Smart Waste Collection Sensor Data
This dataset provides granular IoT sensor readings from smart city waste bins, including fill levels, environmental conditions, operational status, and precise geolocation. It enables urban planners and waste management teams to optimize collection routes, monitor infrastructure health, and advance sustainability initiatives through predictive analytics and real-time monitoring.
Sample rows
preview · 8 of 120 rows · all 18 columns| sensor_reading_idstring | bin_statusstring | battery_level_percentfloat | address_countrystring | bin_idstring | sensor_idstring | reading_timestampdatetime | fill_level_percentfloat | bin_temperature_celsiusfloat | bin_humidity_percentfloat | location_latitudefloat | location_longitudefloat | address_streetstring | address_citystring | address_statestring | address_postal_codestring | bin_typestring | last_maintenance_datedate |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SR-00001 | normal | 86.3 | USA | BIN-1001 | SEN-2001 | 2024-06-01T08:14:00Z | 13.24 | 18.7 | 38.4 | 40.7128 | -74.006 | 123 Broadway | New York | NY | 10007 | general | 2024-05-13 |
| SR-00002 | maintenance_required | 9.1 | UK | BIN-1002 | SEN-2002 | 2024-06-01T09:20:32Z | 92.11 | 42.1 | 88.3 | 51.5074 | -0.1278 | 221B Baker St | London | England | NW1 6XE | recycling | 2024-05-31 |
| SR-00003 | normal | 65.4 | France | BIN-1003 | SEN-2003 | 2024-06-01T10:02:10Z | 54.67 | 22.2 | 63.2 | 48.8566 | 2.3522 | 14 Rue de Rivoli | Paris | Île-de-France | 75004 | general | 2024-05-17 |
| SR-00004 | full | 12.5 | USA | BIN-1004 | SEN-2004 | 2024-06-01T11:45:22Z | 97.32 | 29.8 | 92.7 | 34.0522 | -118.2437 | 456 Main St | Los Angeles | CA | 90012 | hazardous | 2024-05-30 |
| SR-00005 | normal | 72.2 | Finland | BIN-1005 | SEN-2005 | 2024-06-01T12:03:49Z | 3.87 | -8.3 | 18.6 | 60.1699 | 24.9384 | 7 Mannerheimintie | Helsinki | Uusimaa | 00100 | compost | 2024-05-11 |
| SR-00006 | maintenance_required | 8.7 | Canada | BIN-1006 | SEN-2006 | 2024-06-01T13:37:08Z | 81.65 | 37.6 | 97.2 | 43.6532 | -79.3832 | 350 Queen St W | Toronto | ON | M5V 2A2 | hazardous | 2024-05-31 |
| SR-00007 | normal | 55.9 | Japan | BIN-1007 | SEN-2007 | 2024-06-02T07:22:01Z | 44.39 | 20.1 | 42.8 | 35.6895 | 139.6917 | 11 Shinjuku | Tokyo | Tokyo | 160-0022 | general | 2024-05-23 |
| SR-00008 | normal | 81.2 | Australia | BIN-1008 | SEN-2008 | 2024-06-02T08:13:43Z | 19.76 | 34.5 | 89.3 | -33.8688 | 151.2093 | 8 George St | Sydney | NSW | 2000 | compost | 2024-05-10 |
| SR-00009 | full | 2.4 | Russia | BIN-1009 | SEN-2009 | 2024-06-02T09:40:05Z | 96.83 | 62.1 | 100 | 55.7558 | 37.6173 | 1 Red Square | Moscow | Moscow | 101000 | hazardous | 2024-05-27 |
| SR-00010 | normal | 59.3 | India | BIN-1010 | SEN-2010 | 2024-06-02T10:32:36Z | 41.15 | 15.9 | 31.6 | 28.6139 | 77.209 | 5 Connaught Place | Delhi | Delhi | 110001 | general | 2024-05-18 |
| SR-00011 | maintenance_required | 6.5 | Sweden | BIN-1011 | SEN-2011 | 2024-06-02T11:19:17Z | 86.52 | 43.2 | 77.9 | 59.3293 | 18.0686 | 12 Drottninggatan | Stockholm | Stockholm | 111 51 | recycling | 2024-06-01 |
| SR-00012 | normal | 76.8 | Italy | BIN-1012 | SEN-2012 | 2024-06-02T12:50:01Z | 4.71 | blank | 52.6 | 41.9028 | 12.4964 | 15 Via del Corso | Rome | Lazio | 00187 | compost | 2024-05-09 |
| SR-00013 | maintenance_required | 7.9 | Mexico | BIN-1013 | SEN-2013 | 2024-06-02T14:07:22Z | 88.19 | 36.7 | 95.2 | 19.4326 | -99.1332 | 10 Calle Madero | Mexico City | CDMX | 06000 | recycling | 2024-06-01 |
| SR-00014 | full | 10.2 | Japan | BIN-1014 | SEN-2014 | 2024-06-03T07:30:54Z | 96.02 | 48.3 | 91.7 | 35.6762 | 139.6503 | 3 Akihabara | Tokyo | Tokyo | 101-0021 | hazardous | 2024-06-01 |
| SR-00015 | normal | 97.1 | Germany | BIN-1015 | SEN-2015 | 2024-06-03T08:46:16Z | 0.59 | 27.5 | 34.8 | 52.52 | 13.405 | 2 Unter den Linden | Berlin | Berlin | 10117 | general | 2024-05-15 |
| SR-00016 | maintenance_required | 2 | Canada | BIN-1016 | SEN-2016 | 2024-06-03T09:12:23Z | 84.3 | 39.8 | 99.1 | 45.5017 | -73.5673 | 1000 Rue Sainte-Catherine | Montreal | QC | H3B 1E9 | hazardous | 2024-06-02 |
| SR-00017 | normal | 61.8 | Brazil | BIN-1017 | SEN-2017 | 2024-06-03T10:25:48Z | 48.23 | 19.4 | 55.2 | -23.5505 | -46.6333 | 25 Avenida Paulista | São Paulo | SP | 01311-200 | general | 2024-05-14 |
| SR-00018 | normal | 73.5 | Iceland | BIN-1018 | SEN-2018 | 2024-06-03T11:36:11Z | 8.21 | -2.3 | 16.4 | 64.9631 | -19.0208 | 4 Laugavegur | Reykjavik | Capital Region | 101 | compost | 2024-05-12 |
| SR-00019 | full | 5.1 | USA | BIN-1019 | SEN-2019 | 2024-06-03T12:15:07Z | 97.9 | 57.9 | 99.9 | 37.7749 | -122.4194 | 1 Market St | San Francisco | CA | 94105 | hazardous | 2024-06-01 |
| SR-00020 | normal | 48.2 | Thailand | BIN-1020 | SEN-2020 | 2024-06-03T13:02:22Z | 58.74 | 22 | 60.3 | 13.7563 | 100.5018 | 99 Sukhumvit Rd | Bangkok | Bangkok | 10110 | general | 2024-05-16 |
What the 120 rows show
from the 120-row sampleNormal (bin status) stands out: mean battery_
- 50.1median battery_
level_ percent - 4bin types
- 55.2median fill_
level_ percent - 25.7median bin_
temperature_ celsius - 61.2median bin_
humidity_ percent
Median 50.1, from 0.0 to 97.9.
- string 10
- float 6
- date 1
- datetime 1
Columns
18 columns in three groups| column | type | description | example |
|---|---|---|---|
| Text 10 columns | |||
sensor_reading_id | string | Unique identifier for each sensor reading recordunique | SR-00001 |
bin_id | string | Unique identifier for each waste bin | BIN-1001 |
sensor_id | string | Unique identifier for the sensor device in the bin | SEN-2001 |
bin_status | string | Operational status of the bin (e.g., normal, full, maintenance_required, offline)normal · full · maintenance_required · offline | normal |
address_street | string | Street address where the waste bin is locatedoptional | 123 Broadway |
address_city | string | City where the waste bin is locatedoptional | New York |
address_state | string | State or region where the waste bin is locatedoptional | NY |
address_postal_code | string | Postal code of the waste bin's locationoptional | 10007 |
address_country | string | Country where the waste bin is locatedoptional | USA |
bin_type | string | Type of waste bin (e.g., general, recycling, compost, hazardous)general · recycling · compost · hazardous · optional | general |
| Numbers 6 columns | |||
fill_level_percent | float | Current fill level of the waste bin as a percentage (0-100)0 to 100 | 13.24 |
bin_temperature_celsius | float | Temperature inside the waste bin in degrees Celsiusoptional | 18.7 |
bin_humidity_percent | float | Humidity inside the waste bin as a percentage (0-100)0 to 100 · optional | 38.4 |
battery_level_percent | float | Remaining battery level of the sensor as a percentage (0-100)0 to 100 · optional | 86.3 |
location_latitude | float | Latitude coordinate of the waste bin's location-90 to 90 | 40.7128 |
location_longitude | float | Longitude coordinate of the waste bin's location-180 to 180 | -74.006 |
| Dates and times 2 columns | |||
reading_timestamp | datetime | Date and time when the sensor reading was recorded | 2024-06-01T08:14:00Z |
last_maintenance_date | date | Date when the bin was last maintained or servicedoptional | 2024-05-13 |
Use it for
A logistics dashboard
Battery_
level_ percent by bin_ status and a breakdown of address_ country. Excel, Power BI or Tableau. Why do the 69 normal rows have a mean battery_
level_ percent of 68.4? A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
- Sensor readings120SR-0000186.3normalSR-000029.1maintena…SR-0000365.4normal
A software demo
Believable sensor readings with bin_
id, sensor_ id and reading_ timestamp to fill a screen in front of a buyer.
blueprint · smart-waste-collection-sensor-data
Behind this dataset
Same schema. As many rows as you need.
These 120 rows came out of a blueprint — 18 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.
- Each row represents a unique waste bin's hourly sensor reading.
- Include fill level (%), temperature, and bin status (OK/Full/Needs Maintenance).
- Associate each sensor with a geolocation and neighborhood zone.
- Record waste type category (general, recycling, organic).
- Capture both scheduled and unscheduled collection events.
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-waste-collection-sensor-data