Latest Contributions by Pat_Hohl

https://mediaspace.esri.com/playlist/details/1_9q41da9f/categoryId/290804942 ... View more

The interplay of our world and GIS technology is always moving, and many things changed in 2022. What do you see that has changed in the last year that can be leveraged? Products, data, technology, people issues, whatever... ... View more

Machine learning (ML) is helping solve all kinds of problems, but it just sounds rather unapproachable. Most people have heard the term, and many are not sure exactly what it means. How can it help solve utility business problems? Later in this blog post, we'll look at three words that will help anyone become what a colleague of mine calls buzzword compliant in machine learning. Given the surge in data and analytics, the term "machine learning" is appearing everywhere. It's a subset of the artificial intelligence field. That makes it sound a little like science fiction, but it is not. Modern cloud data storage and computational resources have the stunning capacity to help address real business issues, particularly with ML techniques. Machine learning uses generic programs rather than creating specific programs for each new business challenge. These programs evaluate data to identify patterns and then use those patterns to form predictions. In a sense, the machine, or computer, learns from data about past experiences and applies that learning to the problem at hand. Machines learn the same way we humans do. Someone often tells us what to expect (algorithm), we have experiences (data), we make observations and form our own ideas about patterns (training), and then we apply those patterns to future experiences. My wife has learned to read my mood by my facial expression and location. Even though she doesn't have direct knowledge of my inner thoughts, when I make "that face" in the kitchen, she has learned I'm unhappy that the kids left their dishes in the sink. She has observed a pattern and therefore makes accurate predictions. 1. Model In the field of ML, "model" doesn't yet have a standard definition. Think of the model as the system that embodies the techniques, programs, and data. It's the model that will ultimately yield results. You might inquire about a certain model's performance on a new dataset. If you were to ask a data scientist if the model was ready to solve your problem, the reply might be, "The model isn't accurate enough yet; it still needs more tuning." 2. Algorithm An algorithm is a procedure for completing a task, like a recipe. In ML, it's a mathematical approach to finding the patterns in the data. ML software includes libraries of these generic programs that can be used in your models. There are many algorithms written by mathematicians, each with its own strengths and weaknesses for different situations. They often have cryptic names like empirical Bayesian kriging (EBK) or ordinary least squares (OLS), and some testing is required to find the best algorithm for each application. Data science training is usually necessary to select the best algorithm for a particular task. 3. Training Training helps set ML apart from other types of problem solving. The model is trained using a set of data with known outcomes. It applies the algorithm to analyze the training data, finding the correlations and patterns in that data. Once the model is sufficiently trained, it can then be used to make predictions on new data where the outcomes are yet unknown. Solving a Real Problem Electric utilities turn service on and off as part of normal business. For most utility customers, this doesn't happen very often. However, for some, this action is required as frequently as several times a year. This could be due to people moving in and out, or to unpaid utility bills. Some utilities install meters that can be turned on and off remotely from the office, without the need to send an employee and a vehicle to the location. These meters save time for the customer while reducing transaction costs and environmental impact. How could a utility analyze data to predict which customers would benefit from these more expensive meters? To address this problem, we could assemble data from past orders and make predictions about future turn-on-and-off activity. The data could include account type, rate, payment history, bill amounts, address, etc. We would choose an algorithm, gather historic data, and train the model. This model could then be used to examine current accounts and predict which of those are most likely to have a high demand for this service in the future. In this example, as with most utility concerns, information about location would be priceless in helping to solve this problem. We understand that university students occupy apartments with the school cycle and then often move out for the summer. Student moves directly affect electric service orders. If we could also use location information, such as proximity to universities, the model could perform even better. Machine learning techniques will continue to evolve. As they do, it's important to include location intelligence every step of the way. Location is a natural part of utility data preparation, model training, and meaningful predictions. There is no better way to incorporate location intelligence in ML than with GIS. The job of exploiting big data is far too great for manual analysis. Utilities need the best tools and techniques to find actionable insights in data, visualize the results, and clearly communicate the impact to stakeholders. The ArcGIS platform includes these tools along with powerful location-based machine learning techniques. The next time you come out of the kitchen and someone reads your mind based on your facial expression, realize that they are using the same technique as machine learning. Find out how location intelligence and machine learning can address your business challenges.     ... View more

Who's going to DT in San Diego next week?  What are you hoping to see and learn? Esri will have an entire team on-site, with a particular emphasis on Security and Imagery uses of ArcGIS. In addition, it will be a fantastic time to see the latest from Esri business partners in the Esri booth - ENER-i.AI, Eos Positioning Systems, Epoch Solutions, Geonexus, Locana, & UDC, and many other partners exhibiting at DT.    ... View more

A 2-part webinar series was held in April 2021featuring Tactical Awareness, and Collect and Capture workflows for electric and gas utility Field Operations. Introduction blog "Gis Helps Utility Workers do Their Jobs" Video recordings Question/Answer document Tactical Awareness presentation Collect and Capture presentation This webinar featured a post-event discussion. This was a very informative time. A summary of the chat is attached. It contains several useful links.  Please feel free to comment or ask questions related to this topic.    ... View more

The Easy Button for App Development Practical applications on smart devices improve many areas of life and work. Often, these apps use location to enhance both value and user experience. Location helps utility workers be more effective. Moreover, it helps utility customers understand how issues apply to them. Today, people just expect apps to be location-aware. Think about it, how many apps don’t work right when the GPS is turned off?   GIS is widely used for common utility workflows like design and asset management. Beyond these traditional GIS tasks, apps improve other diverse utility functions – timekeeping, safety, customer engagement, environmental concerns, and contact tracing. Utilities seeking these innovative applications have options to buy or even build them with internal resources. Some utilities will prepare specifications, and evaluate proposals before purchasing apps. Others will develop their own apps. Regardless of the approach, it pays to understand Esri location services and how they boost functionality. Apps + Maps for Purpose What is happening around me? How do I get there? What are my options?   Reimagine location in Apps Esri is the premier provider of location services in the world. These services shore up the apps utilities need. Services furnish authoritative basemaps, geocoding, searching, routing, and live data feeds like weather and traffic. Esri’s new offering, ArcGIS Platform, brings cost-effective location services to virtually any application. ArcGIS Platform delivers these services as a Platform as a Service (PaaS). It provides building blocks for developers, who can build and test their apps without cost. A suite of services creates a comprehensive high-quality platform from which to build. See more details in the product launch video. Amazon builds on this platform to provide maps and geocoding to AWS customers. Likewise, Esri’s robust routing services are used by some of the largest logistics companies in the world for their apps. ArcGIS Platform makes using these services much easier. Now, developers can quickly add location functions without learning new tools. They are readily available from the open-source programming interfaces programmers already use - like REST, Mapbox GL JS, Leaflet, and OpenLayers. As a result, this technology can be simply embedded into many existing apps without delay. ArcGIS Platform also introduces a new competitive cost model based on actual usage. Developers work in a free account tier. Customers use only the services that meet their needs and pay as they go. For example, app builders can leverage real-time routing services. The first 20,000 are free. After that, a user would pay $0.50 for 1,000 routes. The pricing calculator to estimate costs is easy to use. Customers with an ArcGIS Online Creator user type (or higher) can also access ArcGIS Platform through their existing licensing. As solutions are deployed, it is straightforward to monitor usage and estimate costs. To illustrate, if an app references the current weather, cost is directly related to how many times that service is utilized. Looking Ahead for Utilities The possibilities for location intelligence in apps and web sites are endless - damage reporting, emergency response, mutual aid, safety awareness, and augmented reality. These all foster higher levels of communication and service.   Utilities continue to deploy apps that personalize the user’s experience and add business value. For instance, many utility customer apps monitor usage and billing. However, few also show the status of nearby outages or construction work. Even employee apps that are typically not map-centric, like timekeeping, benefit from location technology by relating the user to the features around them.   Location technology has never been easier to include within business systems, apps, or future plans. ArcGIS Platform reduces development time by providing strong documentation, widgets, samples, and free training. When planning approaches for apps, organize them to re-use existing ArcGIS content such as web maps and web scenes in new and powerful ways. Such strategies add value, inspire action, and reinforce data-driven decision making. Also, be sure to watch for new solutions and apps coming from Esri Business Partners that leverage ArcGIS Platform and its location services. ... View more

Many people asked to reference Mike Bowen's (AEP) segment from the Electric Keynote at IMGIS.  ... View more

A very agitated Troubleshooter stood before us. They had some spirited opinions about a model of switch that didn’t operate correctly. One occurrence dragged out an already burdensome switching procedure – on the worst possible day. “Something has to be done.” These switches were “falling apart all over!” They knew many that needed to be ripped out immediately. Is that the best course of action? What is the best resolution for the company and the customers? What You See Is All There Is We needed to do something. We had information in front of us -- it made perfect sense. A suggestion surfaced -- create an emergency work order to replace them straight away! “The confidence that individuals have in their beliefs depends mostly on the quality of the story they can tell about what they see, even if they see little.”   “What you see is all there is.”― Daniel Kahneman, Thinking, Fast and Slow A brilliant psychologist, Kahneman determined that we take in information and promptly create a mental narrative. We use only what is right in front of us and form it into the most reasonable storyline. Our mind does this with no conscious effort at all. Furthermore, we are nearly blind to what information is missing. Kahneman says we have an “almost unlimited ability to ignore our ignorance” -- a sobering thought.  Limited Understanding As we talked, we had very limited information about the switches. We needed to understand more. A more careful analysis would ask – what are the consequences of those potential failures? How many of these switches are on-system? What detailed asset information exists? How does this need compare to other operational needs? How should we best apply limited resources? That would require time, too much work, and difficult data. Get it together What’s needed is to conveniently bring all the information together in a way that makes sense to operations – by location. (IoT example) Have you ever seen an operations center without maps? I have not. Maps create understanding with location. Location yields perspective to operational activities and concerns. It’s hard to get all the data together, and harder still to understand it. It would really help to know things like feeder configurations, loads, planned work, past failures, and inspection results. The problem is that utility information is often scattered around different divisions, systems, and formats. Some of it is old, and some is real-time. It is all different. ArcGIS devours data using location technology – everything from spreadsheets to drone imagery! Plus, it analyzes, displays, and distributes business intelligence. Anyone can see the results on a phone app or an infographic. As a result, improved situational awareness upholds system performance and workforce efficiency. Look beyond the isolated equipment issue of the day. Use more data and make better decisions. Leading utilities use a complete picture to optimize their operations. For more information about how ArcGIS improves coordination and operations in the field download our latest e-book about Operations Management. ... View more

Here is a great StoryMap about Digital Twins - it's from the water industry.    The idea of a digital twin is not new, and it has been evolving as technology improves. Today, we are seeing several technologies come together to create what we know is possible. It's very exciting and opens up a whole realm of possibilities to improve training, safety, operations, planning, optimization, and more.  These come together in a digital twin:  Model of the network Asset details Real-time feeds Imagery Context of location and surroundings 3D visualization, AR, VR Analytics, performance monitoring, alerts Use of information across platforms What steps are you taking or planning?  What opportunities do you see?  What data types are you concerned about?  Please comment and share your thoughts.    ... View more