The Internet of WherePosted for Esri
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- Posted on May 24, 2018
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I just made up the term Internet of Where (IOW).
The Internet of Things (IoT), sad, and the Internet of Everything (IoE), sadder, are so last year. The term IoT was first coined by Kevin Ashton back in 1999 in relation to RFID tags and supply chain. The problem with the term IoT is that it conjures up images of a bunch of things, like the stuff you stored in your attic, your garage, or your basement. What Ashton was thinking about was data, not really things, but more specifically real-time data. What an RFID tag did was measure data about things. Things that are happening to things. The value of IoT is not so much about the data itself but about the decision-making that results from the data. If a baseball stadium has a dome roof and the stadium sensor measures rainfall, then the roof closes. If a sensor measures a drop in pressure, then a valve closes.
Utilities used the concept of IoT well before Ashton coined the term. When I was a young intern at a power company, the latest buzz was about this new technology called SCADA. SCADA stands for supervisory control and data acquisition. The system consists of sensors connected to remote terminal units (RTUs) that transmit sensor data to a central computer system. The data is displayed on a big board. SCADA is two way. It can send a signal to do something back through the RTU. It can open or close a switch or lower the tap setting on a transformer. The communication systems back in the old days were dial-up modems working over telephone lines. So technically, it wasn't IoT since the Internet hadn't yet been invented, but the idea was the same. A sensor network gathered data (voltage, power, temperature) about things (electrical things). The system gathered data centrally where people made decisions about what the data meant. When the sensors suggested bad things had happened, operators would act.
With all due respect to Kevin Ashton, the concept of IoT has been around for a long time. Power plants, factories, traffic controls, and fire alarm systems have all been using sensors to measure, then to act.
What has changed is the volume and diversity of sensors.
In the old SCADA days, there were, perhaps, thousands of SCADA points. Their location was known. When an alarm sounded, experienced operators knew what to do. Today there are billions of sensors, some controlled by utilities, most not. The difference in the SCADA world was that each sensor typically signaled a singular event. A high value of electrical current signaled there was a short circuit. A breaker would trip. People would be out of power. However, the power company didn't know exactly what happened and where to send a crew. What if people saw a flash and Tweeted about it? Those two pieces of information together would provide a clue as to what happened and where. What if a lightning sensor network indicated a strike near where the people Tweeted? What if a video feed from the 7- Eleven across the street saw a flash and automatically notified the security company? What if there were sound sensors mounted on poles? What if? What if? If the utility company had access to all these sensors, staff could immediately locate the problem area and dispatch a crew rather than patrol the line and guess where the problem might be. They would organize the sensors by location—ah. These events happened at roughly the same place.
The more sensors in play, the better the decision-making. The key is location. That's why I decided to coin the term, the Internet of Where. Sorry, Kevin Ashton. The notion is that each sensor by itself has limited value.
It's the collection of sensors, organized around a location, that provides the best decision-making.
That's where geographic information system (GIS) technology comes in. Unlike specialty control systems, like SCADA, and advanced distribution management systems or meter data management systems, GIS can bring together data from any sensor. It can take data from SCADA and Twitter, from lightning systems and metering systems, from traffic control systems, from weather stations, from vehicle tracking systems—you name it. The ArcGIS platform consumes sensor data and organizes data by location. It provides easy tools to analyze trends and make sound decisions. Decisions that reduce cost, improve customer service, reduce outage time, and even make things safer.
Yet the GIS platform provides more. In addition to measured data from sensors, GIS routinely manages all kinds of other data. In fact, GIS manages five distinct kinds of data sources:
- Authoritative—Known attributes such as age, maintenance history, material type, part numbers, network connectivity
- Predicative—Things we know might happen, such as where floods might occur or areas of fire hazards or landslide areas
- Measured—Sensor data
- Experiential—Information that experienced people just know (How to capture this data is left for another discussion.)
- Crowdsource—Data from social media and other crowdsourcing apps
Organizations often make decisions based on only one or two of these data sources. The ArcGIS platform provides the data management tools to bring data together. It organizes by location. It uses geoanalytics tools to make sense of the disparate data. It maps and visualizes for easy decision-making. It makes sharing the results with anyone, on any device, easy.
See, that's why the ArcGIS platform is really an Internet of Where technology. Ashton would be proud. Find out more about how GIS can provide your utility with intelligent use of real-time data.