IoTSyn Generated
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Synthetic Smart City IoT Dataset — High-Pollution Day, 1K Rows
Smart City & Urban Sensing
Smart City
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1,000 rows · 64 columns
IoTSyn v4.4.0
License
Abstract
"Free CC0 synthetic dataset: 1,000 rows of UTCI thermal comfort, PM2.5 and NO2 air quality, occupancy and LAeq noise. High-Pollution Day."
Description
Overview
Synthetic urban public-space IoT time series generated by the IoTSyn v4.4.0 reference engine (Smart City & Public Spaces Edition). A coupled physical–stochastic model produces meteorology (solar geometry, cloud/precipitation Markov chains, AR(1) air temperature with a nocturnal urban-heat-island term, and a Weibull wind field induced through a Gaussian copula), human presence (a state-modulated non-homogeneous Poisson arrival process with LogNormal dwell times and infinite-server occupancy), road traffic, species-resolved air quality from a well-mixed mass-balance box model (PM2.5 and NO2, with separate physical and sensor columns), environmental noise composed in the energy domain (LAeq), and UTCI thermal comfort. A three-way separation between physical truth, sensor observation, and decision output is preserved throughout, and a multi-hazard decision layer emits an ordinal urban risk vector (thermal, air quality, noise, crowding), operational action levels, risk episodes, and provenance-tagged behaviour-change strategy objects. All randomness derives from named substreams of a portable MT19937 generator; identical configuration and seed reproduce byte-identical output. Each dataset ships with machine-readable sidecars: normalized scenario, domain validation report, risk episodes, and the strategy file.
1,000 data points, 64 columns. Config: IoTSyn v4.4.0 engine; master_seed: 123456; Capacity: 500; Controls: preset=high_pollution; EXTENDED (non-normative).
Column Schema
| Column | Description |
|---|---|
timestamp | string_iso8601 — interval start, explicit UTC offset |
step_duration_seconds | integer, s |
day_type | enum {weekday | weekend | holiday} |
cloud_state | enum {clear | partly_cloudy | overcast} |
cloud_fraction | float, dimensionless — range 0..1 |
precipitation_mm_h | float, mm/h — >=0; exactly 0 when dry |
air_temperature_c | float, degC |
vapour_pressure_pa | float, Pa |
relative_humidity_pct | float, % — 0..100 after roundoff clamp |
wind_speed_10m_m_s | float, m/s |
wind_speed_pedestrian_m_s | float, m/s |
mean_radiant_temperature_c | float, degC |
crowd_state | enum {quiet | normal | busy | event} |
crowd_state_mechanism | enum {stochastic | forced} |
offered_arrivals_count | integer, persons |
admitted_arrivals_count | integer, persons |
rejected_arrivals_count | integer, persons |
deferred_arrivals_count | integer, persons |
deferred_timeout_count | integer, persons |
queue_length_persons | integer, persons — 0 unless capacity_mode=defer_fifo |
occupancy_persons | integer, persons |
operational_capacity_ratio | float, dimensionless |
audience_general_public_persons | integer, persons |
audience_families_persons | integer, persons |
audience_elderly_persons | integer, persons |
audience_students_persons | integer, persons |
audience_commuters_persons | integer, persons |
audience_event_attendees_persons | integer, persons |
dominant_audience | enum, nullable {general_public | families | elderly | students | commuters | event_attendees} |
traffic_flow_vehicles_h | float, vehicles/h |
pm25_emission_ug_s | float, ug/s |
pm25_background_ug_m3 | float, ug/m3 |
pm25_physical_ug_m3 | float, ug/m3 |
pm25_sensor_raw_ug_m3 | float, ug/m3 |
pm25_sensor_calibrated_ug_m3 | float, ug/m3, nullable |
pm25_rolling_24h_ug_m3 | float, ug/m3, nullable — null until complete window |
pm25_rolling_complete | boolean |
no2_emission_ug_s | float, ug/s |
no2_background_ug_m3 | float, ug/m3 |
no2_physical_ug_m3 | float, ug/m3 |
no2_sensor_raw_ug_m3 | float, ug/m3 |
no2_sensor_calibrated_ug_m3 | float, ug/m3, nullable |
no2_rolling_24h_ug_m3 | float, ug/m3, nullable — null until complete window |
no2_rolling_complete | boolean |
LAeq_15min_dBA | float, dB(A), nullable — column name embeds the declared window; null until complete window unless warm-up supplies history |
noise_window_complete | boolean |
utci_c | float, degC |
utci_stress_category | enum {extreme cold stress | very strong cold stress | strong cold stress | moderate cold stress | slight cold stress | no thermal stress | moderate heat stress | strong heat stress | very strong heat stress | extreme heat stress} |
utci_input_clamped | boolean |
wbgt_outdoor_c | float, degC, nullable |
thermal_risk_level | enum, nullable {low | caution | high_risk | severe} |
air_quality_risk_level | enum, nullable {low | caution | high_risk | severe} |
noise_risk_level | enum, nullable {low | caution | high_risk | severe} |
crowding_risk_level | enum, nullable {low | caution | high_risk | severe} |
overall_action_level | enum, nullable {low | caution | high_risk | severe} |
dominant_issue | enum, nullable {thermal | air_quality | noise | crowding} |
co_dominant_issues | json_array_of_enum {thermal | air_quality | noise | crowding} |
elevated_issues | json_array_of_enum {thermal | air_quality | noise | crowding} |
elevated_hazard_count | integer |
compound_risk_flag | boolean |
risk_completeness_fraction | float, dimensionless |
overall_action_level_provisional | boolean |
risk_communication_template_id | string |
risk_communication_message | string |
Mathematical Models
- Meteorology:
AR(1) air temperature + sinusoidal diurnal cycle + nocturnal urban-heat-island (Oke); Magnus–WMO saturation vapour pressure; Weibull 10 m wind via an AR(1) Gaussian copula (Sklar), pedestrian wind through a log profile - Thermal comfort:
UTCI operational polynomial (Bröde et al. 2012) from air temperature, mean radiant temperature, 10 m wind and vapour pressure; clamp-and-flag domain policy; 10 scientific categories plus a coarser 4-level operational band - Air quality:
Single well-mixed box mass balance with ventilation exchange, deposition and chemical first-order loss and a traffic-driven source; exact exponential one-step update; mean-preserving log-normal sensor observation model; 24 h rolling means - Presence:
Discrete-time Markov-modulated NHPP arrivals with thermal/rain/wind deterrence; exact per-interval Poisson counts with sorted uniform offsets; LogNormal dwell; infinite-server occupancy reconstructed from events; largest-remainder audience allocation - Noise:
A-weighted equivalent continuous level (LAeq) over a declared window, summed in the energy (intensity) domain per ISO 1996 - Risk & strategy:
Conservative-max hazard vector with compound-risk indicators; compound priority score H·log10(1 + person-minutes / E_ref); ex-post, provenance-tagged behaviour-change strategies
Use Cases
- Thermal-comfort (UTCI) and heat-risk analytics
- Air-quality (PM2.5 / NO2) exposure and sensor calibration / drift research
- Occupancy and arrivals (NHPP) estimation benchmarks with exact ground truth
- Environmental-noise (LAeq) exposure analysis
- Multi-hazard urban risk aggregation and decision-support research
Reproducibility
Seed: 123456. Same seed + parameters = identical output. IoTSyn v3.1.
Machine-readable Sidecars
- Normalized scenario + controls (reproducibility): scenario.json
- Domain validation report (recomputed invariants & coverage): validation.json
- Elevated-risk episodes: episodes.json
- Behaviour-change strategy file (priority-ranked, provenance-tagged): strategy.json
Sample Data (18 rows · 64 columns)
| # | timestamp | step_duration_seconds | day_type | cloud_state | cloud_fraction | precipitation_mm_h | air_temperature_c | vapour_pressure_pa | relative_humidity_pct | wind_speed_10m_m_s | wind_speed_pedestrian_m_s | mean_radiant_temperature_c | crowd_state | crowd_state_mechanism | offered_arrivals_count | admitted_arrivals_count | rejected_arrivals_count | deferred_arrivals_count | deferred_timeout_count | queue_length_persons | occupancy_persons | operational_capacity_ratio | audience_general_public_persons | audience_families_persons | audience_elderly_persons | audience_students_persons | audience_commuters_persons | audience_event_attendees_persons | dominant_audience | traffic_flow_vehicles_h | pm25_emission_ug_s | pm25_background_ug_m3 | pm25_physical_ug_m3 | pm25_sensor_raw_ug_m3 | pm25_sensor_calibrated_ug_m3 | pm25_rolling_24h_ug_m3 | pm25_rolling_complete | no2_emission_ug_s | no2_background_ug_m3 | no2_physical_ug_m3 | no2_sensor_raw_ug_m3 | no2_sensor_calibrated_ug_m3 | no2_rolling_24h_ug_m3 | no2_rolling_complete | LAeq_15min_dBA | noise_window_complete | utci_c | utci_stress_category | utci_input_clamped | wbgt_outdoor_c | thermal_risk_level | air_quality_risk_level | noise_risk_level | crowding_risk_level | overall_action_level | dominant_issue | co_dominant_issues | elevated_issues | elevated_hazard_count | compound_risk_flag | risk_completeness_fraction | overall_action_level_provisional | risk_communication_template_id | risk_communication_message |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2026-07-14T00:00:00+01:00 | 900 | weekday | clear | 0.10 | 0 | 26.31 | 1,914.09 | 56.04 | 3.01 | 1.10 | 23.63 | normal | stochastic | 10 | 10 | 0 | 0 | 0 | 0 | 34 | 0.07 | 13 | 9 | 7 | 3 | 0 | 2 | general_public | 424.97 | 377.75 | 48 | 47.83 | 47.93 | 48.33 | true | 708.28 | 80 | 79.73 | 81.36 | 80.29 | true | 58.73 | true | 23.63 | no thermal stress | false | low | high_risk | caution | low | high_risk | air_quality | ["air_quality"] | ["air_quality"] | 1 | false | 1 | false | action_high_risk | Overall action level high_risk; dominant issue air_quality. | |||
| 2 | 2026-07-14T00:15:00+01:00 | 900 | weekday | clear | 0.19 | 0 | 26.85 | 1,915.23 | 54.34 | 1.64 | 0.60 | 24.41 | normal | stochastic | 8 | 8 | 0 | 0 | 0 | 0 | 24 | 0.05 | 10 | 5 | 4 | 4 | 0 | 1 | general_public | 351.04 | 312.04 | 48 | 47.67 | 47.01 | 48.22 | true | 585.07 | 80 | 79.48 | 71.06 | 80.23 | true | 56.97 | true | 25.78 | no thermal stress | false | low | high_risk | caution | low | high_risk | air_quality | ["air_quality"] | ["air_quality"] | 1 | false | 1 | false | action_high_risk | Overall action level high_risk; dominant issue air_quality. | |||
| 3 | 2026-07-14T00:30:00+01:00 | 900 | weekday | clear | 0.26 | 0 | 26.42 | 1,941.31 | 56.49 | 2.85 | 1.04 | 24.20 | quiet | stochastic | 6 | 6 | 0 | 0 | 0 | 0 | 19 | 0.04 | 8 | 3 | 2 | 5 | 0 | 1 | general_public | 350.59 | 311.64 | 48 | 47.80 | 51.35 | 48.26 | true | 584.32 | 80 | 79.68 | 85.08 | 80.31 | true | 57.80 | true | 24.11 | no thermal stress | false | low | high_risk | caution | low | high_risk | air_quality | ["air_quality"] | ["air_quality"] | 1 | false | 1 | false | action_high_risk | Overall action level high_risk; dominant issue air_quality. | |||
| 4 | 2026-07-14T00:45:00+01:00 | 900 | weekday | clear | 0.15 | 0 | 26.03 | 1,823.31 | 54.27 | 4.79 | 1.76 | 23.48 | quiet | stochastic | 8 | 8 | 0 | 0 | 0 | 0 | 18 | 0.04 | 6 | 3 | 2 | 6 | 0 | 1 | 235.48 | 209.31 | 48 | 47.85 | 54.20 | 48.28 | true | 392.46 | 80 | 79.76 | 81.00 | 80.27 | true | 57.31 | true | 21.26 | no thermal stress | false | low | high_risk | caution | low | high_risk | air_quality | ["air_quality"] | ["air_quality"] | 1 | false | 1 | false | action_high_risk | Overall action level high_risk; dominant issue air_quality. | ||||
| 5 | 2026-07-14T01:00:00+01:00 | 900 | weekday | clear | 0.16 | 0 | 25.43 | 1,817.59 | 56.05 | 2.93 | 1.07 | 22.92 | quiet | stochastic | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 0.02 | 5 | 1 | 2 | 3 | 0 | 0 | general_public | 188.30 | 167.38 | 48 | 47.76 | 39.15 | 48.17 | true | 313.83 | 80 | 79.60 | 82.37 | 80.24 | true | 56.46 | true | 22.64 | no thermal stress | false | low | high_risk | caution | low | high_risk | air_quality | ["air_quality"] | ["air_quality"] | 1 | false | 1 | false | action_high_risk | Overall action level high_risk; dominant issue air_quality. | |||
| 6 | 2026-07-14T01:15:00+01:00 | 900 | weekday | clear | 0.42 | 0 | 25.32 | 1,714.01 | 53.21 | 1.20 | 0.44 | 23.58 | busy | stochastic | 20 | 20 | 0 | 0 | 0 | 0 | 27 | 0.05 | 11 | 2 | 7 | 3 | 1 | 3 | general_public | 181.61 | 161.43 | 48 | 47.48 | 51.98 | 48.21 | true | 302.68 | 80 | 79.15 | 81.43 | 80.27 | true | 58.19 | true | 24.51 | no thermal stress | false | low | high_risk | caution | low | high_risk | air_quality | ["air_quality"] | ["air_quality"] | 1 | false | 1 | false | action_high_risk | Overall action level high_risk; dominant issue air_quality. | |||
| 7 | 2026-07-14T01:30:00+01:00 | 900 | weekday | clear | 0.24 | 0 | 25.02 | 1,695.19 | 53.59 | 1.42 | 0.52 | 22.74 | busy | stochastic | 18 | 18 | 0 | 0 | 0 | 0 | 36 | 0.07 | 10 | 8 | 7 | 2 | 4 | 5 | general_public | 172.01 | 152.90 | 48 | 47.54 | 51.28 | 48.24 | true | 286.69 | 80 | 79.25 | 78.09 | 80.15 | true | 57.83 | true | 23.84 | no thermal stress | false | low | high_risk | caution | low | high_risk | air_quality | ["air_quality"] | ["air_quality"] | 1 | false | 1 | false | action_high_risk | Overall action level high_risk; dominant issue air_quality. | |||
| 8 | 2026-07-14T01:45:00+01:00 | 900 | weekday | clear | 0.14 | 0 | 24.89 | 1,595.86 | 50.84 | 0.69 | 0.25 | 22.30 | busy | stochastic | 19 | 19 | 0 | 0 | 0 | 0 | 44 | 0.09 | 16 | 7 | 9 | 3 | 4 | 5 | general_public | 172.17 | 153.04 | 48 | 47.20 | 44.29 | 48.20 | true | 286.94 | 80 | 78.70 | 93.43 | 80.35 | true | 58.40 | true | 23.95 | no thermal stress | false | low | high_risk | caution | low | high_risk | air_quality | ["air_quality"] | ["air_quality"] | 1 | false | 1 | false | action_high_risk | Overall action level high_risk; dominant issue air_quality. | |||
| 9 | 2026-07-14T02:00:00+01:00 | 900 | weekday | clear | 0.17 | 0 | 24.36 | 1,614.54 | 53.07 | 0.59 | 0.22 | 21.87 | normal | stochastic | 3 | 3 | 0 | 0 | 0 | 0 | 28 | 0.06 | 11 | 5 | 5 | 3 | 3 | 1 | general_public | 183.79 | 163.37 | 48 | 47.13 | 47.68 | 48.23 | true | 306.31 | 80 | 78.58 | 88.28 | 80.52 | true | 57.90 | true | 23.60 | no thermal stress | false | low | high_risk | caution | low | high_risk | air_quality | ["air_quality"] | ["air_quality"] | 1 | false | 1 | false | action_high_risk | Overall action level high_risk; dominant issue air_quality. | |||
| 10 | 2026-07-14T02:15:00+01:00 | 900 | weekday | clear | 0.28 | 0 | 24.09 | 1,581.64 | 52.84 | 1.26 | 0.46 | 21.93 | normal | stochastic | 14 | 14 | 0 | 0 | 0 | 0 | 31 | 0.06 | 9 | 5 | 6 | 5 | 3 | 3 | general_public | 212.12 | 188.55 | 48 | 47.51 | 43.65 | 48.23 | true | 353.54 | 80 | 79.21 | 67.35 | 80.51 | true | 60.18 | true | 22.93 | no thermal stress | false | low | high_risk | caution | low | high_risk | air_quality | ["air_quality"] | ["air_quality"] | 1 | false | 1 | false | action_high_risk | Overall action level high_risk; dominant issue air_quality. |
Showing first 10 of 18 sample rows
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Machine-Readable Artifacts JSON
This dataset ships companion files alongside the CSV. Together they make the run independently reproducible and auditable without re-running the generator.
Scenario + controls
Normalized scenario configuration and control parameters — everything needed to reproduce the run
scenario.json
Validation report
Recomputed invariants, coverage checks and Kolmogorov–Smirnov results for this dataset
validation.json
Risk episodes
Table of elevated-risk episodes detected across the simulated period
episodes.json
Strategy file
Priority-ranked, provenance-tagged behaviour-change strategy objects
strategy.json
Cite This Dataset
IoTSyn Generated (2026). Synthetic Smart City IoT Dataset — High-Pollution Day, 1K Rows. [Dataset]. IoTSyn Generated. https://iotsyn.com/view.php?uid=iotsyn_6a556119d22a86.55670331
Source: IoTSyn Generated (2026)
Indexed by IoTDataset.com on Jul 28, 2026
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Related Topics & Keywords
#smart city
#public spaces
#urban sensing
#utci
#thermal comfort
#air quality
#pm2.5
#no2
#occupancy
#laeq
#noise
#nhpp
#box model
#multi-hazard
#reproducible
#v4.4.0
#synthetic data
#physics-based
#cc0
#iotsyn
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