Technology Aids America’s Water Infrastructure

A technological intervention can help much of our water infrastructure at the end of its planned life
By Bob Benstead

Water is the new oil.
In general, the state of our water infrastructure is at a critical point. Much of it is at the end of its planned life, and the costs for renewal run into the hundreds of billions of dollars. Failing or inadequate infrastructure has knock-on effects far beyond the delivery of water to your tap. Failures such as water main breaks and sanitary sewer overflows can impact commerce, degrade environmental quality, create safety issues, and most critically, create health issues in both the short and long term.

There has been much in the news recently about the issues in Flint, Michigan. Aging pipes have leached lead into the drinking water, causing a major public health crisis. But the story is just beginning to unfold, as thousands of children have been exposed to elevated levels of lead, with lawsuits and mitigation efforts underway. Similar to Flint, in 1993, the City of Milwaukee suffered a major parasite outbreak that affected over 400,000 citizens, with 69 deaths. The cause was thought to be contaminated run off entering the water system and one of the major treatment plants. The City of Milwaukee responded with many positive efforts, including major investment in the water infrastructure, the development of collaborative alerts and notifications, and interagency reviews and mitigation planning.

So how do we bridge this gap between future infrastructure renewal and funding requirements, and the need to mitigate potential health issues in the present? One alternative is to take advantage of current innovations in technology, specifically big data, analytics, sensors, and geospatial tools. Most authorities have collected vast amounts of data over the years, but it tends to be housed in silos, with no “connecting of the dots.”

Some of the themes that can be realized with technology

Near or real time use of sensors, integrated with an incident management, can provide alerts when issues are beginning or about to begin.

By having a current understanding of the actual condition of key assets, an organization is in a better position to not only plan for incidents, but to predict areas of risk and fault. This would entail using newer asset management systems that have a dedicated inspection and rating capability. For example, a system that can capture pipe condition ratings in a standardized format (i.e. PACP compliant) can use this data in analysis and planning, thus gain insight into potential areas of failure.

Incorporating asset analytics and risk analysis into an organization’s asset strategy enables both a short and long term ability to mitigate, and perhaps even prevent, potential health hazards due to deficiencies or failures in a system. Analysis should be able to provide information regarding potential failures and degradation over time, work and activities needed to repair or renew, and most importantly, the cost of doing such work (with scenario planning for “how much do I have over x years-biggest bang for the buck,” or “how much is needed to reach a certain condition level”). When risk modeling is added to this capability, the outcomes, and therefore the planning, can change dramatically. Factors such as location, impacts on commerce, health risks, safety, and even reputation can all have an influence on risk. Understand that this is not necessarily an easy task, but the alternatives can be even worse. The key to this is having these functions in a single solution, working together, not in isolated “buckets.”

The terms “Big Data” and “Machine Learning” are heard often these days. They seemed to be portrayed as the answer to all ills, but applied properly, these capabilities can be very valuable. Imagine having a way to automatically sort through vast amounts of data from health clinics, call centers, asset management systems, and sensors and presented in a way that makes sense to organizations. As an example, in real time, an uptick in water quality complaints, merged with an increase in clinical reports for gastrointestinal issues, may point to a potential coliform or parasite outbreak. This would enable both healthcare and water officials to react much faster and alert the public accordingly. Even better, having the ability to portray these incidents visually on “heat maps” could facilitate better deployment of resources, as well as view trends.

Modern Machine Learning is the ability to utilize vast amounts of data and apply that to mission-specific algorithms in order to produce intelligent results in a rapid manner. By taking advantage of enormous computing power found in “Cloud” environments, water operators can use predictive outcomes to improve operations and safety.

Technology can help to solve some of our most pressing issues in the water industry. And while deploying these technologies in a common and interconnected environment is not a simple task, when disparate organizations work together in an organized manner, many of these issues can begin to get resolved. Given the growing demands on our existing water infrastructure and the increasing risk of failures and associated health incidents, the water industry needs a technological “intervention.”
Bob Benstead is the Vice President of Infor Public Sector. For more information visit