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Sharing Wireless Spectrum in the Forest Ecosystems Using Artificial Intelligence and Machine Learning.

Authors :
Naderi, Sonia
Bundy, Kenneth
Whitney, Thayer
Abedi, Ali
Weiskittel, Aaron
Contosta, Alexandra
Source :
International Journal of Wireless Information Networks. Sep2022, Vol. 29 Issue 3, p257-268. 12p.
Publication Year :
2022

Abstract

Intelligent management of power and spectrum is the most important ingredient in creating wireless sensor networks with high reliability and longevity. The main application under study in this paper is accurate monitoring of forest ecosystems using high spatio-temporal resolution. High cost of the current systems and their power consumption limits wide spread use of these systems limiting the accuracy of current models. This project utilizes artificial intelligence and machine learning to learn the changes in the wireless network and environment, producing power efficient systems that are low cost to enable large scale monitoring. The proposed system was built at the University of Maine's Wireless Sensor Networks (WiSe-Net) laboratory in collaboration with University of New Hampshire and University of Vermont researchers for soil moisture measurement with provision to include other sensor types at later stages. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10689605
Volume :
29
Issue :
3
Database :
Academic Search Index
Journal :
International Journal of Wireless Information Networks
Publication Type :
Academic Journal
Accession number :
158725668
Full Text :
https://doi.org/10.1007/s10776-022-00572-9