Next Article in Journal
A Multi-Disciplinary Approach to Remote Sensing through Low-Cost UAVs
Next Article in Special Issue
Intercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production
Previous Article in Journal
Integration of P-CuO Thin Sputtered Layers onto Microsensor Platforms for Gas Sensing
Previous Article in Special Issue
Crop Classification in Satellite Images through Probabilistic Segmentation Based on Multiple Sources
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(6), 1410; doi:10.3390/s17061410

Root System Water Consumption Pattern Identification on Time Series Data

Telefonica Investigación y Desarrollo Chile, Manuel Montt 1404, 7501105 Santiago, Chile
Author to whom correspondence should be addressed.
Academic Editor: Lammert Kooistra
Received: 6 March 2017 / Revised: 25 May 2017 / Accepted: 2 June 2017 / Published: 16 June 2017
(This article belongs to the Special Issue Precision Agriculture and Remote Sensing Data Fusion)
View Full-Text   |   Download PDF [1389 KB, uploaded 16 June 2017]   |  


In agriculture, soil and meteorological sensors are used along low power networks to capture data, which allows for optimal resource usage and minimizing environmental impact. This study uses time series analysis methods for outliers’ detection and pattern recognition on soil moisture sensor data to identify irrigation and consumption patterns and to improve a soil moisture prediction and irrigation system. This study compares three new algorithms with the current detection technique in the project; the results greatly decrease the number of false positives detected. The best result is obtained by the Series Strings Comparison (SSC) algorithm averaging a precision of 0.872 on the testing sets, vastly improving the current system’s 0.348 precision. View Full-Text
Keywords: time series analysis; precision agriculture; data science; pattern recognition; Internet of Things time series analysis; precision agriculture; data science; pattern recognition; Internet of Things

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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

Figueroa, M.; Pope, C. Root System Water Consumption Pattern Identification on Time Series Data. Sensors 2017, 17, 1410.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



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