基于神经网络的高能效无线传感器网络土壤参数预测协调算法

3区 计算机科学 Q1 Computer Science Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-04 DOI:10.1007/s12652-024-04848-1
Dinesh Sharma, Geetam Singh Tomar
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引用次数: 0

摘要

在农业领域使用无线传感器网络(WSN)是信息技术应用的一大进步。最近的技术进步使传感器网络不仅能够提供有关土壤养分水平的实时信息,还能协助实现各种农业流程的自动化。然而,必须承认 WSN 的一个重要局限性,即能源消耗。通过分析从不同土壤类型收集到的实验数据,并采用复杂的数据分析方法,可以观察到养分指数随着时间的推移呈现出相对稳定的模式。因此,可以采用预测性神经网络技术,从 WSN 接收到的主要输入中提取详细的见解。这种方法消除了 WSN 全天持续运行的需要,有助于提高能源效率。为了实现这种高能效运行,NR-MDEC 协议与协调算法结合使用,从而大大提高了整体效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Neural network-based soil parameters predictive coordination algorithm for energy efficient wireless sensor network

The utilization of Wireless Sensor Networks (WSN) in the agricultural field represents a significant stride in the application of Information Technology. Recent advancements in technology have made it possible for sensor networks not only to provide real-time information about soil nutrient levels but also to assist in the automation of various agricultural processes. However, it’s crucial to acknowledge a substantial limitation associated with WSN, namely, energy consumption. Through the analysis of experimental data gathered from diverse soil types and employing sophisticated data analytics, it has been observed that the Nutrient Index exhibits a relatively stable pattern over time. Consequently, predictive neural network techniques can be employed to extract detailed insights from the primary inputs received from WSN. This approach eliminates the need for continuous operation of the WSN throughout the day, contributing to enhanced energy efficiency. To achieve this energy-efficient operation, the NR-MDEC protocol is implemented in conjunction with a coordination algorithm, resulting in a substantial improvement in overall efficiency.

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来源期刊
Journal of Ambient Intelligence and Humanized Computing
Journal of Ambient Intelligence and Humanized Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
9.60
自引率
0.00%
发文量
854
期刊介绍: The purpose of JAIHC is to provide a high profile, leading edge forum for academics, industrial professionals, educators and policy makers involved in the field to contribute, to disseminate the most innovative researches and developments of all aspects of ambient intelligence and humanized computing, such as intelligent/smart objects, environments/spaces, and systems. The journal discusses various technical, safety, personal, social, physical, political, artistic and economic issues. The research topics covered by the journal are (but not limited to): Pervasive/Ubiquitous Computing and Applications Cognitive wireless sensor network Embedded Systems and Software Mobile Computing and Wireless Communications Next Generation Multimedia Systems Security, Privacy and Trust Service and Semantic Computing Advanced Networking Architectures Dependable, Reliable and Autonomic Computing Embedded Smart Agents Context awareness, social sensing and inference Multi modal interaction design Ergonomics and product prototyping Intelligent and self-organizing transportation networks & services Healthcare Systems Virtual Humans & Virtual Worlds Wearables sensors and actuators
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