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Issue title: Artificial Intelligence as a maturing and growing technology: An urgent need for intelligent systems
Guest editors: X. Yuan and M. Elhoseny
Article type: Research Article
Authors: Lou, Feiyana; * | Kong, Depenga | Wang, Zhiweib
Affiliations: [a] The College of Education Science and Technology, ZheJiang University of Technology, Hangzhou, Zhejiang Province, China | [b] Suzhou Tianzhun Technology Co., Ltd, Suzhou, Jiangsu Province, China
Correspondence: [*] Corresponding author. Feiyan Lou, The College of Education Science and Technology, ZheJiang University of Technology, Hangzhou, Zhejiang Province, 310014, China. E-mail: [email protected].
Abstract: Agricultural IoT technology realizes the technology of precise, intelligent, and scientific management of agricultural production. Accurate perception and efficient transmission of farmland data is the basis for precision and smart agriculture. Based on the consideration of WSN distributed monitoring sensor nodes, this paper designs a multi-core sensing agricultural Internet of Things monitoring system based on the low efficiency of existing single-core computing and the inability to adapt to massive sensing data node operations. Multi-core data fusion was simulated and analyzed. Firstly, a method for constructing key value subspaces based on logical landmarks is proposed. The node set maintained by the subspace adds local physical location features to coordinate node discovery and routing. Compared with the traditional key value space, the subspace has a higher system priority, which makes the route local priority, thus realizing traffic localization. The simulation results show that the distributed agricultural network data aggregation algorithm based on multi-core perception can significantly reduce the energy consumption of sensor nodes in WSN, prolong the service life of WSN, and greatly improve the computational efficiency and data accuracy.
Keywords: Agricultural IoT, multi-core sensing, single-core, WSN
DOI: 10.3233/JIFS-189323
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2827-2837, 2021
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