Susan Smith has worked as an editor and writer in the technology industry for over 16 years. As an editor she has been responsible for the launch of a number of technology trade publications, both in print and online. Currently, Susan is the Editor of GISCafe and AECCafe, as well as those sites’ … More »
Space-Time Insight Takes Situational Intelligence a Step Further
April 7th, 2015 by Susan Smith
Technology for electric utilities is not always particularly exciting, but Space-Time Insight raises the bar for the industry in terms of providing virtual reality to actually access and analyze situations arising in utility facilities.
Space-Time Insight has been shipping products since 2008, according to Steve Ehrlich, senior vice president of Marketing and Product Development. Although they focus on the utility industry, they also have customers in logistics, federal and supply chain markets.
“We take data from across the organization, i.e., their operational data from meters or sensors as well as enterprise data from SAP or Oracle applications, external data from weather, vegetation and fires,” said Ehrlich. “We correlate and analyze that data and visualize it through different types of user interfaces.”
Some examples include:
The California Independent System Operator (ISO) uses Space-Time Insight’s software in its state-of-the-art control center to manage the state’s grid. Applications include the visualization and analysis of the condition of the grid, assessment of threats from fires, the impact of congestion on market prices, and the optimization of the use of renewable energy to meet the state’s goals.
“They also look at wind and solar energy and forecast the use of those renewable sources to make sure they’re leveraging them as best as possible,” Ehrlich said.
Hydro One uses the Space-Time Insight Asset Intelligence solution to improve the reliability of the grid and the company’s 4.5 million transmission and distribution assets. Pulling data from thirty different systems, the application visualizes and analyzes seven risk factors for all assets and asset classes. Developed in partnership with Accenture, the software saved Hydro One $1.5M within the first 6 months of deployment, with savings of 5 times that amount expected over the next few years.
“They use software to do asset analytics, to understand when assets are going to fail, and determine which assets need replacement and when and what is the risk of failure across their infrastructure,” said Ehrlich. “This whole concept of taking data from the operational side, combining it with the traditional enterprise type data, then combining it with the external data and very specifically geospatial data as well – is the core of situational intelligence. It’s being able to analyze all those things, visualize the output of that analysis of the data.”
The various visual formats that Space-Time Insight uses are maps, charts, data tables and any other new formats. “When looking at transformers to do a dissolved gas analysis, and they have this format called a Duval triangle,” Ehrlich explained. It’s a unique way of looking at data specific to that asset, so the format differs depending on the problem you’re trying to solve and the volume of data you’re trying to look at. Very often our applications consist of a combination of all those.”
“When I look at my assets on a map, if I click on one it might be color-coded to show me that it’s red,” said Ehrlich. “It would bring up information about that asset, as well as performance data, and I could click on further details, click on the chart to see how that asset has performed, and then might click on another chart to see how that asset might perform in the future, then overlay other information. The impact of weather, loads from collected from smart meters, and many other points can be incorporated in the picture.”
Space-Time Insight takes those types of visualizations into a new world of virtual reality. In the “internet of things,” the volume of data and the quantity of the speed at which that data is arriving, is far greater than traditional user interfaces know how to deal with.
“Traditional business intelligence tools were not designed to deal with real time data and data of this kind of variety,” said Ehrlich. “They were designed for historical analysis. We are using technology that originally came out of the gaming industry to address how to visualize data at very high volumes and also do it in interesting ways.”
“One of our customers already uses our technology to visualize data from sensors on the grid and generate data at 30x per second,” Ehrlich said. “They have billions of data points every month that they have to analyze and visualize in some way. That’s a new breed of visualization that’s coming to the fore. Recently we took that one step further by bringing that technology and gaming tech into a virtual world by allowing users to put on an Oculus headset and immerse themselves inside the virtual world.
With the Oculus headset, users can walk through a virtual substation. They can walk up to an asset and understand the state of that asset by looking at it. They can see immediately if it’s on fire or gas is coming from it, and then also see data related to that asset as part of the being in the virtual world. Users can click through many different charts, data sets, etc. to try and understand a problem, whereas if they are standing in front of an asset and they can see smoke coming out of it, they will know what the problem is right away.
With mobile assets, such as planes, trains, and ships, a virtual environment allows an operator or technician to virtually board the vehicle while it is moving, to diagnosis issues during operation.
Problem solving time is dramatically shortened.
Data comes from sensors or other points on the asset itself. If it’s a smart meter, collecting data every fifteen minutes, there may be a sensor on a truck for example; they’re attaching sensors on vehicles of equipment. It could also come from weather data. In a virtual world, if the asset is showing it’s on fire, you can look back in time and see if there was a lightning storm, etc. If there is a break-in, you could pull data from a gunshot detection system or security system for unauthorized entry.
Every user has access to certain types of data as well as certain types of presentations of data.
The Oculus headset is available for professionals. “So we’re using that version as a developer, with a consumer version available soon,” said Ehrlich. “As soon as it is, any enterprise will be able to use it and use these types of applications with those headsets.
(From company materials) The advantages of virtual reality for large volumes of data include:
More space for information: because virtual reality offers a 3D immersive experience, there’s practically unlimited space for exploring your data. Compare this with the desktop metaphor, where you get more space by either adding more monitors or opening additional windows and moving between them.
A third dimension for information: because virtual reality is 3D, it offers an additional axis for data display and manipulation. In virtual reality, you can have a cube of data; on the desktop, you can have a table or spreadsheet. Many datasets are inherently three-dimensional. For instance, make, model, and year of cars in a fleet of vehicles.
Context for data from the Internet of Things: An explosion of devices are becoming connected to the Internet and generating data: thermostats, appliances, cars and more. Having an immersive environment that replicates the physical one makes it easier to place all that data in a familiar context, making correlation and analysis much more intuitive.
Expanded repertoire of commands and interactions: because virtual reality allows immersion in and movement through three dimensions, exploring data can draw on a wider range of commands and interactions. The 2D desktop allows actions like click, select, swipe and drag. Virtual reality adds actions such as grab, throw, lift, drop, push, pull and rotate.
Categories: analytics, asset management, Big Data, climate change, cloud, cloud network analytics, data, geocoding, geospatial, GIS, mapping, remote sensing, satellite imagery, sensors, utilities, utility geographic information systems