Next Article in Journal
Multispectral Palmprint Recognition Using a Quaternion Matrix
Previous Article in Journal
Template Free Synthesis of Hollow Ball-Like Nano-Fe2O3 and Its Application to the Detection of Dimethyl Methylphosphonate at Room Temperature
Article Menu

Export Article

Open AccessArticle
Sensors 2012, 12(4), 4605-4632; doi:10.3390/s120404605

A Neural Network Approach to Smarter Sensor Networks for Water Quality Monitoring

1
CLARITY: Centre for Sensor Web Technologies, Dublin City University, Glasnevin, Dublin 9, Ireland
2
MESTECH: Marine and Environmental Sensing Technology Hub, Dublin City University, Glasnevin, Dublin 9, Ireland
*
Author to whom correspondence should be addressed.
Received: 21 February 2012 / Revised: 21 March 2012 / Accepted: 30 March 2012 / Published: 10 April 2012
(This article belongs to the Section Sensor Networks)

Abstract

Environmental monitoring is evolving towards large-scale and low-cost sensor networks operating reliability and autonomously over extended periods of time. Sophisticated analytical instrumentation such as chemo-bio sensors present inherent limitations because of the number of samples that they can take. In order to maximize their deployment lifetime, we propose the coordination of multiple heterogeneous information sources. We use rainfall radar images and information from a water depth sensor as input to a neural network (NN) to dictate the sampling frequency of a phosphate analyzer at the River Lee in Cork, Ireland. This approach shows varied performance for different times of the year but overall produces output that is very satisfactory for the application context in question. Our study demonstrates that even with limited training data, a system for controlling the sampling rate of the nutrient sensor can be set up and can improve the efficiency of the more sophisticated nodes of the sensor network.
Keywords: multi-modal sensor networks; rainfall radar; chemical sensors; environmental monitoring; visual sensing multi-modal sensor networks; rainfall radar; chemical sensors; environmental monitoring; visual sensing
Figures

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

O’Connor, E.; Smeaton, A.F.; O’Connor, N.E.; Regan, F. A Neural Network Approach to Smarter Sensor Networks for Water Quality Monitoring. Sensors 2012, 12, 4605-4632.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top