The Internet of Things and Sewers

Aug. 1, 2017
Optimize Maintenance, Lower Operating Expense and Extend Asset Life

When the San Antonio Water System (SAWS) found itself struggling to keep up with the growing demands of cleaning more than 200 sites on a frequent basis to prevent sanitary sewer overflows (SSOs), they turned to monitoring technology for a solution.

Not only has this resulted in lower cleaning costs while preventing SSOs, SAWS is also getting longer life out of its pipeline assets as some are considered high risk and can be damaged by high frequency cleaning (HFC).

Although HFC has long been considered a best practice in the industry, it could also be described as a last resort because of the high operating expense and asset wear. In addition, HFC is essentially a “blind” process because there is no visibility into pipe conditions between cleanings.

SAWS started its journey to optimized maintenance with a one-year study to determine the return on investment achievable by using the Internet of Things to automate and determine when to clean instead of cleaning according to a set schedule.

SAWS selected 10 high-frequency cleanout sites. SmartLevel™ remote field units were installed at each site to monitor levels and watch for pattern changes. For this demonstration project, SAWS suspended its HFC cleaning protocols and shifted over to cleaning only when the SmartLevel system indicated it was necessary.

Using SmartTrend®, the analytical and patented software tool included at no cost with each SmartLevel system, SAWS monitored day-over-day level trend changes and received automated messages for trend anomalies.

Analysis of the real-time monitoring data automatically detected small but potentially important changes in water levels. It showed systematic variances from “normal” diurnal fluctuations. Daily automated scans of each site revealed either rising trends, indicating a potential downstream build-up, or falling trends, signs of a potential upstream build-up.

The combination of real-time monitoring and trend analysis provided powerful, predictive insights into the behavior of the collection system, enabling users to have visibility into a potential problem days or even weeks ahead and concurrently providing continuous overflow protection.

The San Antonio Water System turned to monitoring technology to keep up with sewer cleaning demands


During the 12-month test period, SAWS performed only seven cleanings based upon the monitoring and trend analysis (five at a single problematic site). This compares with the 120 cleanings called for under normal HFC scheduling, representing a 94 percent reduction in scheduled cleanings.

Other than a three-day period in May/June 2016 when nearly 16 inches of rain overwhelmed the SAWS system, there were no SSOs at the pilot locations during the non-flood months of the test period.

As demonstrated by the pilot program, the number of times maintenance trucks are mobilized to clean HFC sites dropped by 94 percent.

Based on SAWS estimates of about $500 per cleaning, the payback time for the monitoring equipment is less than one year, and the net savings is $1,500 to $4,000 per monitored location per year. Additionally, high-value human and equipment resources are freed for more pressing needs, risk to staff is reduced, carbon footprint is minimized, and the risk of spills at monitored locations is dramatically reduced.

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