Iván Palomares Carrascosa Generates 365 Days of IoT Temperature Data With Mimesis
Updated
Updated · KDnuggets · Jun 1
Iván Palomares Carrascosa Generates 365 Days of IoT Temperature Data With Mimesis
1 articles · Updated · KDnuggets · Jun 1
Summary
A 365-day synthetic IoT dataset pairs daily temperature readings with device metadata, including a UUID, city, firmware version and IP address, to mimic a single real sensor.
NumPy drives a sine-wave seasonal curve with a 15°C base, 12°C amplitude and 80-day phase shift, while Mimesis adds daily noise of -2.0 to 2.0°C and latency of 12 to 145 ms.
Sample output shows winter readings near 3.18°C to 4.90°C in early January and summer values around 25.81°C to 28.84°C by late June and early July.
Pandas builds the Jan. 1, 2026-starting daily timeline and stores the records in a DataFrame, leaving the mock series ready for forecasting experiments, dashboards and other IoT analyses.