基于物联网的数字农业大棚远程监控系统

IF 0.9 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI:10.12694/scpe.v24i3.2318
Lu Lu
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引用次数: 0

摘要

传统的数字农业大棚监测系统在实际运行过程中,存在监测范围有限、监测结果与大棚实际情况偏差大等问题。为了解决这一问题,引入物联网技术,提出了一种新的远程监控系统。在完成远程监测系统硬件设计的基础上,通过建立监测数据融合模型,得到数字农业大棚远程监测的最优融合数据值。设计了粒子群优化模糊控制算法,对系统的自适应远程监控过程进行动态优化。采用物联网技术在线部署数字化农业大棚远程监控系统,充分保证远程监控系统的质量和及时性。试验结果表明,新系统能显著改善温室远程监测偏差,监测值接近实际值。
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Remote Monitoring System of Digital Agricultural Greenhouse Based on Internet of Things
In the actual operation process of the conventional digital agricultural greenhouse monitoring system, there are problems such as limited monitoring scope and large deviation between the monitoring results and the actual situation of the greenhouse. To solve this problem, a new remote monitoring system is proposed by introducing the technology of the Internet of Things. On the basis of the completion of the hardware design of the remote monitoring system, the optimal fusion data value of the remote monitoring of the digital agricultural greenhouse is obtained by establishing the monitoring data fusion model. The particle swarm optimization fuzzy control algorithm is designed to optimize the adaptive remote monitoring process of the system dynamically. The Internet of Things technology is used to deploy the remote monitoring system of digital agricultural greenhouses online to fully ensure the quality and timeliness of the remote monitoring system. The test results show that the new system can significantly improve the greenhouse remote monitoring deviation, and the monitoring value is close to the actual value.
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来源期刊
Scalable Computing-Practice and Experience
Scalable Computing-Practice and Experience COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.00
自引率
0.00%
发文量
10
期刊介绍: The area of scalable computing has matured and reached a point where new issues and trends require a professional forum. SCPE will provide this avenue by publishing original refereed papers that address the present as well as the future of parallel and distributed computing. The journal will focus on algorithm development, implementation and execution on real-world parallel architectures, and application of parallel and distributed computing to the solution of real-life problems.
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