Datasets:

ICOS-AI
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scaphandre_power_consumption

timestamp float64 1.75B 1.75B	power_consumption float64 0 119
1,752,571,594.489	108.142073
1,752,571,597.489	103.238541
1,752,571,600.492	97.103658
1,752,571,603.489	96.35527
1,752,571,606.489	96.158461
1,752,571,609.489	93.928262
1,752,571,612.489	82.345303
1,752,571,615.489	103.054384
1,752,571,618.489	102.943467
1,752,571,621.491	84.720439
1,752,571,624.489	100.424696
1,752,571,627.489	86.549167
1,752,571,630.489	78.951423
1,752,571,633.489	88.331293
1,752,571,636.489	111.739137
1,752,571,639.489	108.39853
1,752,571,642.489	95.574421
1,752,571,645.489	94.552514
1,752,571,648.489	86.556033
1,752,571,651.491	64.774462
1,752,571,654.489	97.689792
1,752,571,657.489	94.656991
1,752,571,660.491	90.483545
1,752,571,663.489	95.222431
1,752,571,666.489	102.982565
1,752,571,669.489	101.55846
1,752,571,672.489	85.260135
1,752,571,675.489	97.649479
1,752,571,678.489	95.325159
1,752,571,681.489	80.601182
1,752,571,684.489	106.134585
1,752,571,687.489	94.477198
1,752,571,690.489	87.801715
1,752,571,693.489	90.984561
1,752,571,696.489	104.683635
1,752,571,699.489	101.582286
1,752,571,702.489	85.92635
1,752,571,705.489	81.340273
1,752,571,708.489	76.516823
1,752,571,711.492	51.313551
1,752,571,714.489	85.394136
1,752,571,717.489	85.23164
1,752,571,720.491	81.083699
1,752,571,723.489	75.139062
1,752,571,726.489	78.038225
1,752,571,729.489	74.609336
1,752,571,732.489	60.741369
1,752,571,735.489	108.480295
1,752,571,738.489	112.046941
1,752,571,741.491	90.727166
1,752,571,744.489	107.844052
1,752,571,747.489	95.64399
1,752,571,750.491	88.311606
1,752,571,753.489	87.900687
1,752,571,756.489	96.043585
1,752,571,759.489	92.213744
1,752,571,762.489	83.512488
1,752,571,765.489	80.571743
1,752,571,768.489	76.419705
1,752,571,771.491	52.29108
1,752,571,774.489	107.544786
1,752,571,777.489	111.182379
1,752,571,780.489	106.006039
1,752,571,783.489	96.484845
1,752,571,786.489	96.851684
1,752,571,789.489	92.39447
1,752,571,792.489	81.347532
1,752,571,795.489	103.503755
1,752,571,798.489	103.559489
1,752,571,801.492	83.793987
1,752,571,804.489	91.901142
1,752,571,807.489	76.603473
1,752,571,810.492	68.08631
1,752,571,813.489	69.540236
1,752,571,816.489	95.692395
1,752,571,819.489	92.288938
1,752,571,822.489	86.330013
1,752,571,825.489	100.723192
1,752,571,828.489	104.530407
1,752,571,831.489	83.130767
1,752,571,834.489	109.978391
1,752,571,837.489	103.865012
1,752,571,840.491	97.219782
1,752,571,843.489	88.059434
1,752,571,846.489	79.38555
1,752,571,849.489	76.505052
1,752,571,852.489	62.155645
1,752,571,855.489	111.727652
1,752,571,858.489	116.144579
1,752,571,861.491	102.144219
1,752,571,864.489	110.481415
1,752,571,867.489	95.150152
1,752,571,870.489	87.793454
1,752,571,873.489	91.675676
1,752,571,876.489	103.990212
1,752,571,879.489	102.019235
1,752,571,882.489	87.224667
1,752,571,885.489	82.063105
1,752,571,888.489	77.45618
1,752,571,891.491	51.94163

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Scaphandre Power Consumption Dataset

Dataset Description

This dataset contains power consumption monitoring data collected using Scaphandre for the ICOS Federated Learning infrastructure.

Overview

Source: Scaphandre energy monitoring tool
Collection Method: Live system monitoring (continuous fetching)
Purpose: Training data for ICOS FL
Update Frequency: Real-time collection with 3s intervals

Data Schema

Column	Type	Description
timestamp	float	Unix timestamp of measurement
power_consumption	float	Power usage value

Usage in ICOS FL

This dataset is used during the ICOS Federated Learning training process. Note that actual training uses live-fetched data, so values change continuously.

ICOS Project Context

Part of the ICOS meta-operating system for the edge-cloud continuum, focusing on:

Energy efficiency optimization
Power consumption tracking
Sustainable edge computing

Funded by the European Union's Horizon programme (Grant No 101070177)

Downloads last month: 16

Size of downloaded dataset files:

8.74 kB

Size of the auto-converted Parquet files:

6.16 kB

Number of rows:

300