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Synthetic Smart City IoT Dataset — Source-Dominated Air Quality, 672 Rows

Smart City & Urban Sensing Smart City
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5 min read
672 rows · 64 columns
IoTSyn v4.4.0
License

Abstract

"Free CC0 synthetic dataset: 672 rows of UTCI thermal comfort, PM2.5 and NO2 air quality, occupancy and LAeq noise. Source-Dominated Air Quality."

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.

672 data points, 64 columns. Config: IoTSyn v4.4.0 engine; master_seed: 88; Capacity: 500; Controls: preset=source_dominated_air_quality; EXTENDED (non-normative).

Column Schema

ColumnDescription
timestampstring_iso8601 — interval start, explicit UTC offset
step_duration_secondsinteger, s
day_typeenum {weekday | weekend | holiday}
cloud_stateenum {clear | partly_cloudy | overcast}
cloud_fractionfloat, dimensionless — range 0..1
precipitation_mm_hfloat, mm/h — >=0; exactly 0 when dry
air_temperature_cfloat, degC
vapour_pressure_pafloat, Pa
relative_humidity_pctfloat, % — 0..100 after roundoff clamp
wind_speed_10m_m_sfloat, m/s
wind_speed_pedestrian_m_sfloat, m/s
mean_radiant_temperature_cfloat, degC
crowd_stateenum {quiet | normal | busy | event}
crowd_state_mechanismenum {stochastic | forced}
offered_arrivals_countinteger, persons
admitted_arrivals_countinteger, persons
rejected_arrivals_countinteger, persons
deferred_arrivals_countinteger, persons
deferred_timeout_countinteger, persons
queue_length_personsinteger, persons — 0 unless capacity_mode=defer_fifo
occupancy_personsinteger, persons
operational_capacity_ratiofloat, dimensionless
audience_general_public_personsinteger, persons
audience_families_personsinteger, persons
audience_elderly_personsinteger, persons
audience_students_personsinteger, persons
audience_commuters_personsinteger, persons
audience_event_attendees_personsinteger, persons
dominant_audienceenum, nullable {general_public | families | elderly | students | commuters | event_attendees}
traffic_flow_vehicles_hfloat, vehicles/h
pm25_emission_ug_sfloat, ug/s
pm25_background_ug_m3float, ug/m3
pm25_physical_ug_m3float, ug/m3
pm25_sensor_raw_ug_m3float, ug/m3
pm25_sensor_calibrated_ug_m3float, ug/m3, nullable
pm25_rolling_24h_ug_m3float, ug/m3, nullable — null until complete window
pm25_rolling_completeboolean
no2_emission_ug_sfloat, ug/s
no2_background_ug_m3float, ug/m3
no2_physical_ug_m3float, ug/m3
no2_sensor_raw_ug_m3float, ug/m3
no2_sensor_calibrated_ug_m3float, ug/m3, nullable
no2_rolling_24h_ug_m3float, ug/m3, nullable — null until complete window
no2_rolling_completeboolean
LAeq_15min_dBAfloat, dB(A), nullable — column name embeds the declared window; null until complete window unless warm-up supplies history
noise_window_completeboolean
utci_cfloat, degC
utci_stress_categoryenum {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_clampedboolean
wbgt_outdoor_cfloat, degC, nullable
thermal_risk_levelenum, nullable {low | caution | high_risk | severe}
air_quality_risk_levelenum, nullable {low | caution | high_risk | severe}
noise_risk_levelenum, nullable {low | caution | high_risk | severe}
crowding_risk_levelenum, nullable {low | caution | high_risk | severe}
overall_action_levelenum, nullable {low | caution | high_risk | severe}
dominant_issueenum, nullable {thermal | air_quality | noise | crowding}
co_dominant_issuesjson_array_of_enum {thermal | air_quality | noise | crowding}
elevated_issuesjson_array_of_enum {thermal | air_quality | noise | crowding}
elevated_hazard_countinteger
compound_risk_flagboolean
risk_completeness_fractionfloat, dimensionless
overall_action_level_provisionalboolean
risk_communication_template_idstring
risk_communication_messagestring

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: 88. Same seed + parameters = identical output. IoTSyn v3.1.

Machine-readable Sidecars

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 0.32 0 24.95 1,729.79 54.91 0.89 0.33 22.90 normal stochastic 6 6 0 0 0 0 15 0.03 4 5 1 1 2 2 families 117.21 10,139.84 8 16.10 15.73 27.27 true 16,674.93 14 26.73 24.54 43.78 true 55.27 true 24.34 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 partly_cloudy 0.41 0 24.37 1,633.18 53.67 0.87 0.32 22.59 normal stochastic 10 10 0 0 0 0 16 0.03 9 3 1 2 1 0 general_public 119.98 10,331.71 8 16.43 16.40 27.33 true 16,997.28 14 27.26 32.61 43.94 true 54.41 true 23.72 no thermal stress false low high_risk low 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 partly_cloudy 0.59 2.74 23.61 1,734.66 59.65 1.25 0.46 22.39 normal stochastic 2 2 0 0 0 0 9 0.02 4 2 0 2 1 0 general_public 116.96 10,122.44 8 14.25 14.13 27.36 true 16,645.70 14 23.87 26.39 43.96 true 55.44 true 23.11 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 partly_cloudy 0.74 1.69 22.58 1,723.75 63.11 0.57 0.21 21.80 normal stochastic 4 4 0 0 0 0 8 0.02 2 2 0 2 2 0 131.70 11,146.03 8 20.06 22.51 27.49 true 18,365.33 14 32.91 28.75 44.09 true 56.88 true 22.86 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 partly_cloudy 0.48 0 22.52 1,671.66 61.42 0.94 0.35 20.95 busy stochastic 21 21 0 0 0 0 27 0.05 8 9 1 6 2 1 families 137.98 11,582.29 8 16.92 17.29 27.54 true 19,098.24 14 28.11 30.45 44.19 true 55.84 true 22.19 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 overcast 0.68 0 22.75 1,529.83 55.43 0.32 0.12 21.80 busy stochastic 10 10 0 0 0 0 28 0.06 10 8 2 6 1 1 general_public 137.13 11,523.01 8 24.81 24.55 27.65 true 18,998.65 14 40.19 36.31 44.36 true 54.54 true 22.55 no thermal stress true low high_risk low 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 overcast 0.78 0 22.72 1,549.70 56.24 0.29 0.11 22.05 busy stochastic 12 12 0 0 0 0 23 0.05 9 5 2 5 2 0 general_public 154.74 12,745.78 8 27.93 30.83 27.86 true 21,052.90 14 45.04 38.64 44.56 true 57.65 true 22.66 no thermal stress true 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 partly_cloudy 0.59 0 22.42 1,577.77 58.31 0.30 0.11 21.19 busy stochastic 14 14 0 0 0 0 26 0.05 14 6 0 3 2 1 general_public 189.62 15,167.93 8 31.32 28.71 27.97 true 25,122.12 14 50.55 52.34 44.85 true 55.26 true 22.30 no thermal stress true 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 partly_cloudy 0.38 0 21.60 1,546.79 60.11 0.49 0.18 19.73 busy stochastic 9 9 0 0 0 0 21 0.04 8 3 2 3 2 3 general_public 175.39 14,180.05 8 25.13 23.88 28.04 true 23,462.49 14 40.98 45.47 45.08 true 57.23 true 21.35 no thermal stress true 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 partly_cloudy 0.46 0 20.84 1,544.86 62.90 0.35 0.13 19.22 normal stochastic 13 13 0 0 0 0 23 0.05 6 7 3 3 2 2 families 166.38 13,554.13 8 27.45 27.58 28.18 true 22,410.95 14 44.46 42.60 45.28 true 57.15 true 20.80 no thermal stress true 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

Data Visualization Interactive

Numeric Trends

Category Distribution

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 — Source-Dominated Air Quality, 672 Rows. [Dataset]. IoTSyn Generated. https://iotsyn.com/view.php?uid=iotsyn_6a641ddc32a451.23134771

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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