Sharing Wireless Spectrum in the Forest Ecosystems Using Artificial Intelligence and Machine Learning
Sharing Wireless Spectrum in the Forest Ecosystems Using Artificial Intelligence and Machine Learning
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DOI：
10.1007/s10776-022-00572-9
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发表时间：
2022-08-09
影响因子：
2.5
通讯作者：
Contosta, Alexandra
中科院分区：
文献类型：
--
作者：
Naderi, Sonia;Bundy, Kenneth;Contosta, Alexandra
功率和频谱的智能管理是创建高可靠性和长寿命无线传感器网络的最重要因素。本文研究的主要应用是利用高时空分辨率精确监测森林生态系统。当前系统的高成本及其功耗限制了这些系统的广泛使用，从而限制了当前模型的准确性。该项目利用人工智能和机器学习来了解无线网络和环境的变化，生产低成本的节能系统，以实现大规模监控。拟议的系统是在缅因大学的无线传感器网络 (WiSe-Net) 实验室与新罕布什尔大学和佛蒙特大学的研究人员合作构建的，用于土壤湿度测量，并在后期阶段包括其他类型的传感器。
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.