Real-Time Cold Chain Sensor Logs

This dataset provides granular, real-time IoT sensor logs for refrigerated supply chain shipments, including environmental readings, shipment details, location, and compliance status. It enables logistics managers to monitor temperature and humidity integrity, respond to alerts, and ensure regulatory compliance for food and pharmaceutical products. The comprehensive schema supports operational optimization, risk mitigation, and detailed reporting.

  • opened 5 times
  • last updated 1 Dec 2025
  • by GoMask
The brief that made it

Real-time monitoring of refrigerated shipments for temperature and humidity integrity

Sample rows

preview · 8 of 120 rows · all 20 columns
log_idstringalert_typestringhumidity_percentfloatalert_flagbooleansensor_idstringtimestampdatetimeshipment_idstringproduct_typestringtemperature_celsiusfloatlocation_latitudefloatlocation_longitudefloatlocation_citystringlocation_statestringlocation_countrystringalert_thresholdfloatbattery_level_percentfloatshipment_start_datedateshipment_expected_delivery_datedatecarrier_namestringcompliance_statusstring
ABC123-001none54.2falseSENS-000012024-05-01T08:15:26ZSHIP-0001food5.634.0522-118.2437Los AngelesCAUSAblank98.32024-04-282024-05-03FedExcompliant
XYZ789-002none41.5falseSENS-000022024-05-01T09:30:12ZSHIP-0002pharmaceutical3.240.7128-74.006New YorkNYUSAblank87.52024-04-302024-05-05UPScompliant
LMN456-003noneblankfalseSENS-000032024-05-01T10:20:45ZSHIP-0003other29.851.5074-0.1278LondonEnglandUKblank73.22024-04-292024-05-06RoyalMailcompliant
DEF321-004none60.7falseSENS-000042024-05-01T11:45:15ZSHIP-0004food8.148.85662.3522ParisÎle-de-FranceFranceblank90.12024-04-272024-05-02LaPostecompliant
JKL654-005temperature_high65.3trueSENS-000012024-05-01T13:05:54ZSHIP-0001food13.734.0522-118.2437Los AngelesCAUSA1096.42024-04-282024-05-03FedExnon-compliant
QRS987-006temperature_high13.9trueSENS-000052024-05-01T14:15:36ZSHIP-0005pharmaceutical42.155.755837.6173MoscowMoscowRussia4039.82024-04-302024-05-07RussianPostnon-compliant
TUV321-007none14.7falseSENS-000062024-05-01T15:00:00ZSHIP-0006other035.6895139.6917TokyoTokyoJapanblank80.42024-04-292024-05-05JapanPostcompliant
MNO987-008none52.1falseSENS-000072024-05-01T16:45:23ZSHIP-0007food2.945.4215-75.6998OttawaONCanadablank88.72024-04-262024-05-03Purolatorcompliant

What the 120 rows show

from the 120-row sample

Temperature_high (alert type) stands out: 25 of its 25 rows have alert_flag = true, against 16 of 95 for the rest.

  • 34%alert_flag = true
  • 49.2median humidity_percent
  • 2compliance statuses
  • 3product types
  • 18carrier names
  • 19location countries
Alert flag rate by alert_typealert_flag = true
0%50%100%100%temperat…25 of 25100%temperat…7 of 7100%humidity…9 of 90%none0 of 79

Temperature_high (alert type)'s mean humidity_percent is 73.5, against 12.2 for temperature_low, 91.3 for humidity_high and 43.3 for none.

humidity_percent110 rows, in bands of 10
010204127132018154116050100humidity_percent →

Median 49.2, from 0.0 to 100.0.

sensor_id120 rows · top 10 of 36 values
  1. SENS-385219
  2. SENS-650137
  3. SENS-439517
  4. SENS-239646
  5. SENS-540216
  6. SENS-263846
  7. SENS-148936
  8. SENS-000013
  9. SENS-000033
  10. SENS-000043
20 columns by typefrom the column list below
  • string 10
  • float 6
  • date 2
  • datetime 1
  • boolean 1

Columns

20 columns in four groups
blueprint · 20 columns
columntypedescriptionexample
Text 10 columns
log_idstringUnique identifier for each sensor log entryuniqueABC123-001
sensor_idstringUnique identifier for the IoT sensor deviceSENS-00001
shipment_idstringUnique identifier for the shipment associated with the sensor readingSHIP-0001
product_typestringType of product being shipped (e.g., food, pharmaceutical)food · pharmaceutical · otherfood
location_citystringCity where the sensor reading was takenoptionalLos Angeles
location_statestringState or region where the sensor reading was takenoptionalCA
location_countrystringCountry where the sensor reading was takenoptionalUSA
alert_typestringType of alert triggered (e.g., temperature_high, temperature_low, humidity_high, humidity_low)5 values · optionalnone
carrier_namestringName of the logistics carrier responsible for the shipmentoptionalFedEx
compliance_statusstringStatus indicating if the shipment is in compliance with temperature/humidity regulationscompliant · non-compliant · pending · optionalcompliant
Numbers 6 columns
temperature_celsiusfloatMeasured temperature in degrees Celsius-50 to 505.6
humidity_percentfloatMeasured relative humidity as a percentage0 to 100 · optional54.2
location_latitudefloatLatitude coordinate of the sensor at the time of reading-90 to 90 · optional34.0522
location_longitudefloatLongitude coordinate of the sensor at the time of reading-180 to 180 · optional-118.2437
alert_thresholdfloatThreshold value that triggered the alert, if anyoptional10
battery_level_percentfloatSensor battery level as a percentage at the time of reading0 to 100 · optional98.3
Dates and times 3 columns
timestampdatetimeDate and time when the sensor reading was recorded (UTC)2024-05-01T08:15:26Z
shipment_start_datedateDate the shipment beganoptional2024-04-28
shipment_expected_delivery_datedateExpected delivery date for the shipmentoptional2024-05-03
True or false 1 column
alert_flagbooleanIndicates if the reading triggered a temperature or humidity alertfalse

Use it for

  • alert flag34%41 of 120 rowsmean humidity percent…73.5temp…12.2temp…91.3humi…43.3none

    A logistics dashboard

    The alert_flag rate, humidity_percent by alert_type and a breakdown of sensor_id. Excel, Power BI or Tableau.

  • Why do 41 of 120 rows have alert_flag = true?

    A root-cause class exercise

    Hand out the rows and one question. The answer is in the data, not in the brief.

  • A software demo

    Believable logs with timestamp, sensor_id and shipment_id to fill a screen in front of a buyer.

Not quite right?

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Preview 20 rows free

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This dataset120 rows20 columns
Yours1,000 rows20 columnslocation_latitude: UK only

blueprint · real-time-cold-chain-sensor-logs

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 20 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with
  • Each row represents a sensor snapshot from a shipment at a timestamp.
  • Temperatures must remain within predefined safe ranges depending on cargo type.
  • Automatic alerts triggered if temperature deviates for more than 10 minutes.
  • Sensor readings include geolocation and status (normal, warning, critical).
  • Shipments flagged for inspection if three or more warnings occur in transit.
Rows
Open the blueprint in Data Factory

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Exports
CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence
yours to use, including commercially
API slug
real-time-cold-chain-sensor-logs

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