the system pays for itself in operating cost savings, and a good IIoT solution will not only reduce downtime, it will also free up cash for future infrastructure upgrades.

Augury, for example, provides a predictive maintenance solution called Halo for wastewater treatment plants. Wireless sensors are installed on critical equipment, where they “listen” to vibration, temperature, and other data to continuously monitor the equipment for failure indications.

A common use case for such types of technology is to monitor dry pit pumps in Lift Stations. These pumps often rely on manual inspection using human labor, which is costly in both time and money, and can be error prone. This also presents a risk for accidental discharge during peak hours if pumps fail to come online.

When problems with a pump are detected by an automated diagnostics system in real-time, alerts are sent to plant operators immediately — as soon as the system “hears” something abnormal. This enables efficient equipment maintenance as well as timely emergency response in the event of sudden failures like the one at West Point.

Collective Intelligence

IIoT solutions like this also benefit from collective intelligence. Platforms like Augury’s have an extensive “malfunction dictionary” of data points that help to digitally identify and predict equipment-specific failures in dry pit pumps and other critical equipment in wastewater treatment plants.

This collective intelligence is what makes affordable preventive maintenance possible for wastewater utilities. The malfunction dictionary is based on algorithms that are continuously being updated with new, real-time data from the field, and big data gathered in IIoT implementations across multiple wastewater plants. In many cases, predictive maintenance can help cut equipment costs by 25-30%, and downtime by 75%.

Experts agree that the incident at West Point was more than just equipment failure: there was a human component as well. With an IIoT-based predictive maintenance strategy, wastewater plant operators can reduce or eliminate the chance of human diagnostic errors, and control for faulty equipment with much greater precision and certainty.

To learn more about how you can reduce downtime, get in touch.

The post Reduce Downtime with IIoT at Wastewater Facilities appeared first on Augury.

Just about every day I read a report or projection about the breakneck growth of connected hardware or, as it is more commonly called, the Internet of Things.

Just about every day I read a report or projection about the breakneck growth of connected hardware or, as it is more commonly called, the Internet of Things.

Cisco, Gartner and Forbes all project that the IoT market will be worth trillions of dollars within the next decade as consumers and businesses recognize the enormous value in products and services linked by information. Given the resources being devoted to IoT by Fortune 500 companies such as GE, Amazon and Microsoft, its future indeed seems rosy.

But all the optimism and hopes for growth rest on the assumption that the information generated by IoT is accurate, credible and transparent. Perhaps we should question that assumption, or at least recognize that we will need stronger standards and a mechanism to enforce those safeguards as IoT develops.

I raise the issue because recent events cast doubts on how much we can trust corporations or governmental bodies or almost any organization, large or small, to provide unbiased, accurate and transparent data via supposedly neutral technology.

Take Volkswagen. To say the company misled regulators and the car-buying public is an understatement. VW engineers programmatically designed their hardware to understate nitrogen oxide emissions and deceive California Air Resources Board (CARB) officials during air quality testing. More than 11 million VW cars are estimated to suffer from this “cheatware” and the episode illustrates that corporate groupthink and the pressure to produce consistent earnings growth can trump the truth.

Government is no better. Officials in Flint, Michigan, wanted to save money by pumping water from the polluted Flint River rather than buying water from Detroit. They ignored warnings and then residents’ complaints about the water’s quality, jeopardizing the health of their city’s residents. They had the data to make the right decision, but instead chose to allow children to drink water tainted with toxic lead so as to preserve their political careers.

Whether it was for money or power or both, these episodes illustrate that people in positions of power can easily put their own interests ahead of the interests of customers and fellow citizens, even when that self-interest threatens others’ lives. This is not exactly an earth-shattering revelation, as evidenced by the fact that humans have been grappling with the issue of conflicts of interest for millennia. As times change, the mechanisms we have put in place to rein in undesirable human behavior in this sphere have changed too. And while not perfect, and in many ways either too onerous or even counterproductive, our modern regulatory and consumer protection efforts are attempts to make sure that people play by the rules even when the rewards for self-dealing can be great.

For the Internet of Things to truly reach its potential, some kind of rigorous standards-setting and monitoring function must be developed in order to ensure that any information collected, analyzed and provided is indeed as accurate, credible and transparent as it purports to be. As manufacturing IoT tools become more ubiquitous and more central to the way we interact with our environment, and as these devices and their software not only record data but transform it, more and more users will be prompted to take actions that could have dire consequences if the data-integrity issue is not addressed.

Integrity, standardization and transparency are already so vital to our national economic interests that the Department of Commerce has a special division dedicated to regulating and maintaining the accuracy of data and measurements. The mission of that division — the National institute of Standards and Technology (NIST) — is “to promote U.S. innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve our quality of life.” Said differently, NIST ensures that consumers – whether individuals or businesses – don’t get stiffed and get what they pay for. For example, when you fill your car’s tank with gasoline, NIST is behind state regulators to make sure the station gives you a gallon of gas, not 0.98 gallons.

NIST’s accreditation regime provides calibration and standardization services for everything from Geiger counters to peanut butter. It is as good a foundation for IoT standard-setting as we can hope for at this stage. The problem with NIST, however, is that it doesn’t communicate standards in a way that would allow users of technology to know categorically and in real-time whether their devices actually are performing correctly.

Since software and firmware updates can change the performance of IoT devices in a moment, standard-setting and measurement for IoT devices is a major challenge, not to mention overcoming the inherent reluctance of manufacturers to be completely transparent about the products they make. But challenges notwithstanding, standards are needed for the industry to grow.

Customers will complain, but they understand that mistakes, bugs and accidents are almost inevitable in any software and manufacturing process. On the other hand, most customers become downright hostile (and litigious) if they feel they’ve been deceived. By being able to present in real time metrics that conform to transparent standards, producers of IoT will be able to lay their cards on the table. Users can then decide if they want to proceed with the hand they’re dealt.

The post Setting a Standard for the Internet of Things appeared first on Augury.

Since I started using an Apple Watch, I find myself taking conference calls on the go, roving around the office and generally moving as much as I can in order to meet the daily activity and exercise goals I programmed into my new watch.

Time To Switch From ‘Should’ To ‘Must’

Thanks to the sensors and other sophisticated electronics built into my new Internet of Things (IoT) device, I now have a high-tech nag / mentor / monitor / coach and accountant keeping track of everything I do to keep fit.

Of course, I could ignore everything my watch tells me and sit behind my desk for most of the day like I did pre-Apple Watch. But now I feel more engaged. Before I knew I should be moving around more. Now I feel I must.

The difference between “should” and “must” is often more a matter of psychology and motivation than it is about reason. We know we “should” select a salad over a cheeseburger, but it’s easy to give into temptation.

In the consumer world, therefore, I believe that much of the economic payback from the IoT will hinge on its ability to get humans to switch from the “should” mode to the “must” mode.

Here’s Why.

The most compelling IoT applications arise when user behaviors are altered in such a way as to fundamentally alter the economics of the activity in question. Said differently, the marginal cost (whether in money or psychological discomfort) of obtaining the additional information required to produce behavioral change is outweighed by the returns that the “improved” behavior produces.

Meet Oscar’s Misfit

Consider Oscar, a health insurance company that uses Biometric sensors to improve the lives of its policyholders (customers). Oscar provides policyholders with Misfit, an IoT device that tracks their fitness levels. In exchange for meeting the minimum daily fitness requirements, Oscar customers are rewarded with Amazon gift cards – effectively a discount to their insurance premiums.

Oscar benefits by having a pool of healthier policyholders, which in turn, lowers its risk. The use of biometric sensors is a technologically inspired form of loss control, which are the risk-management practices insurance companies traditionally use to reduce claims.

But how do Oscar and Misfit get people to work out more than they would absent the Misfit device? In short, how do they convert health-supporting “should” behaviors into “must” behaviors?

The answer lies more in psychology than it does in technology. The device and platform incorporate characteristics that are inherently appealing:

• Simplicity – The device is as easy to put on as a watch.
• Personalization – Since Misfit comes in different colors, sizes and decorative features, you can make it your own. There is even a Swarovski line of bejeweled Misfits.
• Status – It’s inherently cool.

In addition, Misfit capitalizes on another aspect of human nature that drives behavior: the enjoyment of games and competition. At Oscar, Misfit users who are inspired by personal well-being alone can track their progress against prior achievements. But Misfit also allows the six-packed sadist who can’t tolerate being out-burpeed to compare his athletic performance against other Misfits to see who is the most fit. As evidenced by our national love affair with professional sports, competition is a huge driver of activity.

The IoT Game

At Augury, we apply similar gamification mechanisms through our IoT device, the Auguscope, so that potential users are able to compete with one another. But the fact is they already compete with each other — their game is real business and their game is getting more competitive and more filled with “musts.”

The users of our Auguscope are HVAC Mechanical Service Technicians and Reliability Engineers, most of whom have a MacGyver-like instinct for understanding how machines work. On top of their fundamental curiosity usually lies years of experience, which is why so many of the best Mechanical Techs often have lots of salt and pepper in their hair — like the best surgeons.

Like operating room wizards, the experienced Mechanical Tech has honed his or her craft by examining a wide variety and quantity of pumps, fans and chillers over the years and developing a deep understanding of how each of those machines reacts differently to its environment. The more applied knowledge and experience a Mechanical Tech has, the more able they are to solve the widest range of problems. Perhaps most important, they are able to identify smaller problems before the problems become larger ones and more costly to repair.

Hybrid Intelligence: Humans and Machines Together

But HVAC is becoming more complex and there aren’t enough top Mechanical Techs to go around. To go back to the surgeon analogy for a minute, you would never expect a surgeon to tell a patient, “Boy, that aneurysm’s a doozy; I’ve never seen that before.” Similarly, if the HVAC unit in that surgeon’s hospital blew out, you wouldn’t expect the Tech to tell the surgeon, “Let me come back in a few days; I don’t know what’s wrong and I need to find someone who does.”

At Augury, we’ve figured out how to deliver a lifetime’s worth of experiential technical knowledge through the Auguscope, which is connected to the world’s largest dictionary of machine malfunctions. Whatever the range of his or her own experience, a Mechanical Tech armed with an Auguscope will know what’s wrong or what will go wrong before it happens.

Today, having that kind of knowledge truly is more of a “must” than a “should.”

The post What The IoT Should Do appeared first on Augury.