Next Article in Journal / Special Issue
Multiparametric Monitoring in Equatorian Tomato Greenhouses (III): Environmental Measurement Dynamics
Previous Article in Journal / Special Issue
Multiparametric Monitoring in Equatorian Tomato Greenhouses (I): Wireless Sensor Network Benchmarking
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(8), 2556; https://doi.org/10.3390/s18082556

Multiparametric Monitoring in Equatorian Tomato Greenhouses (II): Energy Consumption Dynamics

1
Departamento de Eléctrica y Electrónica, Universidad de las Fuerzas Armadas ESPE, Av. General Rumiñahui s/n, Sangolquí 171-5-231B, Ecuador
2
Departamento de Teoría de la Señal y Comunicaciones, Sistemas Telemáticos y Computación, Universidad Rey Juan Carlos, 28943 Fuenlabrada, Spain
3
Departamento de Ciencias Exactas, Universidad de las Fuerzas Armadas ESPE, Av. General Rumiñahui s/n, Sangolquí 171-5-231B, Ecuador
4
Center for Computational Simulation, Universidad Politécnica de Madrid, Boadilla del Monte, 28660 Madrid, Spain
5
Carrera de Telecomunicaciones, Universidad Politécnica Salesiana, 010105 Cuenca, Ecuador
*
Author to whom correspondence should be addressed.
Received: 31 May 2018 / Revised: 31 July 2018 / Accepted: 2 August 2018 / Published: 4 August 2018
(This article belongs to the Special Issue Intelligent Sensor Systems for Environmental Monitoring)
Full-Text   |   PDF [3931 KB, uploaded 6 August 2018]   |  

Abstract

Tomato greenhouses are a crucial element in the Equadorian economy. Wireless sensor networks (WSNs) have received much attention in recent years in specialized applications such as precision farming. The energy consumption in WSNs is relevant nowadays for their adequate operation, and attention is being paid to analyzing the affecting factors, energy optimization techniques working on the network hardware or software, and characterizing the consumption in the nodes (especially in the ZigBee standard). However, limited information exists on the analysis of the consumption dynamics in each node, across different network technologies and communication topologies, or on the incidence of data transmission speed. The present study aims to provide a detailed analysis of the dynamics of the energy consumption for tomato greenhouse monitoring in Ecuador, in three types of WSNs, namely, ZigBee with star topology, ZigBee with mesh topology (referred to here as DigiMesh), and WiFi with access point topology. The networks were installed and maintained in operation with a line of sight between nodes and a 2-m length, whereas the energy consumption measurements of each node were acquired and stored in the laboratory. Each experiment was repeated ten times, and consumption measurements were taken every ten milliseconds at a rate of fifty thousand samples for each realization. The dynamics were scrutinized by analyzing the recorded time series using stochastic-process analysis methods, including amplitude probability functions and temporal autocorrelation, as well as bootstrap resampling techniques and representations of various embodiments with the so-called M-mode plots. Our results show that the energy consumption of each network strongly depends on the type of sensors installed in the nodes and on the network topology. Specifically, the CO2 sensor has the highest power consumption because its chemical composition requires preheating to start logging measurements. The ZigBee network is more efficient in energy saving independently of the transmission rate, since the communication modules have lower average consumption in data transmission, in contrast to the DigiMesh network, whose consumption is high due to its topology. Results also show that the average energy consumption in WiFi networks is the highest, given that the coordinator node is a Meshlium™ router with larger energy demand. The transmission duration in the ZigBee network is lower than in the other two networks. In conclusion, the ZigBee network with star topology is the most energy-suitable one when designing wireless monitoring systems in greenhouses. The proposed methodology for consumption dynamics analysis in tomato greenhouse WSNs can be applied to other scenarios where the practical choice of an energy-efficient network is necessary due to energy constrains in the sensor and coordinator nodes. View Full-Text
Keywords: wireless sensor networks; stochastic process; energy consumption; tomato greenhouse; M-mode plots. wireless sensor networks; stochastic process; energy consumption; tomato greenhouse; M-mode plots.
Figures

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

Share & Cite This Article

MDPI and ACS Style

Erazo-Rodas, M.; Sandoval-Moreno, M.; Muñoz-Romero, S.; Huerta, M.; Rivas-Lalaleo, D.; Rojo-Álvarez, J.L. Multiparametric Monitoring in Equatorian Tomato Greenhouses (II): Energy Consumption Dynamics. Sensors 2018, 18, 2556.

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

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