Physics-Based · CC0 Licensed · Reproducible

Synthetic IoT Dataset Generator

Every data point comes from documented mathematical models — Fourier decomposition, mass-balance ODEs, Weibull distributions. No opaque neural networks.

Start Free How it Works
6 IoT Domains · 10,000+ Rows per Dataset · 10 Academic References
🏠

Smart Home

Fourier temperature, CO₂ mass-balance ODE, Markov occupancy, deadband HVAC

🛡️

IoT Security

Burst attack patterns, LogNormal packets, 5 attack types with phase progression

⚙️

Predictive Maintenance

Weibull degradation, ISO 10816 vibration, bearing temperature models

🏥

Medical IoT

Circadian vital signs, NEWS2 scoring, glucose meal-response model

🏭

IIoT Network

Modbus/OPC UA/DNP3 traffic, OT-specific attacks, device role modeling

🚗

Connected Vehicle

Speed state machine, GPS dead reckoning, fuel consumption model

Generate a Dataset

Choose domain, configure parameters, download CSV.

Ready to Generate?

Create a free account to start generating research-grade IoT datasets. Your first generation is on us.

Create Free Account Sign In

1 free generation · No credit card required

How IoTSyn Works

Transparent, reproducible data generation grounded in established mathematical frameworks.

1

Choose Domain & Parameters

Select from 6 IoT domains. Configure physical parameters — climate, equipment type, patient demographics, network topology. Defaults are calibrated from literature.

2

Physics-Based Generation

Data is generated from explicit mathematical models — Fourier decomposition, mass-balance ODEs, Weibull distributions, Markov chains. Every equation is documented.

3

Download & Cite

Download as CSV with metadata header. Each dataset includes its seed for exact reproduction, and auto-generated citations in APA, MLA, Chicago, IEEE, BibTeX, and Harvard.

Sample Mathematical Models

Temperature (Multi-harmonic Fourier)

T(t) = T_set + A₁·sin(ω₁t + φ₁) + A₂·sin(2ω₁t + φ₂) + T_season(d) + ε(t)

CO₂ Concentration (Mass-Balance ODE)

dC/dt = (n·G − Q·(C − C_out)) / V

Equipment Degradation (Weibull CDF)

D(t) = 1 − exp(−(t/L)^β)

Correlated Variables (Cholesky)

Y = μ_y + σ_y · (ρ·Z_x + √(1−ρ²)·Z_ind)
See complete methodology with all equations →

📄 Technical Report

Full mathematical specification of all 6 generators, with 10 academic references including Box-Muller, Knuth, Marsaglia-Tsang, and ISO 10816.

Read & cite the technical report →

📦 Public Dataset Repository

Generated datasets are periodically published to IoTDataset.com for direct browsing and download.

Visit IoTDataset.com →