Collection systems have invested millions of dollars over the past decade to digitize geographic assets, work order processes, and condition assessment analyses. You have invested in GIS, CMMS and CCTV – what’s the starting point for maximizing the return on those investments? While machine learning and Artificial Intelligence get the hype and headlines, as much as 80% of any data science opportunity falls within the scope of the “data wrangling.”
The game show "Let's Make a Deal" debuted in 1963 and was hosted for 30 years by Monty Hall. The game show was known for the crazy costumes the contestants wore and is famous in the statistics world for the "Big Deal" segment. In the Big Deal segment of the show, contestants are shown 3 numbered doors and are told about the fabulous/expensive prize behind 1 of the three doors. One of the other doors has an ok prize, and the third door typically would have a lousy prize, like a goat (the farm animal kind, not the Tom Brady kind).
Gathering condition data during the cleaning process engages your crew and provides data on roots, FOG and debris that can drive operational efficiencies. Data provides a foundation for analytics that can optimize the gravity main cleaning frequencies designed to minimize SSO risk from these issues.
Can we ever “Terminate” all SSOs at the source? Will machines and their “learning” ever be so smart that we have just-in-time maintenance preventing backups on sewer mains just BEFORE the SSO would occur? Can machine learning use detailed genetic profiles to perfectly diagnose cancer treatment, reducing cancer fatalities to zero?
A few years ago, Keanu Reeves was spotted in Alameda, CA eating some ice cream. Why was he here? What kind of ice cream was it? What was he wearing? Why did the internet (or at least the internet around me) care so much?? And why do women think he’s so good looking?? I was confused. Ultimately it appears he was here because another version of “The Matrix” was in the works. Was this just my “confusion matrix?”
