Water Online

MAR 2017

Water Innovations gives Water and Wastewater Engineers and end-users a venue to find project solutions and source valuable product information. We aim to educate the engineering and operations community on important issues and trends.

Issue link: https://wateronline.epubxp.com/i/795216

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Page 18 of 34

By Dr. Andy Shaw A t a very basic level, Big Data just means we have a lot of data. Water utilities see data from supervisory control and data acquisition (SCADA) systems, including flow statistics, online monitoring, dissolved oxygen (DO) measurements, and air flows, as well as data from laboratory information management systems (LIMS) and computerized maintenance management systems (CMMS), to name several examples. Such data is beneficial, and much of it has been around for years. Unfortunately, the way data is gathered at treatment facilities is often fragmented. There are silos of data in computer systems that don't always talk to each other. The Internet Age has ushered in the ability to funnel disparate data into a single, meaningful pool of information that allows water and wastewater treatment plant operators to understand, manage, and use it to optimize plant reliability and performance. Big Data initiatives and new data management tools enable us to turn all that data into understandable, useful information that helps us become more proactive and make better decisions about plant operations. For example, Black & Veatch offers ASSET360™, a smart analytics platform to give utilities, cities, and other entities a holistic, 360-degree understanding of their infrastructure-based systems. Although the focus on Big Data in the water industry is relatively new, comprehensive data management isn't new for energy utilities; Black & Veatch has provided asset analytic solutions to utility clients for more than 20 years and has operated a smart analytics monitoring and diagnostics service for more than 10 years. The company's utility analytics include operational intelligence and adaptive planning solutions. Sometimes You Have To Get MAD To Be Smart No matter what specific services or tools water and wastewater utilities choose to use, it's important to develop a management plan, pull all important data together, and take advantage of dashboards and smart screens that use that data to perform calculations and identify trends. Then, utility managers can break the information down to answer questions such as "Where am I using energy or spending my dollars?" or "What am I spending on energy and chemicals in different parts of the facility?" Furthermore, utility staff with such information in hand can proactively identify potential problems before they happen rather than react to something such as a broken pump. Although SCADA systems have real-time capabilities, displaying current status and immediately warning of problems, being able to predict a potential problem through use of smart analytic platforms is a game changer. The next step — pooling data and using analytical tools to predict where we should be heading to become more proactive — is a big one for the water industry. We're getting smarter all the time. Becoming smarter, however, requires focus on the quality as well as the quantity of our data, shifting our focus from Big Data to bad data. If sensors are not cleaned, calibrated, or properly used, for example, it doesn't matter what we do with the resulting data. The starting point is to make sure you have good primary measurements. In Smart Water Utilities: Complexity Made Simple (IWA Publishing, 2016), Dr. Pernille Ingildsen and Dr. Gustaf Olsson consider what utilities need to do to be smart. They boil it down to a simple, yet very useful, framework and suggest that water 16 wateronline.com n Water Innovations Understanding Big Data In The Water Industry The next step — pooling data and using analytical tools to predict where we should be heading to become more proactive — is a big one for the water industry. If you feel like you have too much data but not enough understandable or usable information, fine-tuning data collection and funneling it into an integrated data management system may be the way to become more proactive and make better decisions.

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