Smart City IoT Device Logs
This dataset provides granular, real-time logs from smart city IoT devices deployed for traffic management, air quality monitoring, and energy grid operations. It includes device identifiers, location details, event types, operational metrics, and contextual readings, enabling comprehensive analysis for urban infrastructure optimization and predictive maintenance.
Sample rows
preview · 8 of 120 rows · all 20 columns| log_idstring | device_typestring | event_valuefloat | location_countrystring | device_idstring | location_latitudefloat | location_longitudefloat | location_street_addressstring | location_citystring | location_statestring | location_postal_codestring | timestampdatetime | statusstring | event_typestring | event_unitstring | battery_levelfloat | signal_strengthfloat | firmware_versionstring | operator_idstring | notesstring |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| A9X7PQ1L | traffic_sensor | 342 | USA | TS-1001 | 40.7128 | -74.006 | 400 Broadway | New York | NY | 10013 | 2024-06-03T08:21:17 | active | reading | vehicles/hour | 86.4 | -67.5 | v2.0.1 | op-nyc-01 | Peak traffic period |
| B7C4X2ZQ | air_quality_monitor | 67 | USA | AQ-2021 | 34.0522 | -118.2437 | 915 S Grand Ave | Los Angeles | CA | 90015 | 2024-06-03T08:31:18 | active | reading | AQI | 72.8 | -80.2 | v1.8.3 | op-la-02 | PM2.5 elevated |
| Q1J7K8V3 | energy_meter | 153.78 | UK | EN-3302 | 51.5074 | -0.1278 | 12 King Street | London | London | SW1A 1AA | 2024-06-03T08:45:05 | active | reading | kWh | blank | blank | v5.4.2 | op-lon-01 | Normal consumption |
| M3T6V9F0 | traffic_sensor | 251 | USA | TS-1002 | 40.7306 | -73.9352 | 210 5th Ave | New York | NY | 10010 | 2024-06-03T09:00:22 | active | reading | vehicles/hour | 93.7 | -73.4 | v2.0.1 | op-nyc-01 | Light drizzle |
| G8E2R7S6 | air_quality_monitor | 43 | USA | AQ-2022 | 37.7749 | -122.4194 | 101 Market St | San Francisco | CA | 94105 | 2024-06-03T09:15:34 | active | reading | AQI | 68.2 | -90.1 | v1.8.3 | op-sf-01 | Low pollution |
| Z4W6D8P2 | energy_meter | 98.33 | France | EN-3303 | 48.8566 | 2.3522 | 5 Rue de Rivoli | Paris | Île-de-France | 75001 | 2024-06-03T09:22:19 | active | reading | kWh | blank | blank | v5.4.2 | op-par-01 | Weekend usage |
| F2Z9Y6H1 | traffic_sensor | 421 | USA | TS-1003 | 41.8781 | -87.6298 | 233 S Wacker Dr | Chicago | IL | 60606 | 2024-06-03T09:35:11 | active | reading | vehicles/hour | 78.6 | -59.3 | v2.0.0 | op-chi-01 | Morning rush |
| H7S5J2B8 | air_quality_monitor | 58 | Germany | AQ-2023 | 52.52 | 13.405 | 89 Alexanderplatz | Berlin | Berlin | 10178 | 2024-06-03T09:44:54 | active | reading | AQI | 61.7 | -100.8 | v1.8.4 | op-ber-01 | Ozone spike |
| L5U8R4K0 | energy_meter | 245.6 | Japan | EN-3304 | 35.6895 | 139.6917 | 2 Chome-6-1 Marunouchi | Tokyo | Tokyo | 100-0005 | 2024-06-03T10:02:17 | active | reading | kWh | blank | blank | v5.4.3 | op-tok-01 | Above average |
| C3V8F2D1 | traffic_sensor | 195 | USA | TS-1004 | 29.7604 | -95.3698 | 1200 Smith St | Houston | TX | 77002 | 2024-06-03T10:13:09 | active | reading | vehicles/hour | 82.1 | -62.7 | v2.0.1 | op-hou-01 | Event nearby |
| K4A0Q7T2 | air_quality_monitor | 79 | Russia | AQ-2024 | 55.7558 | 37.6173 | 9 Red Square | Moscow | Moscow | 101000 | 2024-06-03T10:28:07 | active | reading | AQI | 53.9 | -110.6 | v1.8.2 | op-mos-01 | Industrial area |
| N9P3J2L5 | energy_meter | 190.14 | Spain | EN-3305 | 41.3851 | 2.1734 | 33 Passeig de Gracia | Barcelona | Catalonia | 08007 | 2024-06-03T10:32:51 | active | reading | kWh | blank | blank | v5.4.2 | op-bar-01 | Solar panel spike |
| T2S9E4M6 | traffic_sensor | 105 | USA | TS-1005 | 39.7392 | -104.9903 | 1700 Lincoln St | Denver | CO | 80203 | 2024-06-03T10:45:44 | active | reading | vehicles/hour | 60.5 | -95 | v2.0.2 | op-den-01 | Clear weather |
| P7O3V1N8 | air_quality_monitor | 62 | Italy | AQ-2025 | 41.9028 | 12.4964 | 21 Via del Corso | Rome | Lazio | 00186 | 2024-06-03T10:57:19 | active | reading | AQI | 80.1 | -75.6 | v1.8.4 | op-rom-01 | Tourist season |
| S6F2C8Z3 | energy_meter | 167.42 | Japan | EN-3306 | 35.6762 | 139.6503 | 11 Shibuya | Tokyo | Tokyo | 150-0002 | 2024-06-03T11:11:37 | active | reading | kWh | blank | blank | v5.4.3 | op-tok-01 | Office complex |
| X1G7N6Q4 | traffic_sensor | 89 | USA | TS-1006 | 33.4484 | -112.074 | 340 N 3rd St | Phoenix | AZ | 85004 | 2024-06-03T11:18:12 | active | reading | vehicles/hour | 54.2 | -108.9 | v2.0.1 | op-phx-01 | Road work nearby |
| R8V1P3S7 | air_quality_monitor | 148 | India | AQ-2026 | 28.7041 | 77.1025 | 55 Connaught Place | Delhi | Delhi | 110001 | 2024-06-03T11:28:30 | active | reading | AQI | 39.8 | -119.2 | v1.7.9 | op-del-01 | Air pollution alert |
| U2K4D6M9 | energy_meter | 157.88 | Spain | EN-3307 | 40.4168 | -3.7038 | 8 Gran Via | Madrid | Madrid | 28013 | 2024-06-03T11:36:02 | active | reading | kWh | blank | blank | v5.4.1 | op-mad-01 | Holiday usage |
| E9N3W5L1 | traffic_sensor | 172 | USA | TS-1007 | 32.7767 | -96.797 | 300 Reunion Blvd | Dallas | TX | 75207 | 2024-06-03T11:45:39 | active | reading | vehicles/hour | 62.7 | -70.1 | v2.0.0 | op-dal-01 | School zone |
| W2J8Q4C7 | air_quality_monitor | 65 | Italy | AQ-2027 | 45.4642 | 9.19 | 14 Via Dante | Milan | Lombardy | 20121 | 2024-06-03T11:52:16 | active | reading | AQI | 87.2 | -55.3 | v1.8.3 | op-mil-01 | Low NO2 |
What the 120 rows show
from the 120-row sampleEnergy_
- 157.9median event_
value - 3event units
- 4event types
- 5statuses
- 68.2median battery_
level - -76.2median signal_
strength
Median 157.9, from 32.0 to 2,491.
- string 14
- float 5
- datetime 1
Columns
20 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 14 columns | |||
log_id | string | Unique identifier for each log entryunique | A9X7PQ1L |
device_id | string | Unique identifier for the IoT device generating the log | TS-1001 |
device_type | string | Type of IoT device (e.g., traffic_sensor, air_quality_monitor, energy_meter)traffic_sensor · air_quality_monitor · energy_meter | traffic_sensor |
location_street_address | string | Street address of the device's locationoptional | 400 Broadway |
location_city | string | City where the device is locatedoptional | New York |
location_state | string | State or region where the device is locatedoptional | NY |
location_postal_code | string | Postal code of the device's locationoptional | 10013 |
location_country | string | Country where the device is locatedoptional | USA |
status | string | Operational status of the device at the time of log (e.g., active, inactive, error)active · inactive · error · maintenance | active |
event_type | string | Type of event recorded (e.g., reading, alert, error, maintenance)reading · alert · error · maintenance | reading |
event_unit | string | Unit of measurement for event_value (e.g., vehicles/hour, AQI, kWh)3 units · optional | vehicles/hour |
firmware_version | string | Version of the device's firmwareoptional | v2.0.1 |
operator_id | string | Identifier for the operator or system managing the deviceoptional | op-nyc-01 |
notes | string | Additional notes or comments related to the log entryoptional | Peak traffic period |
| Numbers 5 columns | |||
location_latitude | float | Latitude coordinate of the device's location-90 to 90 | 40.7128 |
location_longitude | float | Longitude coordinate of the device's location-180 to 180 | -74.006 |
event_value | float | Numeric value associated with the event (e.g., traffic count, air quality index, energy consumption)optional | 342 |
battery_level | float | Current battery level of the device (percentage 0-100)0 to 100 · optional | 86.4 |
signal_strength | float | Signal strength of the device's network connection (dBm)-120 to 0 · optional | -67.5 |
| Dates and times 1 column | |||
timestamp | datetime | Date and time when the log was recorded | 2024-06-03T08:21:17 |
Use it for
An energy dashboard
Event_
value by device_ type and a breakdown of location_ country. Excel, Power BI or Tableau. Why do the 36 energy_
meter rows have a mean event_ value of 1,081? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Logs120A9X7PQ1L342traffic_…B7C4X2ZQ67air_qual…Q1J7K8V3153.78energy_m…
A software demo
Believable logs with device_
id, device_ type and location_ latitude to fill a screen in front of a buyer.
This dataset120 rows20 columns
Yours1,000 rows20 columnslocation_latitude: UK only
blueprint · smart-city-iot-device-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 unique device log event.
- Include device type, location ID, event timestamp, and status code.
- Flag critical events (e.g., malfunction, threshold breach).
- Aggregate usage metrics per device daily.
- Anonymize device IDs to maintain privacy.
- Log network connectivity status for reliability monitoring.
Open the blueprint in Data Factory
1 credit per row. Preview 20 rows free. Buy rows for the full run.
- Exports
- CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
- Licence
- yours to use, including commercially
- API slug
- smart-city-iot-device-logs