Next Article in Journal
Crack Detection in Concrete Tunnels Using a Gabor Filter Invariant to Rotation
Next Article in Special Issue
Autonomous Sensors Powered by Energy Harvesting from von Karman Vortices in Airflow
Previous Article in Journal
Scheduling for Emergency Tasks in Industrial Wireless Sensor Networks
Previous Article in Special Issue
A Smart and Balanced Energy-Efficient Multihop Clustering Algorithm (Smart-BEEM) for MIMO IoT Systems in Future Networks
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessArticle
Sensors 2017, 17(7), 1666; https://doi.org/10.3390/s17071666

Dual-Source Linear Energy Prediction (LINE-P) Model in the Context of WSNs

1
Thomas Johann Seebeck Department of Electronic, Tallinn University of Technology, Tallinn 12616, Estonia
2
Department of Cybernetics, Tallinn University of Technology, Tallinn 12616, Estonia
*
Authors to whom correspondence should be addressed.
Received: 12 May 2017 / Revised: 13 July 2017 / Accepted: 14 July 2017 / Published: 20 July 2017
(This article belongs to the Special Issue Energy Harvesting Sensors for Long Term Applications in the IoT Era)
View Full-Text   |   Download PDF [1791 KB, uploaded 20 July 2017]   |  

Abstract

Energy harvesting technologies such as miniature power solar panels and micro wind turbines are increasingly used to help power wireless sensor network nodes. However, a major drawback of energy harvesting is its varying and intermittent characteristic, which can negatively affect the quality of service. This calls for careful design and operation of the nodes, possibly by means of, e.g., dynamic duty cycling and/or dynamic frequency and voltage scaling. In this context, various energy prediction models have been proposed in the literature; however, they are typically compute-intensive or only suitable for a single type of energy source. In this paper, we propose Linear Energy Prediction “LINE-P”, a lightweight, yet relatively accurate model based on approximation and sampling theory; LINE-P is suitable for dual-source energy harvesting. Simulations and comparisons against existing similar models have been conducted with low and medium resolutions (i.e., 60 and 22 min intervals/24 h) for the solar energy source (low variations) and with high resolutions (15 min intervals/24 h) for the wind energy source. The results show that the accuracy of the solar-based and wind-based predictions is up to approximately 98% and 96%, respectively, while requiring a lower complexity and memory than the other models. For the cases where LINE-P’s accuracy is lower than that of other approaches, it still has the advantage of lower computing requirements, making it more suitable for embedded implementation, e.g., in wireless sensor network coordinator nodes or gateways. View Full-Text
Keywords: WSN; energy harvesting; transient computing WSN; energy harvesting; transient computing
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).

Share & Cite This Article

MDPI and ACS Style

Ahmed, F.; Tamberg, G.; Le Moullec, Y.; Annus, P. Dual-Source Linear Energy Prediction (LINE-P) Model in the Context of WSNs. Sensors 2017, 17, 1666.

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