Engineer urges quick pilot using 311 and solid‑waste data to fix service gaps
A machine‑learning engineer who analyzed more than 46,000 service requests told council the city can use existing data to give 311 staff timely answers and improve trash collection responsiveness; councilmembers invited a working session.
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John Isbekov, who identified himself as a senior machine‑learning engineer in Houston, presented an analysis of more than 46,000 public solid‑waste service requests filed in 2026 and highlighted opportunities to make 311 data actionable in real time.
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