Kentucky-Open-Science/TEMI-VOC

Temi VOC/Smell Datasets

This dataset includes processed smell collection metrics recorded by 2 versions of the SmartNanotubes Smell Inspector. The sensor was attached to the tray of a Temi robot, which roamed our office on a set path. The robot patrolled roughly once an hour during working hours and recorded a few dozen smell data points on each run. At each smell data point (in the processed/new-sensor.csv file), the robot also took a picture using its front top camera of the area that it was in.

Data collection ran from 2025-04-21 to 2026-01-09 (263 calendar days, ~8.6 months), with data recorded on 148 of those days.

Old Sensor: Firmware version 3.0.1 New Sensor: Firmware version 2.1.1 (we replaced the old sensor with the new sensor due to faults in the old sensor, even though it was a downgrade in firmware version). The two firmware numbers do not reflect a linear progression in capability.

Raw and processed CSV data and code for cleaning can be found on github.

Contents

• processed/old-sensor.csv — 64 raw channels + temperature + humidity
• processed/new-sensor.csv — the above plus robot x/y position and frame filename
• processed/old-sensor-features.csv, processed/new-sensor-features.csv — Configuration A feature mapping applied
• frames.zip — 74,870 JPEG frames, one per row of new-sensor.csv

Dataset Summary

All figures below were computed from the released files.

Property	Old sensor	New sensor	Combined
Collection period	2025-04-21 to 2025-05-30	2025-06-02 to 2026-01-09	2025-04-21 to 2026-01-09
Calendar span	39 days	220 days	263 days (~8.6 months)
Days with data	23	125	148
Cleaned rows	12,360	74,870	87,230
Patrol runs	155	972	1,127
Median rows per run	67	61	—
Median logging interval	6.0 s	6.0 s	6.0 s
Synchronized frames	N/A	74,870	74,870
Image archive size	N/A	4.3 GB (frames.zip)	4.3 GB
Frame resolution	N/A	640 × 480	640 × 480
Robot position	No	Yes	New sensor only
Patrol footprint	N/A	~33 m × 62 m	N/A
Temperature range	25.3–28.6 °C	25.4–27.8 °C	25.3–28.6 °C
Humidity range	23.3–53.7 %	7.3–37.3 %	7.3–53.7 %
Firmware version	3.0.1	2.1.1	—

The device's own read-out cadence is 1.8 s for all 64 channels (per the manufacturer's manual), but the logging service sampled it during patrol runs rather than continuously; the median interval between consecutive logged rows within a run is 6.0 s. All rows carry timestamps between 08:00 and 17:00 local time.

Every row in new-sensor.csv references a distinct frame in frames.zip, and the archive contains exactly 74,870 images — the row/frame correspondence is one-to-one.

Temporal gaps

Sampling is not uniform. Data were recorded on 23 of the 39 calendar days spanned by the old-sensor split and 125 of the 220 days spanned by the new-sensor split. Within those periods, intervals longer than one hour occur 42 times (old sensor) and 217 times (new sensor); the longest single gaps are 10.0 and 12.7 days respectively. Gaps come from charging cycles, firmware updates, network outages, and periods when the robot was unavailable. Nothing is interpolated — rows are either present or absent — so gap locations are recoverable directly from the timestamp sequence. Handle them explicitly in any time-series modeling.

Data Dictionary (processed/old-sensor.csv)

Column	Data Type	Purpose
Timestamp	DateTime (YYYY-MM-DD hh:mm:ss)	The timestamp when the smell measurement was taken
value_{0,1,2,...63}	float	Measurement from each of the 64 smell sensor channels (raw values from sensor)
temperature	float	Measurement from the temperature sensor included in the smell sensor (Celsius)
humidity	float	Measurement from the humidity sensor included in the smell sensor (%)

Data Dictionary (processed/new-sensor.csv)

Column	Data Type	Purpose
Timestamp	DateTime (YYYY-MM-DD hh:mm:ss)	The timestamp when the smell measurement was taken
value_{0,1,2,...63}	float	Measurement from each of the 64 smell sensor channels (raw values from sensor)
temperature	float	Measurement from the temperature sensor included in the smell sensor (Celsius)
humidity	float	Measurement from the humidity sensor included in the smell sensor (%)
robot_x_position	float	X position of the robot w.r.t. its home base
robot_y_position	float	Y position of the robot w.r.t. its home base
frame_filename	string	Filename of the picture taken by the robot when a smell was measured (see frames.zip)

A note on raw channel magnitudes

Raw channel magnitudes are strongly non-uniform. In new-sensor.csv, seven channels (0, 1, 14, 15, 19, 48, 49) have median values more than an order of magnitude above the typical channel, with channels 19, 48 and 49 sitting near 2.2e6 against a median channel value of ~8.1e3. In old-sensor.csv the spread is much smaller (largest per-channel median is 24× the smallest, and no channel exceeds 10× the typical value).

In both splits these high-magnitude channels are exactly the base/reference channels that the manufacturer's Configuration A mapping marks as 999 and that the feature-preparation script drops. The spread is a property of individual channels and their assigned role, not of any one detector chip. If you work with the raw 64-channel vector instead of the mapped feature set, scale per channel before analysis.

Channel mapping

Under the manufacturer's Configuration A mapping, 45 of the 64 channels carry analyte-relevant signal corresponding to 15 distinct feature IDs, each measured by 3 replicate channels; the three replicates for a given feature ID sit within a single detector type, not one per detector. The remaining 19 channels are base/reference channels excluded from analysis. The *-features.csv files have this mapping already applied.

License

This dataset is licenced under the Apache License 2.0.