Dishwashing Water-Usage Data Capture
Budget / SalaryHourly project
TypeFreelance project
LocationRemote
Posted1 hour ago
I’m building a training set focused on one very specific household task: washing dishes. The goal is to capture reliable, real-world data that shows how much water is actually used during normal dish-washing sessions.
Here’s what I need from you: record several everyday dish-washing routines and log the exact water consumption for each session. A kitchen sink flow meter, a smart faucet reading, or any other accurate measuring tool you already have is fine—the key is that the final figures are precise and reproducible. Video or photo evidence of each session is helpful but optional; the water-usage numbers themselves are mandatory.
Deliverables
• A spreadsheet (CSV or XLSX) listing date, duration of the wash, total litres/gallons consumed, and brief contextual notes (e.g., hand-washing a family dinner load vs. quick rinse of a few mugs).
• Raw flow-meter or faucet log files—or clearly labeled photos of the meter reading before and after—to back up the numbers.
Acceptance criteria
• Minimum of 10 individual dish-washing sessions captured.
• Water-usage readings accurate to within ±2 %.
• Data and supporting media uploaded in an organised folder structure so it can be fed straight into my AI pipeline without extra cleaning.
That’s the full scope—straightforward but important work that will help me teach a model how to optimise household water consumption.
Here’s what I need from you: record several everyday dish-washing routines and log the exact water consumption for each session. A kitchen sink flow meter, a smart faucet reading, or any other accurate measuring tool you already have is fine—the key is that the final figures are precise and reproducible. Video or photo evidence of each session is helpful but optional; the water-usage numbers themselves are mandatory.
Deliverables
• A spreadsheet (CSV or XLSX) listing date, duration of the wash, total litres/gallons consumed, and brief contextual notes (e.g., hand-washing a family dinner load vs. quick rinse of a few mugs).
• Raw flow-meter or faucet log files—or clearly labeled photos of the meter reading before and after—to back up the numbers.
Acceptance criteria
• Minimum of 10 individual dish-washing sessions captured.
• Water-usage readings accurate to within ±2 %.
• Data and supporting media uploaded in an organised folder structure so it can be fed straight into my AI pipeline without extra cleaning.
That’s the full scope—straightforward but important work that will help me teach a model how to optimise household water consumption.
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