Sewer inspection reports allow wastewater teams to review and share vital information about a system’s condition, functionality, risks and maintenance plan. They highlight data from sections, inspections, observations or ratings, and they serve as records that can be referenced for future maintenance, planning and trends. And the data they contain ensures more informed decisions are made regarding rehabilitation and inspection.
Ovality measurements can identify potential risks to a pipe’s integrity, making them a vital part of sewer inspection and maintenance. With a laser profiler and WinCan on hand, wastewater teams can easily gather information about a pipe’s diameter as part of a routine inspection. Inspection teams simply need to gather media, calibrate the Laser Scan module in WinCan and record the data.
When your primary focus is sewer inspections, it’s easy to lose sight of wastewater’s intended destination: a treatment plant. Wastewater treatment is the process of removing organic and inorganic matter, chemicals and other pollutants from water, ensuring it is clean and safe for discharge into the local environment.
Sewer inspection workflows vary from one municipality to the next. They are often built around the structure of the inspection team, but equipment, budget and the size of a sewer system all play an important role in determining what workflow makes the most sense for a given community. With so many different inspection, asset management and mapping solutions on the market today, there is no end to the possibilities. Take a look at the workflows below to get an idea of how WinCan workflows compare to more traditional, manual workflows.
Data takes on new meaning when it’s laid out on a map. Heat maps, iconography and geographical features all help build a clearer picture. The human brain naturally processes images differently than it does letters and numbers, allowing us to gain a unique understanding of data sets and how they interact with each other. In the world of wastewater management, mapping data can make it easier to understand where a sewer system is located, as well as potential risks to the community and infrastructure.
Like most of America, the village of Addison, IL sits on aging sewer infrastructure. But investment in new tools and technology have helped Addison sustain a healthy system in the face of population growth.
The Chicago suburb’s sewer division has made significant changes to its workflow over the past five years to adapt for new development, but Addison isn’t quite done growing. With the addition of two new subdivisions, the village anticipates added wear and tear on aging sewer infrastructure, and the sewer division is outfitting itself with the future in mind.
When approaching sewer maintenance, inspection teams need to both see defects and determine what kind of defects they are. That might not be asking much of a NASSCO-certified engineer, but the simple task of seeing and identifying defects is a tall order for artificial intelligence (AI), which is only starting to scratch the surface of its true potential in the wastewater industry.
As technology continues to shoulder more and more of our inspection workloads, it’s easy to forget that having enough qualified people to operate equipment, code and convert data, manage deliverables and analyze sewer infrastructure is just as important as having the software and equipment itself. But even with the right team, workloads can spike when you least expect it, causing your team to take on more work and stress, with the ensuing risk of delays and mistakes. AI-enabled data services allow your team to leverage the power and efficiency of AI, hands-on verification from data professionals, and fully integrated cloud hosting without breaking the bank or your team’s backs.
WinCan has always evolved to meet the needs of the wastewater industry. Now, in a continued commitment to industry-leading sewer inspection solutions, WinCan is proud to introduce Sewermatics, a new collection of AI-powered services that help you get more out of your inspection data.