In-network distributed solar current prediction

Basha, Elizabeth, Jurdak, Raja and Rus, Daniela (2015) In-network distributed solar current prediction. ACM Transactions on Sensor Networks, 11 2: . doi:10.1145/2629593

Author Basha, Elizabeth
Jurdak, Raja
Rus, Daniela
Title In-network distributed solar current prediction
Journal name ACM Transactions on Sensor Networks   Check publisher's open access policy
ISSN 1550-4867
Publication date 2015-02
Year available 2015
Sub-type Article (original research)
DOI 10.1145/2629593
Open Access Status
Volume 11
Issue 2
Total pages 28
Place of publication New York, United States
Publisher ACM Special Interest Group
Collection year 2016
Language eng
Formatted abstract
Long-term sensor network deployments demand careful power management. While managing power requires understanding the amount of energy harvestable from the local environment, current solar prediction methods rely only on recent local history, which makes them susceptible to high variability. In this article, we present a model and algorithms for distributed solar current prediction based on multiple linear regression to predict future solar current based on local, in situ climatic and solar measurements. These algorithms leverage spatial information from neighbors and adapt to the changing local conditions not captured by global climatic information. We implement these algorithms on our Fleck platform and run a 7-week-long experiment validating our work. In analyzing our results from this experiment, we determined that computing our model requires an increased energy expenditure of 4.5mJ over simpler models (on the order of 10-7% of the harvested energy) to gain a prediction improvement of 39.7%.
Keyword Energy management
Sensor network
Solar current
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Information Technology and Electrical Engineering Publications
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