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Academic Users Group

6 Posts authored by: Erica Trump

The Academic Symposium at PI World 2018 is the largest and most diverse Academic Community event that OSIsoft has hosted to date. In all, we had around 220 attendees, of which ~25% were from academia and ~75% represented our industrial customers. We hosted an AM Industry Innovation session and a PM Workforce Development session. The day included several podium presentations, panel discussions, a workshop, and a networking dinner.


Presentation recordings are now available on the OSIsoft website. Just click the preview images below to stream the videos.


To all who attended, thank you for spending the day with us! Your engagement and participation made this event a success.


AM Session: Industry Innovation


1. Welcome and Overview of Day

John Matranga, OSIsoft


2. Utopus Insights Journey: An innovative company launched from Vermont Electric Power Company

Kerrick Johnson, Utopus Insights


3. Partnering with Academia to Develop Advanced Analytics Platform To Accelerate US Manufacturing Competitiveness

Scott Miller, Texas A&M University


4. The Journey from a Classroom Idea to Commercialization of an Energy Management Company

Mike Broeker, Building Ideas Group; Mike Mihuc, OSIsoft


5. Lightning Round Talks: OSIsoft Call for Collaboration – 1st Year Innovation Showcase

Ashkan Negahban, Penn State; Denis Grancanin, Virginia Tech; Frank Lee, UC Davis


6. Panel Discussion: Student Engagement with Real-World Data

George Paterson, University of Iowa; Pratt Rogers, University of Utah; Steve Moore, Del Mar College; Leo Vitor, Radix; Erica Trump, OSIsoft



PM Session: Industry Innovation


7. Welcome from OSIsoft VP of HR

Dawn Sprague, OSIsoft



8. Keynote from Academia: Revamping Student Education with Real-World Data

Brian Davison, Lehigh University



9. Multidisciplinary Collaboration for Student Education - UC Davis PI Systems for Learning & Research

Kiernan Salmon, UC Davis; Jill Brigham, UC Davis



10. OSIsoft Cloud Offering: Transforming Student Education with the Academic Community Service

Zhiyuan Cheng, Industrial Learning Solutions; Erik Ydstie, Carnegie Mellon University; Erica Trump, OSIsoft



11. Student Education – Keeping Pace with Industry Trends: TransCanada Sees a Need for New Skills

Emily Rawlings, TransCanada; Keary Rogers, TransCanada


Erica Trump

PI World Hands-On Labs

Posted by Erica Trump Mar 5, 2018

Attention, academic attendees at PI World 2018!


We’re excited to have so many of you join us in San Francisco for the 2018 OSIsoft Academic Symposium. This event will kick off the conference on Monday, April 23rd. PI World 2018 will be full of opportunities to learn how the PI System is used to solve business challenges, to interact with industry representatives, and to learn about OSIsoft technologies.


Our PI World Hands-On Learning Labs provide one such opportunity. These hands-on labs occur on Thursday, April 26th and Friday, April 27th. Note that pre-registration is required. You may register for the labs when you register for PI World. If you have already registered, please email to update your registration.


These labs will be of particular interest to the Academic Users Group:


A Digital Plant Template for Operational Insights - An Enterprise Strategy

This lab uses a follow-the-money strategy to provide an example that integrates the AF/Asset Analytics/Event Frame data for running a plant. In this lab, you will learn how to bridge the gap between production planning and execution and to simplify implementation for production monitoring. We will run simple analyses that will help increase production yields and reduce operating costs with an integrated approach for Overall Production Management. Power User Lab.






Advanced Analytics for PI data for Data Scientists

PI System is the standard time series data infrastructure across several industries. Decades of operational data collection has turned each PI System into a treasure trove for data scientists to extract knowledge. Come to this lab and learn, as a data scientist, how you can access, shape, and use PI data to generate insight and knowledge. A basic understanding of data science basics is required for this lab. No knowledge of PI System is necessary.


Fit for Purpose - Layers of Analytics using the PI System – AF, Matlab, Machine Learning

This hands-on lab covers scenarios to illustrate the different levels of analytics that are fit-for-purpose when using the PI System. For example, what calculations and analyses do you do in AF? When do you use Matlab and similar libraries for advanced calculations that hook into AF? When do you call on “data science and machine learning ?” Use cases will include those focused on an equipment, such as a pump, motor or compressor, and those focused on a process. We will also cover examples of advanced analytics that are part of the data collection from the edge devices and contrast these with predictive analytics – both the model development and model deployment (scoring new incoming real-time data) and include cloud vs. fog vs. edge scenarios.


Introduction to PI System Developer Technologies

This lab is designed for software developers new to the PI System who desire programmatic access to it. You will be introduced to various Developer Technologies that you can leverage in your custom application to interact with the PI System. You will have some hands on experience with each technology. At the end of the lab, you will walk away with knowledge of their basic capabilities and also know where to go if you want to dive deeper into them.

The talks from the orientation session were:


1. PI System 101 - General Introduction to the PI System for Academic Users

2. OSIsoft Collaborations with Academia - Pathway to Success and Grant Partnering

3. Getting Started with PI at your University - First Semester Tools for Success

4. OSIsoft Learning Resources - Transform Your Classroom

5. A Classroom Example and Hands-on Demo


Video recordings will also be available soon.

We put together YouTube Playlists to supplement the morning orientation session at the 2017 Academic Symposium.


Here they are:


PI System 101 - General introduction to the PI System for Academic Users

Academic Symposium - PI 101 - YouTube

Getting Started with PI at Your University – First Semester Tools for Success

Academic Symposium - Getting Started with PI - YouTube


Remember to check back after the event for slide decks from these and other sessions!

We’re sharing a demo based on an IoT device that we call RoomBot. This is a simple device that we designed for educational demos. It’s easy to assemble and easy to integrate with PI.


We want you to replicate this setup for use in your classroom! We documented the RoomBot setup steps and are sharing it here. We also share the sketch that we used to program the Arduino and the associated Python code that writes the data to PI using PI Web API.


We used this device to collect room data at the Johnson City office. We spotted interesting trends right away!





Getting Started:


This project had a small start-up cost. Arduino devices are cheap and the learning curve is small.


I’ll admit to being a little intimidated at the start of this project. I was not at all familiar with Arduino devices or any kind of microcontroller. I also don’t know Python, although I am competent with scripting in other languages.


I was excited to find that working with Arduino devices is simple! I was writing sensor data to PI within two hours of unpacking the device.


To start, I downloaded the Arduino IDE software, as instructed by the packaging, and loaded an example Sketch called “Accelerometer”. The sketch programs the device to read data from the sensors (accelerometer and gyroscope sensors) that are built into all Arduino 101 devices.


I then found an example Python script that reads data from Arduino devices using a quick Google search. I modified this quickly and added some lines of code to write data to PI using REST calls through PI Web API. And that was it! A quick and dirty prototype, with sensor data writing to PI.


We then passed the project over to a team of two engineers in the OSIsoft Johnson City Office: Steve Edwards and Caleb Steiner. They experimented with different Arduino sensors before coming up with the final RoomBot setup. The RoomBot has temperature and light intensity sensors, as well as a knob that is attached to a potentiometer; adjusting this knob mimics a set point change. They built an Arduino sketch for their setup, perfected and documented the associated Python code, created a schematic of the Arduino wiring, and documented their work. We’re sharing all of their work with you here.


Steve and Caleb also did some setup in PI for the demo and documented their steps. They setup the Arduino device in PI, using a template, and created a web-based visualization. We later brought a second Arduino online. Now we’re able toggle the display to look at data from either device.


Other Projects:


We've had a number of projects collecting data from Arduino devices and sending to PI that were posted to PI Square.  These include the following posts:

  1. Daniel Lopez used Powershell scripts to pull in data from various sensors, including solar cell output, ambient sound levels, equipment vibration, air temperature and humidity,     and motor current and position.
  2. Barry Shang hooked up his Arduino with a simple temperature sensor to monitor in his office, and collected the data with similar Python code, also writing data through the PI Web API.
  3. Butch Payne had a similar setup as Barry to collect temperature data from an Arduino, but instead passed the data through a Microsoft Azure Event Hub, before consuming the data with the PI UFL Connector


We’ve found many ideas for IoT projects with Arduinos or similar devices. Using the above methods, this data could also be collected in PI.


Some links with these project ideas include:


Some interesting ideas included:

  • Collecting additional environmental data (humidity, pressure, soil moisture)
  • Intelligent bug zappers
  • Gas detection (e.g. natural gas leaks, radon)
  • Smart meat smoking

Do you use MATLAB in your academic projects? If so, you should check out the recently released PI-to-MATLAB Utility! This simple, graphical tool allows you to import PI data into MATLAB. In almost no time, you'll be making use of MATLAB's computational abilities to enhance your time-series data.


Screenshot-PI System to Matlab1.png


For more information, reference the PI Developers Club White Paper: Using the PI-to-MATLAB Utility. The install package and the C# code for the utility are freely available on GitHub.