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In the cited AI leak-detection study, what input did the system analyze?

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  1. In the cited AI leak-detection study, what input did the system analyze?
    • Acoustic recordings of water-pipe leak sounds
    • Household water bills alone
    • Street photographs without sound or pressure data
    • Social-media posts about wet roads
  2. According to EPA, what can non-revenue water include?
    • Only water physically leaking from a pipe
    • Real losses, apparent losses, and authorized consumption that is not billed
    • Only treated water lost to evaporation
    • Only inaccurate customer bills
  3. What objective does the cited pump-scheduling study use?
    • Maximize chemical dosing regardless of water quality
    • Eliminate all storage tanks
    • Minimize pumping-energy cost subject to water-system operating constraints
    • Replace the network with a digital map
  4. In the cited treatment study, what did machine-learning models predict?
    • Ownership of distribution pipes
    • Satellite position over reservoirs
    • Customer bills from social-media posts
    • Chemical dosage from water-quality and streamflow inputs
  5. What can EPA’s EPANET software simulate in a distribution network?
    • Pipe flows, node pressures, tank levels and chemical concentrations
    • Only rainfall over agricultural fields
    • Only billing and payment activity
    • Only treatment-plant staffing schedules
  6. What does the cited satellite-data study predict for agricultural water-use support?
    • Household water-meter identity
    • Soil-moisture content using satellite imagery, ground truth and climate records
    • Location of every city pipe leak
    • Chlorine residual at each treatment plant
  7. Which inputs did the cited water-demand forecasting study use?
    • Only treatment-plant photographs
    • Only water chemistry from one hour
    • Demand history, calendar variables and external weather features
    • Audio from customer-service calls
  8. What agricultural goal does the satellite soil-moisture study say its predictions could support?
    • Choosing which customers pay higher tariffs
    • Finding chemical contaminants in pipes
    • Planning a Mars rover route
    • Improving water-use efficiency and reducing dependence on irrigation