Accurate models of energy harvesting for smart environments

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Title: Accurate models of energy harvesting for smart environments
Authors: Jackson, G
Kartakis, S
McCann, J
Item Type: Conference Paper
Abstract: Over the last decade, the energy optimization of resource constrained sensor nodes constitutes a major research topic in smart environments. However, state of the art energy optimization algorithms make strong and unrealistic assumptions of energy models, both in simulations and during the operation of smart systems. For instance, simplistic energy models for energy harvesting leads to inaccurate representation and prediction of the true dynamics of energy. Consequently, systems for smart environments are unable to meet expected performance criteria. In this paper, we propose innovative models to overcome the drawbacks of simplistic energy representations in smart environments. We provide the insights of how to generate precise lightweight energy models. Using the physical properties of solar and flow energy harvesting as case studies, the trade-off between energy harvesting inference and real-time measurement of energy generation is explored. To evaluate our proposed energy models against the simplistic versions, we use real measured data from our environmental micro-climate monitoring deployment in an urban park and a 103% improvement is seen. Additionally, to define the trade-offs between inferred and measured energy generation, experiments are conducted utilizing solar and smart water testbeds.
Issue Date: 29-May-2017
Date of Acceptance: 4-Apr-2017
Publisher: IEEE
Copyright Statement: This paper is embargoed until publication.
Sponsor/Funder: NEC Corporation
Intel Corporation
Funder's Grant Number: N/A
Conference Name: IEEE International Conference on Smart Computing (SMARTCOMP 2017)
Publication Status: Accepted
Start Date: 2017-05-29
Finish Date: 2017-05-31
Conference Place: Hong Kong, China
Embargo Date: publication subject to indefinite embargo
Appears in Collections:Faculty of Engineering

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