Testing The IoT Waters: How GE Partner GrayMatter Created A Smart Drinking Fountain

Originally published in CRN

Solution provider GrayMatter is navigating the turbulent IoT waters, using its technical expertise and operational technology background to successfully deploy connected drinking fountains in public places like schools.

“We did a connected smart water fountain [with DC Water] – people think of that as a [classic] IoT application,” GrayMatter CEO James Gillespie told CRN. “That’s a good example because it combines a whole bunch of innovation.”

The Pittsburgh-based GE partner worked with the District of Columbia Water and Sewer Authority to create drinking fountains that monitor water quality and flow in real-time, which gives users more confidence in the water they are drinking while saving money spent on maintenance and testing.

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The smart drinking fountains, which will initially be installed in hospitals, daycare centers and schools, are equipped with sensors that use real-time data and analytics to monitor water quality and flow levels. The sensors then send that data to the cloud and back with alerts if water quality measurements begin to deteriorate.

The smart sensor drinking fountain, a co-innovation product by GrayMatter and DC Water.

Gillespie said the flow and water quality sensors give an accurate indicator of when the lead filter should be changed compared to traditional filters — like refrigerator filters — that measure flow only.

If water quality begins to deteriorate, alerts are sent by text or email to water managers, while a “change filter” message alerts maintenance so they don’t have to estimate when lead filters should be changed.

“It’s IoT and the value of the network, so when you have multiple drops on the network you can now get like a Google map picture of the water quality instead of the traffic with blue, yellow and red signifying how the water quality is in different points of consumption,” said Gillespie. “At the same time we’ve made the devices intelligent so they check their own quality, and they try to clean themselves and let someone know if they need help being cleaned. It’s kind of a confluence of all these things that weren’t possible coming together.”

The connected drinking fountains are also programmed to shut off at a set water quality level until maintenance staff make the necessary corrections.

Gillespie said in many IoT projects, the solution provider is beginning to look at its customers as not just an end-user, but co-innovators: “When we work with someone like Washington DC Water, we’re really a co-innovation partner with them. So if you asked them, they’d say they come to us when they’re looking to solve a problem they couldn’t solve before, and they come to us to find out the art of the possible,” he said.

An essential part of the solution GrayMatter brought to the table was not only its knowledge of sensors, data analytics and cloud-based solutions – but its market expertise around digital utilities.

The knowledge of water and wastewater issues – like collection systems, regulations, water quality and utility management – helped the company better understand the outcomes that DC Water wanted and needed.

Interested in learning more?

Check out our white paper on water innovations and read more on IoT in water, game-changing technologies and more customer success stories:

Read More About Water

 

TechHub: GE CEO on Digital Partners, Using Data You’re Already Collecting & More

GE CEO John Flannery: ‘Partners Are The Key Pillar Of Our Digital Strategy’

Originally published in CRN

Minds + Machines 2017 took place this week in San Francisco, revealing a ton of new digital software solutions to the world.

GE CEO John Flannery, while speaking to a crowd of systems integrators, resellers and ISVs, said that the Boston-based company wants to help customers work through an IT skills gap as they connect their machines, said CRN.

“Partners are the key pillar of our digital strategy going forward,” he said. “We’ll prioritize the market in two areas, with resources to focus heavily in verticals … like oil and gas, transportation, and mining … and we’ll continue to work to address adjacent markets as well, largely through our partners.”

According to a GE survey released on Tuesday, only 13 percent of executives have a mature digital industrial transformation plan in place. The rest of the industrial market customers are facing a critical skills shortage as they struggle to figure out how to tap into IT tools and drive value from their operations.

data

GrayMatter CEO Jim Gillespie giving a media interview during Minds + Machines.

That’s where partners come in, said Flannery: “Bridging this gap starts with small steps, that can help you move in the right direction,” he said. “We are ready and willing to be your partner.”

GE is helping its partners help their customers navigate real-time data, predictive analytics, and IoT through an array of resources, including blueprints, real use cases, and specific technologies.

These technologies include an array of new products and solutions the company has recently released, said Flannery – including Predix Studio, a solution that helps companies build and scale their industrial applications and simplify the development process.

James Gillespie, CEO of GrayMatter, a Pittsburgh-based solution provider and GE partner, said that he is seeing that “digital gap” in industrial companies who want a better digital strategy but don’t know where to start.

“That digital gap mirrors what we see when we’re talking to clients and prospects,” he said. “The challenge for customers is their level of knowledge, skills and culture … it’s sort of a perfect storm. More people are prioritizing it as a strategy now as they look ahead.”

Pulling Needles Out of Your Data Haystack

Steps to Use Data You’re Already Collecting

By Jim Gillespie, CEO of GrayMatter

The Impossible is Now Possible. Industry 4.0 is moving fast and I’d like to let you in on a few very valuable developments about the data you’ve been collecting. It can now help you make better decisions. You can talk to your industrial data and it’s talking back to you, letting you know what’s working inside your operation and what’s not.

It’s exciting for me to see GrayMatter and our partners innovating by taking the data you’ve been collecting through sensors on industrial equipment and applying artificial intelligence and machine learning in the cloud so you can find insights on performance. Then you know exactly where to make improvements.

You need a system to sort through the haystack of data and pull needles out to focus your subject matter experts. That’s what we can do now.

It all starts by framing up the action strategy in three parts.

Step One: Set Your Goals

Start at the end and work backwards.

What return on investment do you want to see? You don’t need all the data you think you need. What information will help you solve the problems you want to solve? What’s the path to getting there? Having this road map first is critical, because otherwise a lot of time and money can be wasted.

Step Two: Start Creating Digital Twins

You hear the term digital twin, but what does it really mean?

Simply put, creating a digital twin is the process of merging physical and digital worlds.

The process takes a physical machine and uses technology to get all the information about past states, present states and predictions. That information creates a digital model that’s alive – taking in a stream of data – using that to adjust so the model is personalized to be a precise representation of the asset.

The software version is used for what used to be a physical inspection – requiring people to be right next to the machine. The virtual version can be done from anywhere and at any time, expanding the value of those inspections and allowing them to have more of a real-time impact. It creates a constant inspection that allows the operators to predict failures sooner.

pulling needles out of data haystack

Digital Twin Value

The digital model of a machine, built and run in a virtual environment used to be available only to the biggest companies with the largest budgets. But the Industrial Internet and an explosion in sensor technology have lowered the cost and broadened the access beyond the elite.

People are not only connected to people, they’re connected to every kind of device at home and now work.

Manufacturers stand to win big from this. Factory floors are outfitted with tremendous amounts of sensors to collect data, but because that data has been locked up it hasn’t provided value.

The digital twin allows us to unlock that data and not just for one asset at a time. We can now model machines in groups – for example, a machine builder with thousands of machines installed across hundreds of customers – will now be able to operate best in class using digital twins.

There’s potential to unleash productivity and efficiencies like we’ve never seen before.

Step Three: Get Behavioral Information from Digital Twins

In order to move to more advanced use cases, such as adaptive diagnostics, condition-based maintenance or predictive failure, Industrial IoT systems need to know more than simply the current device state.

They need to know why. Knowing current device state only helps from a monitoring standpoint. While important, it’s really just the beginning of what we can expect out of IIoT systems. If we know why an asset exhibits a certain state, we can determine what conditions lead to that state and take proactive steps to prevent future occurrences. 

This new layer of getting insight through behavioral information allows you to ask for more. You can search your data and get answers back right away. It’s like an instant messenger for operational technology.

Step Four – Get Digital Twins to Interact

Achieving this may mean digital twins built using multiple discrete machine learning algorithms potentially spread across multiple IoT platforms, not simply relying on one. Eventually, we should expect that digital twins will interact with one another in virtual space.

data

Leap Ahead

If you’re short on time, staffing or budget – GrayMatter can get you up and running to achieve value quickly. You know you need an IoT strategy in the near future, but may not know how to go about it. Rather than trying to design, source and build it yourself we can put the strategy in place in days or weeks.

You also don’t have to do everything at once, you can start with a limited selection of assets and scale up or down as you learn performance and asset behaviors.

Our strategy is a Salesforce version of a remote monitoring and diagnostics center that you can buy and implement incrementally.

GrayMatter’s Digital Twin Strategy

We use data, predictive capabilities and machine learning to identify your best and worst performers in each asset group. Your operators are automatically alerted to the worst performers, then they use an intuitive web interface, to turn the worst into the best.

Continuous improvement becomes expected, simplified, and routine.

As your team builds new improvements or optimized settings, they can be scaled out, automatically, to every instance of a specific machine or piece of equipment.

You Don’t Need a Data Scientist

The complex algorithms that can leverage your data are pre-built so anyone can start creating the models and analytics to generate insights. One person no longer holds the keys to data, with this unique platform everyone gets a better understanding of your businesses processes, so you’re not focusing on the math to bring the insight, you’re focusing on creating better outcomes for your customers.

Think Big, Start Fast

You need to think big to truly transform your organization, but you also have to start acting on your data today.

We’re anxious to spread the word about how easy this is and to un-complicate it for you. Let me know if you’d like to discuss further. The case study is also available to read here:

Read the Case Study

New Ransomware Attack on Russia, Ukraine

A new strain of ransomware nicknamed “Bad Rabbit” has affected systems at three Russian websites, an airport in Ukraine and a subway system in Kiev, according to BBC.

However, despite bearing similarities to the WannaCry and Petya outbreaks earlier this year, it’s unknown how far this new malware will spread.

“In some of the companies, the work has been completely paralysed – servers and workstations are encrypted,” head of Russian cyber-security firm Group-IB, Ilya Sachkov, told the TASS news agency.

The Russian Central Bank said in a statement that it had recorded a BadRabbit attack on Russian financial institutions, but none were compromised. BadRabbit had targeted several of the top 20 Russian banks but failed.

A majority of the victims of the attack are located in Russia, with attacks also in Ukraine, Turkey and Germany.

TechHub: Google Pledges $1B for Tech Education, Additive Manufacturing News & More

Google Pledges $1 Billion for Tech Education, Training

Google’s CEO, Sundar Pichai unveiled an initiative for a $1 Billion program for tech education and training on Thursday at the company’s Pittsburgh office – noting the city’s transformation from an industrial manufacturing center for steel to a hub of robotics and artificial intelligence engineering.

Sundar Pichai, the chief executive of Google, announcing the Grow With Google program in Pittsburgh.

The new program, Grow With Google, will create an online destination for job seekers to get training and professional certificates and for businesses to improve their web services.

It will allow anyone with an Internet connection to become proficient with technology and prepare for a job in areas like IT support and app development, according to The New York Times.

“We understand there’s uncertainty and even concern about the pace of technological change, but we know that technology will be an engine of America’s growth for years to come,” Pichai said. “The nature of work is fundamentally changing, and that is shifting the link between education, training and opportunity.”

This announcement comes shortly after Apple announced in May that it was creating a $1 Billion fund to invest in advanced U.S. manufacturing, and Amazon in January announcing plans to hire 100,000 new employees over the next 18 months.

Additive Manufacturing: Possibility Meets Reality Through Generative Design

What we know of products and their manufacturing, distribution, assembly and maintenance processes may be obsolete in the not too distant future, according to Forbes.

Massive disruption, thanks to new technologies such as additive manufacturing and generative design, are already having a profound impact on the industrial space.

An example of a 3D printed gear. The gears inside the part can rotate. It would be virtually impossible without a 3D printer. Image credit: GE Reports/Chris New

GE recently shared how additive manufacturing, also known as 3-D printing, has changed turbine frame assembly from a process requiring 300 parts and 60 engineers to one that requires one digital file and eight engineers, as well as an assembly of only 50 source parts down to one.

If this sounds dramatic, that’s because it is.

“There is a seismic shift occurring in manufacturing, fueled by the fourth industrial revolution and shaped by digital transformation.”

Traditional manufacturing processes are giving way to new technologies, with additive manufacturing and generative design transforming supply chains and facilitating the innovation and customization buyers seek.

The effects of these technologies will be felt from the factory floor to the boardroom as their role expands to end-use parts. Rethinking the supply chain as well as how to effectively leverage generative design and additive manufacturing is now imperative for companies seeking to build sustainable brands and products in this new manufacturing paradigm, according to Forbes.

CRN’s 2017 IoT Innovators Awards

The Internet of Things is beginning to truly take off as companies recognize the benefits of IoT solutions in terms of data insight, predictive maintenance and improved customer service.

But customers are still facing hurdles as they figure out how to integrate complex solutions while also taking security and return on investment into consideration.

smart sensor

Co-innovated smart drinking fountain by GrayMatter & DC Water.

From systems integration to managed services, solution providers are key to filling in the gaps when it comes to helping customers set up and implement IoT projects. Solution providers with the necessary vertical market expertise and critical relationships with multiple vendors and customers are expressing interest in IoT,  but some are taking it to the next level by successfully deploying solutions with their clients, according to CRN.

GrayMatter is proud to have made the list as an IoT Innovator for our work with DC Water on co-innovating a smart sensor drinking fountain.

The new tech fountains have sensors that use real-time data and analytics to monitor both water quality and flow levels, sending that information to the cloud and back, alerting when water quality measurements begin to deteriorate.

By measuring water quality and flow in real time, they give users more confidence in the water they are drinking while saving money spent on maintenance and testing.

“This project redefines public water consumption, putting people and clean water first,” said Jim Gillespie, GrayMatter CEO.

Learn more about GrayMatter water innovations by reading our white paper:

Get the White Paper

Pulling Needles out of Your Data Haystack

3 steps to act on data you’re already collecting. 

The Impossible is Now Possible

Industry 4.0 is moving fast and I’d like to let you in on a few very valuable developments about the data you’ve been collecting. It can now help you make better decisions. You can talk to your industrial data and it’s talking back to you, letting you know what’s working inside your operation and what’s not.

It’s exciting for me to see GrayMatter and our partners innovating by taking the data you’ve been collecting through sensors on industrial equipment and applying artificial intelligence and machine learning in the cloud so you can find insights on performance. Then you know exactly where to make improvements.

You need a system to sort through the haystack of data and pull needles out to focus your subject matter experts. That’s what we can do now.

It all starts by framing up the action strategy in three parts.

Step One: Set Your Goals

Start at the end and work backwards.

What return on investment do you want to see? You don’t need all the data you think you need. What information will help you solve the problems you want to solve? What’s the path to getting there? Having this roadmap first is critical, because otherwise a lot of time and money can be wasted.

Step Two: Start Creating Digital Twins

You hear the term digital twin, but what does it really mean?

Simply put, creating a digital twin is the process of merging physical and digital worlds.

The process takes a physical machine and uses technology to get all the information about past states, present states and predictions. That information creates a digital model that’s alive – taking in a stream of data – using that to adjust so the model is personalized to be a precise representation of the asset.

The software version is used for what used to be a physical inspection – requiring people to be right next to the machine. The virtual version can be done from anywhere and at any time, expanding the value of those inspections and allowing them to have more of a real-time impact. It creates a constant inspection that allows the operators to predict failures sooner.

Digital Twin Value

The digital model of a machine, built and run in a virtual environment used to be available only to the biggest companies with the largest budgets. But the Industrial Internet and an explosion in sensor technology have lowered the cost and broadened the access beyond the elite.

pulling needles out of data haystack

People are not only connected to people, they’re connected to every kind of device at home and now work. Manufacturers stand to win big from this. Factory floors are outfitted with tremendous amounts of sensors to collect data, but because that data has been locked up it hasn’t provided value.

The digital twin allows us to unlock that data and not just for one asset at a time. We can now model machines in groups – for example, a machine builder with thousands of machines installed across hundreds of customers – will now be able to operate best in class using digital twins.

There’s potential to unleash productivity and efficiencies like we’ve never seen before.

Step Three: Get Behavioral Information from Digital Twins

In order to move to more advanced use cases, such as adaptive diagnostics, condition-based maintenance or predictive failure, Industrial IoT systems need to know more than simply the current device state.

They need to know why. Knowing current device state only helps from a monitoring standpoint.  While important, it’s really just the beginning of what we can expect out of IIoT systems. If we know why an asset exhibits a certain state, we can determine what conditions lead to that state and take proactive steps to prevent future occurrences. 

This new layer of getting insight through behavioral information allows you to ask for more. You can search your data and get answers back right away. It’s like an instant messenger for operational technology.

Step Four – Get Digital Twins to Interact

Achieving this may mean digital twins built using multiple discrete machine learning algorithms potentially spread across multiple IoT platforms, not simply relying on one. Eventually, we should expect that digital twins will interact with one another in virtual space.

Leap Ahead

If you’re short on time, staffing or budget – GrayMatter can get you up and running to achieve value quickly. You know you need an Iot strategy in the near future, but may not know how to go about it. Rather than trying to design, source and build it yourself we can put the strategy in place in days or weeks.

You also don’t have to do everything at once, you can start with a limited selection of assets and scale up or down as you learn performance and asset behaviors.

Our strategy is a Salesforce version of a remote monitoring and diagnostics center that you can buy and implement incrementally.

GrayMatter’s Digital Twin Strategy

We use data, predictive capabilities and machine learning to identify your best and worst performers in each asset group. Your operators are automatically alerted to the worst performers, then they use an intuitive web interface, to turn the worst into the best.

Continuous improvement becomes expected, simplified, and routine. As your team builds new improvements or optimized settings, they can be scaled out, automatically, to every instance of a specific machine or piece of equipment.

You Don’t Need a Data Scientist

The complex algorithms that can leverage your data are pre-built so anyone can start creating the models and analytics to generate insights. One person no longer holds the keys to data, with this unique platform everyone gets a better understanding of your businesses processes, so you’re not focusing on the math to bring the insight, you’re focusing on creating better outcomes for your customers.

Think Big, Start Fast

You need to think big to truly transform your organization, but you also have to start acting on your data today.

We’re anxious to spread the word about how easy this is and to un-complicate it for you. Let me know if you’d like to discuss further.

– Jim Gillespie, GrayMatter CEO.

Click to download the case study to start acting on your data:

Download Now

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