Deep Learning: Get Ready for Another Revolution

Deep learning—the use of multiple layers of wide neural networks to solve a learning problem—is hugely popular, but still a toddler. Almost everyone is familiar with the term deep learning, partly due to a string of remarkable and widely publicized successes in domains such as image processing and speech recognition. If you’ve conversed with Alexa, scanned a check for deposit or searched online for images, you’ve used deep learning. While most advances have occurred just since 2000, and large-scale impacts on the industry are only about 10 years old, age is not the only reason that deep learning qualifies as a toddler. The more remarkable reason is that even though the algorithms and mechanics of deep learning are well understood, the theory is not. Science is just beginning to understand how deep learning works, and why it works so well. And that means there is a lot of room to improve it.

Our ignorance is fading fast. The last several years have witnessed an intense cross-fertilization of ideas from numerous mathematical fields aimed not only at extending deep learning to new problems and new kinds of data, but also at advancing the basic science of what happens when a deep network learns, and more importantly, what could be done to make learning more efficient, faster and fool proof. Due to this cross-fertilization, the next generation of deep learning models promises to be even more remarkable. Hence, the subtitle, get ready for another revolution.

Many recent papers on deep learning use terms and concepts from optimal transport and dynamical systems, including control theory. I single out these two fields because of the short room available here for discussion. There are more influences. For example, ideas from information geometry are helping to improve deep learning on graphs. In the brief narrative that follows, I highlight a few ways in which dynamical systems and optimal transport are impacting the development of deep learning.

First, it might help to understand how deep learning is structured. Here we focus on the supervised learning setting, where the goal is to find a map that intakes inputs x and produces outputs y. If all goes well, outputs of the map closely match observed values, and if so, we say that the map has low error. Deep learning is a map that is, in essence, a composition of functions. If f1, f2, and f3 are functions, deep learning is structured as y = f3(f2(f1(x)))). It’s a nesting of functions, like a Matryoshka (Russian) doll. The result of f1(x) is used as input to f2, and that result is used as input to f3. Each of the functions is parameterized, and “learning” means to find those parameters that produce output y with the least error.

The whole thing is more complicated, of course, and there can be more than three composite functions. This is just a birds-eye view.

A deep neural network can be structured in many ways, one of which is called a residual network, or resnet for short. This is just like the composition of functions I mentioned above, only now each layer receives a duplicate input term. If h is the output from each function, then starting from the inside, h1 = x + f1(x); using this result, h2 = h1 + f2(h1); and using this result, h3 = h2 + f3(h2). Dropping the subscripts for clarity, the pattern at each layer is h + f(h).

In a milestone paper from 2018, Chen et al. recognized that this same pattern occurs for an ordinary differential equation (ODE): xt+1 = xt + f(xt), where t is time. They developed a method to conduct learning using solvers from the field of dynamical systems. Rearranging terms to be a bit more formal,  (xt+1 - xt ) = f(xt), where the term on the left-hand side is a derivative, like dx/dt for small time steps, and on the right-hand side f is a neural network. As such, the deep learning problem can be solved by passing the function f, and some initial conditions, into a standard ODE solver.

The upshot is that tools for dynamical systems can now be applied to deep learning. Not only does this suggest new possibilities for solving deep learning problems, but it also means that the mature field of dynamical systems analysis can be applied toward understanding how learning occurs in resnet, recurrent networks, and other similar deep neural network architectures. Liu and Theodorou and Li et al. provide reviews.

As an aside, an at first seemingly unrelated development over the last few years is called normalizing flows. The idea is to transform a simple distribution, such as a Gaussian, into one that is more complex and better matched to the data at hand. This is done by repeatedly applying a simple transform to a base input. But, as you might already suspect, this process is very similar to the recurrent pattern discussed above. It turns out that in many cases neural ODEs can be understood as continuous normalizing flows and resnets can be understood as discretized versions of normalizing flows. Again, a cross-fertilization of ideas is occurring.

Concepts from optimal transport appear in numerous deep learning papers. One interesting application has to do with how the weights of deep neural networks evolve during training. At the start of training they are randomly initialized, then in each round of training (or with each minibatch of training), they are adjusted slightly to improve model fit. If all goes well, errors fall during training rounds, and at some point, training can stop.

Optimal transport is a field focused on the problem of transforming one distribution into another at the least cost, via the shortest path, or while doing the least work. It turns out that deep learning networks tend to perform best if weights do not vary far from initial values. This prevents some weights from growing wildly large, for example, or following erratic paths. An ideal training path alters weights as little as possible to achieve desired model accuracy. Optimal transport to the rescue. Karkar et al. describe how ideas from optimal transport can be used to train neural networks. Similarly, Onken et al. describe how ideas from optimal transport can be used to improve the dynamics and training of neural ODEs.

This is just a quick foray into the cross-fertilization of fields that is not only driving the maturation of deep learning, but also expanding the domain of deep learning to new kinds of problems and new kinds of data (like graphs). As Itron Idea Labs explores opportunities in the world of machine learning and artificial intelligence, we welcome conversations with our utility customers and others regarding challenges that require advanced approaches. If you would like to schedule a conversation with the Idea Labs team on these topics, please feel free to contact us at

Increasing Citizen Engagement in Smart City Planning

Over the past six months, Itron Idea Labs has had discussions with cities to understand their biggest complications when it comes to creating a smart city. Many cities shared the following challenges:

                1. It is challenging to get continual input from citizens unless they are upset.

                2. The cross-section of individuals we hear from is narrow and very specific.

                3. It is difficult to communicate with and educate citizens.

Citizen engagement is obviously an important piece of smart cities. Being able to deeply communicate with a wide swath of citizens is important in good times and bad. Many cities lamented that only a limited set of people knew where their tax dollars were going or how to use existing city programs.

If engaging citizens is the first challenge, utilizing existing data is the second. A truly smart citizen will have access to the city’s data as well as the ability to share their own data with the city. Right now, we are at a unique time in history, where most citizens carry a smart phone (i.e., radio with multiple sensors attached to it). Imagine the power of this collaboration between city and citizens! When the city finds a new and pressing problem, the citizens can provide the data with a little guidance.

Our world is full of unplanned and unprecedented events that cause new and pressing problems. With a two-way communication structure between the city and citizen, there is a way to react actively to gather data and share data to collectively improve these challenging situations. Early on in our discussions, we found that in many cases cities solve a single problem with a single service. While each service was useful in its own right, different locations for each communication with the city was cumbersome. Citizens wanted to be able to do more than one thing with the city app or webapp. The platform needed to have the flexibility to solve many pain points, and not just a single issue.

We also heard from cities that a level of trust is needed between the cities and the citizens to enable any positive interaction. For all the complexity involved, trust seemed to really boil down to two things:

                1. Have frequent, open and clear communication.

                2. Follow-up so they know the city is listening.

But it is difficult to get people to interact consistently! The real-world is messy and things do not always get resolved as desired. We began to discuss how we could create a cycle of engagement that would keep the citizens interacting and helping improve the city. A few items we identified as possible catalysts in this area were gamifying the experience and giving the citizens daily and weekly goals, and then providing feedback based on completion of those goals. Cities with a focus on citizen engagement for more than 10 years noted that even when the feedback is not communicating success, the communication is still vital, and possibly even more so.

From the city perspective, how would a smart city look? This became more apparent as we worked through the citizen side of things. Cities traditionally take a very long time and spend a lot of money to implement a solution, sometimes discovering the solution did not solve the problem. This is where Ecclesia comes in. Ecclesia is a project that explores the challenges around citizen engagement using two-way communication to solve problems for both the city and the citizen. Ecclesia seeks to enable rapid iteration of solutions, adjusting on the fly and pivoting until a good solution is found. The structure Itron Idea Labs has identified for this concept is based around the idea of campaigns and opportunities. A campaign is started by the city to solve a problem. Within that campaign the city can set up different opportunities for the citizens to engage. Engagement examples might be taking a photo of a specific area at a specific time, completing a poll based on happenings in your area or viewing a video posted by the city – always short, easy to complete opportunities. As is continually shown, crowdsourcing is incredibly powerful and applying many minds to the same problem can lead to exciting results.

Imagine your city wants to renovate a rundown section of town. The city may have many theories of what can be done to bring back a buzzing economy and lots of foot traffic, but most of these solutions require months of planning with significant cost. Using Ecclesia, your city can create a campaign based on the desired improvement, starting with an opportunity of a basic poll for the citizens. Asking about the area’s biggest problems, the times you feel unsafe, etc. With that information, the city might choose to increase the smart lighting levels at certain times of day.

Next, the city can try an opportunity based on identifying the "fear hotspots," by having citizens use the Ecclesia application to identify places they feel safe and places they feel uneasy. Once the fear hotspots have been identified, the city can then look for simple changes to improve that area, such as a temporary light generator or scheduled police presence.

The city could continue the campaign by re-polling to see if public sentiment changes. This iterative approach can continue until a solution is found, at which point a permanent solution can be crafted with a far greater chance of success and public support since citizens were engaged in finding a solution from the start.

This scenario represents a typical use case for the solution being explored by Itron Idea Labs – a solution that expands citizen engagement and magnifies a city’s ability to access and use the data collected. 

To learn more about Itron Idea Labs, visit the Itron Idea Labs website.

Animal, Societal and Artificial Cognition

How does a society think? For that matter, how does cognition occur in any organism or superorganism? What is the purpose of cognition? What can we learn from biology to make progress in artificial intelligence and to make wiser decisions as a society? Questions like these are driving a convergence of ideas from fields as diverse as complex systems science, evolutionary biology, information theory, cognitive science and computer science. One result is active inference, a Bayesian explanation of cognition and biological self-organization that applies to cognition in cells and animals, as well as to societies of these.

Active inference plays a central role in work I have done at Oregon State University (OSU), Environmental Sciences Graduate Program, where I am courtesy faculty. Perhaps in the future it will also play a role at Itron, as it seeks to improve and expand its capacity to deliver machine learning and artificial intelligence solutions. For example, active inference could be a natural fit for problems where multiple intelligent agents, such as intelligent IoT devices, must coordinate behaviors to reach a common goal.

I’m pleased to announce that ScienceX just published a short article summarizing the work I have done at OSU. The topic is societal cognition as it relates to societal transformation in the face of climate change, biodiversity loss and other pressing social and environmental problems.

As Itron Idea Labs explores opportunities in the world of machine learning and artificial intelligence, we welcome conversations with our utility customers and others regarding challenges that require advanced approaches. If you would like to schedule a conversation with the Idea Labs team on these topics, please feel free to contact us at

Challenges in Removing Obstacles on the Path to IoT

Companies such as Cisco, Ericsson and other players have been projecting the exponential expansion of connected IoT devices for years. From the first connected device in 1990 (a toaster connected by TCP/IP) to 26 billion connected devices in 2019, technologies for communication and connectivity continue to evolve. However, with expansion comes the challenge of growth.

With standards-based code embedded on the modules and with the use of common data objects, Itron Idea Labs is working with IOTEROP, a company offering IoT device management solutions, to promote a common architecture from device to cloud so every device developer and every IoT solution designer can enjoy an accelerated path to deployment.

On Jan. 19, I was able to join a panel of IoT experts as part of the Cellular IoT for Smart Cities webinar to discuss how Itron Idea Labs is collaborating with IOTEROP and others to surgically remove obstacles and enable the IoT explosion.

During the panel, device management was the first obstacle to be addressed. Panelist Matt Hatton of Transforma pointed out the need for no touch provisioning in use cases where a city or service provider has millions of sensors spread out in a diverse geographic area. Imagine a router upgrade in your own home. Your televisions, both laptops, the tablets, gaming devices, everybody’s phone, the doorbell and who knows what else will need to be provisioned to reconnect with the IoT - and that’s just a single home. Hence the need for a truly scalable, truly no-touch process for device manufacturers, application developers, businesses and cities. Stephen Lurie, a panelist from IOTEROP, pointed out that Itron understands the need for device management that scales from “a business or human or processes standpoint.”

Another obstacle raised by the panel was data exchange. Envision a city with multiple departments all gathering data in their own way. Sharing that data among departments and with organizations outside the city can be crucial to enabling essential use cases. To address this challenge, the key is standards! And Itron is engaged with standards organizations who are making a difference. As an example, I described Itron’s work to define common functions and processes using a public repository of data objects with defined attributes (OMA ISPO objects). Using the LwM2M standard and the work done by the OMA Specworks organization, a public repository of data objects with their attributes is now available. IoT solution developers can align around open standards and standardized data models, working within this framework to ensure their data collection adheres to standards that will enable sharing.

A third obstacle to IoT explosion was the fact that security is an ever-moving target. Hatton mentioned the need for over-the-air firmware updates to ensure that IoT devices stay current. For this example, I described our work with module makers (Quectel, Ublox, Sequans, Sierra, Nordic, etc.) to ensure the ability to embed a full IP stack with keys, protocols and secure firmware extensions. This built-in stack on the module becomes a foundation for a device developer, reducing the expertise needed in underlying protocols and allowing developers to focus on building their solution. This architecture promotes a single SKU that works anywhere in world, delivering a global footprint with the added benefit of reducing the attack area on each device.

Itron’s decades-long experience deploying Industrial IoT devices in the field helps us bring standards, security and scalability together for our industry and the developer community, and the evolving landscape changes from an intimidating maze to a well-lit, clearly marked pathway for deployment and adoption of IoT solutions.

View a recording of the Cellular IoT for Smart City: An Evolving Landscape panel, with my presentation visible at minute 34.

Joining the Age of Automation with Consumer-Enabled Data Collection

Rapid technological advances are the norm in the 21st century. Entire industries have become obsolete in the wake of smart phones, digitization, online commerce and “remote everything.” We upgrade phones, cars, televisions and other household devices every few years, but in some parts of the world, the basic non-communicating meters at our homes have been there for decades.

Due to the COVID-19 pandemic, the Itron Idea Labs team learned – through a combination of interviews with utilities and consumers – that some utilities had begun to ask residents to help out by reading their own meters. In a small global survey conducted over the summer, we found that 76% of our respondents (130 of the 160 surveyed) had been asked to read their own meter — by mail, phone, text, email and a variety of other methods.

And as these consumers responded, some utility staff found themselves overwhelmed with a host of manual tasks required to make the submissions into a usable billing index. Emails had to be opened, images had to be viewed and stored. Reads and other identifying data had to be extracted from the image, verified, and entered into a spreadsheet for ingestion to billing. These manual tasks add labor and expense for utility customer service teams.

In the midst of this challenging time, the Itron Idea Labs team – in partnership with members of the Itron Bangalore team – developed a mobile app to automate read collection by consumers. The Consumer Collect app streamlines what could be a manual seven-step process into a single step by employing machine learning, optical character recognition, usage validation algorithms and accuracy verification at multiple levels. The consumer simply points their mobile device at the meter, and the Consumer Collect application captures the meter serial number and the read. The captured data is automatically transported to Itron’s system, where data management algorithms verify the accuracy and send the read on to the utility’s billing system. In essence, the Itron Idea Labs team has eliminated the costly and labor-intensive elements of the manual process where error and fraud can be introduced.

Early field trials with the Consumer Collect solution included experimentation with machine learning algorithms developed by our Itron team and a variety of third parties. Following the field trials where we evaluated multiple vendors, Itron Idea Labs decided to collaborate with Anyline for continued development activities. The beta solution is now available for utilities to pilot. With Consumer Collect, Itron Idea Labs makes it possible for utilities who still have a large install base of non-communicating meters to join the age of automation.

To Move or Not to Move: Insights from CES 2020

Humans are designed to walk 12 miles per day, according to anthropologists. This dates back to when we roamed the Serengeti desert. Modern humans today generally think we are supposed to walk 10,000 steps per day, because that’s what popular apps tell us.

The technology on display at this year’s Consumer Electronics Show (CES) seems to give competing messages: minimize motion on the one hand and maximize it on the other hand.

Segway showed the S-Pod, a self-balancing chair so you don't have to walk around anymore. Or you can drive around with a Smart Cycle.

If you don't want to make the effort of driving, just attach a self-driving box to the roof of your car and it will do it for you – this includes Lidar, radar and cameras.

The smart shower mat weighs you as you step on it, right out of the shower, so you don't have to walk all the way to the scale. No need to change trash bags with Townew, the self-sealing, self-changing trash can. Rock the baby automatically with the automatic bassinet. And no need to play with your dog with the self-moving dog toys.

But not so fast! Health was also big at CES 2020. Technology makes it so that you don’t have to move, but it also gives you the tools to move in style if you want to: treadmills with screens showing you classes, cameras checking your form while you run, shoes with all sorts of sensors and all types of wearable devices monitoring your biometric functions while you move.

This advanced level of automation was also reflected in Itron Idea Labs’ demonstrations during the show, where sustainability and carbon reduction were predominant topics. In one demonstration, sustainability managers at large hotel resorts can monitor real-time consumption of energy, water, gas and steam – including the facility’s total carbon emissions – to help meet sustainability targets. In another, cities can monitor traffic patterns, analyzing data from many different sources. Automation and data aggregation at the utility and municipality level are going to make new insights available at everyone's fingertips.

Overall, our motions are becoming more valuable: technology allows us to move throughout most of our day without actually moving. But when we do move – whether in our personal lives or at the business level – each single motion is measured and analyzed.

We are Living in the Future: A Week at the Consumer Electronics Show

I feel like the gap between what I would see in science fiction movies and what actually exists used to be much wider. Futuristic movies today show holograms coming out of your phone in broad daylight, sheets of glass that turn into TVs and robots that do literally everything for you.

Well guess what? I saw all of those things this week during the Consumer Electronics Show (CES) in Las Vegas, Nevada. They all exist. My colleague’s jaw literally dropped when he saw the ambient light hologram.

I saw biometrics that run your whole house: your door unlocks automatically when it sees you; the shower temperature is exactly set to your preference; and the sink faucet dispenses the exact quantity of water that you need for your brew. There were also robots that mow your lawn, robots that get a new roll of toilet paper for you if you run out at an inopportune moment and robots that play with your dog for you (so sad!). Everything is electrifying. Even the things that used to be totally manual – like a door mat, which now features a powerful vacuum so you don’t have to wipe your feet.

All of this got me thinking about the implications for energy management. We used to have around five major electric end uses in the home - HVAC, lighting, water heating, cooking and “miscellaneous plug loads.” We never had to consider toilet paper robots in our load profiles before. These smart devices can absolutely be a benefit to the grid. But if we are going to learn how to manage 50 loads in the home instead of five or 10, we are going to have to get much better at sending the right signals to these devices and to make sure they are all coordinated and optimized. This means sharing lots of data amongst a diverse set of actors, sophisticated artificial intelligence and robust identity management, access control and data privacy.

Fortunately, several of the projects the Itron Idea Labs team demoed during CES address exactly these problems. Our suite was packed all week, and we had lots of great meetings with our utility and city customers as well as our technology partners. Our future looks bright…and completely (sometimes excessively) automated!

Stay tuned for additional insights from this year’s CES event in Las Vegas. To learn more about the Itron Idea Labs team, click here.

Itron Idea Labs @ CES 2020: Innovating for a Sustainable Future

With 275 cities adopting energy and water mandates since 2017, utilities, cities and countries across the globe are being challenged to do better and be better at preserving and protecting our planet’s resources. The need for more sustainable solutions and better conservation efforts across the globe is more crucial than ever—and at Itron Idea Labs, we have our eyes on future technology to help us meet the challenge.

If you get the opportunity to visit the Itron Idea Labs team during the 2020 International Consumer Electronics Show (CES2020) in Las Vegas, Nevada, our theme will be clear – Innovating for a Sustainable Future. Itron Idea Labs is exploring technologies that will extend Itron’s commitment to the resourceful use of energy and water into homes, neighborhoods, businesses and global communities. With 10 projects underway, our CES2020 exhibits display a robust intersection of our work with narrow band IoT, private LTE, microgrids, artificial intelligence (AI) and machine learning (ML).

Imagine the cumulative impact if every smart home could make energy usage choices based on when clean energy is available on the grid. Our exhibit showcases ML and AI models that are quantifying the potential for emission savings by shifting load for home appliances based on grid emissions data. Consider the urgency felt by hotels and other large commercial or industrial building owners when local laws establish thresholds on greenhouse gas emissions – and set penalties. Stop by and see how Itron Idea Labs is piloting the delivery of data to hotel owners so they can determine their baseline of usage and plan the changes required to satisfy energy efficiency mandates.

In addition, one of the newest Itron Idea Labs projects will investigate the creation of a utility-focused Mobile Virtual Network Operator (MVNO) service to enable devices and applications in the narrowband space. Our team is exploring how narrow band IoT can deliver previously unavailable convenience and quality of life benefits to isolated homes or businesses in remote regions of the world.

Itron has decades of experience delivering innovative solutions for utilities, cities and businesses tasked with the resourceful use of energy and water. As Itron’s innovation incubator, our projects originate, evolve, pivot and take root through a combination of research, customer discovery, experimentation and prototyping.

We hope you’ll visit our suite at the Venetian Resort (Room 35-307) at CES2020 to learn more about our continued commitment to delivering innovative technology and services for a sustainable future. Email to schedule a meeting.

The Importance of Modern-Day Innovation

For those of us who grew up with the Space-time continuum as defined by Dr. Emmett Brown (Doc Brown) in the Back to the Future trilogy, we know that for real innovation to occur, there has to be plutonium, predictable weather and fourth dimensional thinking. But we’re not in 1955, or 1985 for that matter, and plutonium is not available in every corner drugstore as Doc Brown once predicted. So, what does a technology firm need in the 21st century to infuse innovation into everything we do? Opinions of experienced executives and industry experts echo a few themes:

  • Make space and time for innovation
  • Build a culture of experimentation
  • Celebrate innovation

It seems the Space-time connection is still relevant, and even crucial to sustained innovation. Making space for innovative thinking can range from a simple idea wall or virtual comment box to a fully-funded innovation incubator. Organizations often make space for innovation, but fail to make time for innovation. According to Clayton Christensen, the father of Disruptive Innovation, “If you defer investing your time and energy until you see that you need to, chances are it will already be too late.”

SPACE and TIME are essential to take an innovative idea to actual implementation. Once the ideas start flowing, someone has to be able to do the actual work – whether that means investigating a market opportunity, talking to customers about their interests or doing a little development to test a minimum viable product – and it will take time to figure out if, when and how an idea helps the customers and the company.

Building a culture of experimentation means finding ways to ensure that every individual in the entire company can embrace and test innovative ideas, discovery and the development of innovative ideas. It goes unspoken that the day-to-day work of delivering solutions must get done. However, just envision the power and potential that companies could experience if they successfully make time and space for innovative exploration and experimentation interwoven with their deadline and delivery demands.

When organizations invest in and promote a culture that makes space and time for innovation, I suspect the celebration piece will likely take care of itself. Although we may not see DeLoreans traveling through time, there is no doubt we will see new innovations that improve the quality of life for people around the world.

Improving Sustainability at Commercial and Industrial Companies: It Begins with Measurement

As I read the news of those who hit the streets for the climate strike, I reflected on my own habits. I consider myself an environmentally responsible person. But what am I actually doing and how am I improving? Am I measuring my impact? As the saying goes, if you can’t measure it, you can’t improve it.

I take public transportation a lot, walk and use a bikeshare. I barely turn on my TV…but I have not one but two laptops, two phones, a computer monitor, home printer/scanner, shredder – and everything now needs to be plugged in and charged. These technological advancements seem like “necessities,” but do I really need to use an electric toothbrush? How much is our technologically-advanced lifestyle adding to energy usage and to GHG emissions? Is it a drop in the bucket, or contributing to a rise in sea level?

Each month when I receive my utility bill, I revel in how low I can get my bill ($25.67 is my 12-month low currently). However, in the peak months of the summer when the air conditioning is “needed,” I’m just guessing on my energy usage until the end of the month and then am dismayed with a $150 bill – too late for me to make a change in usage.

Some of our commercial and industrial (C&I) customers have been telling us they don’t want to be surprised either when the monthly utility bill comes. C&I customers would like access to their electric and water usage data frequently enough so that they can detect unintended usage or waste quickly and take steps to improve their sustainability numbers. That’s just what we at Itron Idea Labs are working on – getting customers the energy and water data they need enterprise-wide and as close to real-time as possible so that they can identify ways to reduce waste and unintended usage. Because once it is measured, C&I customers can improve – and small changes at large companies can make a big difference.

If we want to REALLY be sustainable, we have to take a more active approach at reducing our impact in the world. That all starts with knowing how much we are consuming and emitting. To learn how Itron can help your business measure your energy and water usage and take measures to improve, visit

Innovation and the Inception of Itron Idea Labs

Nine out of 10 Fortune 500 companies in 1955 disappeared from the list by 2016. The average tenure of a Fortune 500 company decreased from 33 years in 1965 to 18 years in 2012—and it’s forecasted to shrink to 14 years by 2026. The accelerating rate of technology development and disruptive innovation are the key drivers of this trend.

Itron has always been an innovator in the utility industry, but I saw an opportunity for disruptive innovation. In 2014, I thought it was time to introduce a new approach, which we now call Itron Idea Labs.

Read the full story about how I formed Idea Labs to embrace industry-leading, disruptive innovation in my new book Innovation for Survival. In the book, I explain the successes and failures of projects at Idea labs and the importance of disruptive innovation to deliver breakthrough products to customers.

I’ve worked with a variety of leading technology companies including Google, Edico Genome, Walt Disney and Paul Allen’s innovation incubator, Interval Research. These experiences helped me understand the benefits of an entrepreneurial approach to innovation.

In the book, I explain how Idea Labs was able to replicate startup methodologies within an established company. I present the strategy that we developed at Itron Idea Labs through lessons learned from both failures and successes. The book describes our process of pitching an idea, developing products and finding the right way to structure a team of innovators. The book is not only a story about a successful experiment, it is also a guide for how to pursue disruptive innovation and fail fast.

The purpose of this book is to provide a practical guide to building an innovation lab in a large corporation. We all learned a lot and I believe we cracked the nut of how to build a successful innovation lab in a large corporation. This story is not finished, as we continue pushing forward to get into even more exciting times.

If you are interested in the journey of innovation, purchase Innovation for Survival on Amazon today.

My Friend Went 100% Solar. . . Indirectly

I was speaking with one of my friends recently and they were proudly telling me that they signed up for their utility’s 100% solar rate plan. I played dumb and asked them what that meant. They said that for this program, they pay a little extra and their utility supplies them with solar power. Going a little further, I asked “what happens when you use electricity at night?” They hadn’t really thought about it, but now they were curious.

I explained that when I was recently visiting my parents in Indiana, I saw my dad do something he does every month – he goes down to the basement with his pencil and paper, looks at his solar inverter and writes down how much electricity was produced. Then he enters that value into a web portal where he sells his solar renewable energy credits (SRECs). He often sells the SRECs to other states, which means sometimes a utility in Maryland gets the credit for the clean energy produced in Indiana.

I paused to clarify – my dad doesn’t sell clean electricity. He sells the rights to claim credit for that clean energy. This forms the basis of the Renewable Portfolio Standard, which has been a very effective mechanism to help many states meet their clean energy goals—and this is also how your utility provides you with a 100% clean energy rate plan. It procures a certain amount of clean energy itself and then it offsets your additional usage through mechanisms like RECs.

Based from the look on her face, I thought I had totally confused my friend. She said, “No, I’m not confused. I’m dissatisfied. It seems a little indirect – like I’m choosing clean energy in a round-a-bout way.” She wasn’t confused, she was exactly right. She had also totally taken my bait!

“Funny you should say that,” I said. “I just happen to be working on a project that provides a new way to choose clean energy in a more direct way.”

Itron Idea Labs is using near-real-time grid emissions data to enable end customers to use electricity when emissions are lowest in their region. Let’s say you have a smart thermostat – we know that your air conditioner needs to run 20 minutes to keep your house comfortable for the next two hours. Your air conditioner can either run continuously for 20 minutes or it can spread it out – 5 minutes here and 5 minutes there – based on when emissions are lowest. If enough of your neighbors do this too, the power plants with the highest emissions will run less. Lots of small changes add up to big emissions reductions.

As it turns out, providing this service to customers also helps solve several emerging problems for utilities. For one, if we aren’t paying close attention to emissions, operating battery storage devices can make the grid dirtier. This is exactly what happened with batteries deployed through California’s Self Generation Incentive Program (SGIP). A November 2017 report by Itron showed that because the emissions content of electricity is not directly reflected in the price of electricity, batteries operating on price signal alone could (and did) increase emissions.

Controlling smart devices like thermostats, electric vehicles, battery storage, refrigerators and pool pumps according to price, local grid needs and emissions content can have many benefits for utilities. In addition to the battery storage example, this service can be used to reduce renewables curtailment, increase the effectiveness of demand response programs, improve overall grid flexibility, and perhaps most importantly, improve customer engagement by directly involving them in the decarbonization of electricity.

Itron Idea Labs is focused on bringing new, innovative businesses, products and services to Itron customers. For more information, click here.

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