INDUSTRY FIELD GUIDE
Dairy milking sensor records for AI event review
A blank reading can mean the sensor stopped reporting.
NAICS 112120 · Dairy Cattle and Milk Production
A blank reading can mean the sensor stopped reporting. It should never silently become a zero. USDA’s Economic Research Service has studied precision dairy and robotic milking in the United States. A farm can demonstrate an event-review dataset with mock time series and a verified record of what happened during the gap. USDA ERS precision dairy and robotic milking research
Invent two sessions with similar curves. Make one show a confirmed equipment dropout alongside a maintenance note. Give the other a low but confirmed sensor reading and a record that sends the case to staff. Include sample intervals, units, and anonymized session keys. Test whether a model distinguishes missing measurement from a measured value and correctly routes the unresolved case. Do not make animal health findings the model’s output.
Milk processor, equipment-platform, or third-party testing contracts may govern data access. Keep actual animal records, herd productivity, staff details, and commercial terms out of the first packet.
Describe a milking data sample
Original Fiund exercise
A sensor dropout and a confirmed low measurement need different states
Two invented session traces use arbitrary measurement units and no animal identity. They illustrate record interpretation without animal-health assessment or live equipment access.
| Record | Source | What it records |
|---|---|---|
| DS1 | Session A | At minutes 1, 2, 3: values 4, missing, 4 U. Maintenance note links the minute-2 gap to a confirmed reporting dropout. |
| DS2 | Session B | At minutes 1, 2, 3: values 4, 0.2, 4 U. Separate validation card confirms the 0.2-U reading; no dropout flag. |
| DS3 | Review rule | Missing values remain missing. Valid low measurements go to staff review with their source; the exercise supplies no health rule or outcome. |
Question for the model
How should minute 2 be represented in each session, and what may the assistant conclude about animal health?
Show the reference answer and checks
DS1's minute-2 value is missing with a documented sensor-reporting dropout, not a zero measurement. DS2's 0.2-U value is a confirmed low reading and should retain that number and its validation source. DS3 calls for staff review of the latter, but provides no basis for a health conclusion in either case. Similar curve shapes do not make the missing and measured states interchangeable.
- Filling a missing sensor interval with zero.
- Discarding a validated low measurement as a dropout or turning it into a health diagnosis.
Fields to preserve
- Session, sample interval and unit
- Defines the time series.
- Value and missingness flag
- Preserves the measurement state.
- Maintenance or validation source and referral
- Supports distinct review paths.
Test another case
Remove A's maintenance note. Require the value to stay missing while its cause becomes unknown, rather than retaining the prior dropout explanation.
Use invented traces. Exclude actual animal records, productivity, staff and commercial terms; processor and equipment-platform contracts may control real exports.
Discuss a contribution
Describe the sources you control, the task they could support and what has already been checked. Use the existing-data assessment for an archive or the collection brief for a new recording project. The contributor agreement defines Fiund’s licensing authority and compensation. A guide or fictional exercise does not establish an accepted collection or a sale.