Costa Mesa Sanitary District: Creating smoother, safe streets
An intangible benefit is safety. CMSD employees are not subjecting themselves to potential life-threatening injuries by being struck from fast-moving vehicles when they were in the street manually inspecting manhole covers. Another benefit is the ability of transferring nearly 700 work hours employees were spending a year manually inspecting manhole covers to other operational areas such as spending more time cleaning the sewer system and/or performing closed-circuit televising of pipeline to evaluate the current condition of the asset.
When the Costa Mesa Sanitary District (CMSD) needed a more efficient system for sewer manhole maintenance, it turned to the experts at Egen to deliver an innovative solution.
CMSD serves more than 118,000 residents and provides solid waste and wastewater collection services to Costa Mesa, California, as well as parts of Newport Beach and unincorporated Orange County. The sanitary district traditionally spent a significant amount of time and money — more than $100,000 annually — maintaining sewer manholes. The process required many staff hours to manually survey, rate, and service approximately 5,000 manholes along 218 street miles.
To save time, make the most of taxpayer resources, and improve maintenance efforts and public safety, CMSD wanted to streamline manhole maintenance with a technology-forward and scalable solution. CMSD selected Egen to create a solution that improves manhole maintenance using a GoPro camera and Google Cloud technology, and the power of machine learning to detect sewer manholes, analyze them, and rate their conditions.
Every quarter, a CMSD team member drives a car outfitted with a GoPro camera through the entire district of more than 218 street miles to detect all manholes. Since privacy is a top priority, the system limits image processing to the section of street in front of the vehicle.
After each day of recording, the driver uploads images and videos from the GoPro SD card to a local server. The solution automatically loads the data into Google Cloud Storage. A Google Cloud Scheduler workflow detects any new videos at the end of each day and uses machine learning to review the images and videos, identify any damage, and rate each manhole’s condition. CMSD stores final scores in Google BigQuery.
CMSD team members access results through a web application that identifies which manholes require maintenance. CMSD staff members then review the results and determine repair priorities. The infrastructure intelligence solution continues to learn and improve based on feedback submitted by CMSD employees via the web application.
By automating a significant portion of the manhole maintenance process, CMSD is saving nearly 700 employee work hours annually that can now be directed to providing other public services. With this saved public employee time, CMSD cut costs associated with manhole maintenance by 60%.
The initiative is improving public safety with more frequent and effective manhole maintenance, resulting in smoother streets, avoiding sewer blockages, and improving worker access to underground public utilities.
Not only does this scalable infrastructure intelligence solution streamline manhole maintenance, it also allows more frequent reviews of manhole conditions and provides a view of how the manholes change over time.