Published June 27, 2019 | Version 1.0
Report Open

D6.1 Report on value-adding approaches and algorithms for single sensor and inter-sensor data processing. Deliverable report of project H2020 MONOCLE (grant 776480)

  • 1. Plymouth Marine Laboratory
  • 2. VITO
  • 3. Water Insight
  • 4. Universiteit Leiden
  • 5. DDQ
  • 6. Peak Design
  • 7. CSIC

Description

This document highlights a number of techniques and approaches that are being tested in MONOCLE in order to increase the quality and utility of the data collected by the suite of sensors developed and used in the project.  Many of the techniques discussed here could be used for other sensors in the field of water quality monitoring.

The approaches can be split into two categories: 1) techniques/approaches that will optimise data processing procedures and 2) those that will allow increased information retrieval from a  given dataset or combination of datasets.  Following a discussion of both of these areas, we formulate intended tests and demonstrations to be performed within MONOCLE alongside a set of data requirements.

Files

D6.1_Value-adding-approaches-algorithms-for-single-sensor-and-inter-sensor-data-processing_v1.0.pdf

Additional details

Funding

MONOCLE – Multiscale Observation Networks for Optical monitoring of Coastal waters, Lakes and Estuaries 776480
European Commission