Automated multivariate analysis of multi-sensor data submitted online: Real-time environmental monitoring

<div><p>A pilot study demonstrating real-time environmental monitoring with automated multivariate analysis of multi-sensor data submitted online has been performed at the cabled LoVe Ocean Observatory located at 258 m depth 20 km off the coast of Lofoten-Vesterålen, Norway. The major purpose was efficient monitoring of many variables simultaneously and early detection of changes and time-trends in the overall response pattern before changes were evident in individual variables. The pilot study was performed with 12 sensors from May 16 to August 31, 2015. The sensors provided data for chlorophyll, turbidity, conductivity, temperature (three sensors), salinity (calculated from temperature and conductivity), biomass at three different depth intervals (5–50, 50–120, 120–250 m), and current speed measured in two directions (east and north) using two sensors covering different depths with overlap. A total of 88 variables were monitored, 78 from the two current speed sensors. The time-resolution varied, thus the data had to be aligned to a common time resolution. After alignment, the data were interpreted using principal component analysis (PCA). Initially, a calibration model was established using data from May 16 to July 31. The data on current speed from two sensors were subject to two separate PCA models and the score vectors from these two models were combined with the other 10 variables in a multi-block PCA model. The observations from August were projected on the calibration model consecutively one at a time and the result was visualized in a score plot. Automated PCA of multi-sensor data submitted online is illustrated with an attached time-lapse video covering the relative short time period used in the pilot study. Methods for statistical validation, and warning and alarm limits are described. Redundant sensors enable sensor diagnostics and quality assurance. In a future perspective, the concept may be used in integrated environmental monitoring.</p></div

Q-residual plot for one August observation (marked with an arrow in Fig 5).

<p>Q-residual plot for one August observation (marked with an arrow in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189443#pone.0189443.g005" target="_blank">Fig 5</a>).</p

Scatter plot of the current speed north at 18 and 23 m above sea bed for Continental (left) and at 23 m above sea bed for Continental and Aquadopp (right).

<p>A: Aquadopp; C: Continental; N: north.</p

Correlation loading plot after PCA on current speed data 3–23 m above sea bed from both current speed sensors.

<p>A: Aquadopp; C: Continental; E: east; N: north.</p

Score plot (left) and correlation loading plot (right) for the calibration model.

<p>Score plot (left) and correlation loading plot (right) for the calibration model.</p

Score plot with projection of the August data on the calibration model.

<p>Score plot with projection of the August data on the calibration model.</p

Illustration of the multi-block model.

<p>Ind: variable block for individual sensors; A: variable block for Aquadopp profiler; C: variable block for Continental ADCP.</p

Hotelling's <i>T</i>² contribution plot representing one observation (marked with an arrow in Fig 3).

<p>Hotelling's <i>T</i>² contribution plot representing one observation (marked with an arrow in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189443#pone.0189443.g003" target="_blank">Fig 3</a>).</p

Abbreviations used for some variables in the correlation loading plot (Fig 2) and the contribution plots (Figs 4 and 6).

<p>Abbreviations used for some variables in the correlation loading plot (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189443#pone.0189443.g002" target="_blank">Fig 2</a>) and the contribution plots (Figs <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189443#pone.0189443.g004" target="_blank">4</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0189443#pone.0189443.g006" target="_blank">6</a>).</p

Q-residual plot for all August observations.

<p>Q-residual plot for all August observations.</p