Analysis of intelligent agricultural system and control mode based on fuzzy control and sensor network

被引:8
|
作者
Cheng Lijun [1 ]
Zhang Yubo [1 ]
机构
[1] Shanxi Agr Univ, Sch Software, Taigu 030801, Peoples R China
关键词
Intelligent agriculture; wireless technology; sensor networks; fuzzy control; INFORMATION-SYSTEM; ALGORITHM;
D O I
10.3233/JIFS-179213
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Internet of Things (IOT) is the main technical support of smart agriculture. The sensor equipment of the Internet of Things (IOT) in agriculture is developing in the direction of low cost, self-adaptation, high reliability and low power consumption. In the future, the sensor network will gradually have the characteristics of distributed, multi-protocol compatibility, self-organization and high throughput. In this paper, the authors analyze the intelligent agricultural system and control mode based on fuzzy control and sensor network. Intelligent agriculture is based on the most efficient use of various agricultural resources to minimize agricultural energy consumption and costs. It is supported by Internet of Things technologies such as comprehensive perception, reliable transmission and intelligent processing. Using ROF technology, the WiFi signal is pulled far, and the wireless coverage is expanded greatly. At the same time, through the combination of wireless sensor technology such as ZigBee, the transmission and centralized control of sensing signals are realized, and the monitoring system of intelligent agricultural greenhouse is established. The simulation results show that the system can effectively improve the level of intelligence and information of agricultural greenhouse management, and greatly improve crop production efficiency.
引用
收藏
页码:6325 / 6336
页数:12
相关论文
共 50 条
  • [31] AN INTELLIGENT CONTROL SYSTEM BASED ON RECURRENT NEURAL FUZZY NETWORK AND ITS APPLICATION TO CSTR
    JIA Li YU Jinshou (Research Institute of Automation
    Journal of Systems Science & Complexity, 2005, (01) : 43 - 54
  • [32] Layered mode selection logic control with fuzzy sensor fusion network
    Born, Traig
    Wright, Andrew
    UNMANNED SYSTEMS TECHNOLOGY IX, 2007, 6561
  • [33] Intelligent fuzzy sliding mode control for complex robot system with disturbances
    Zheng, Kunming
    Hu, Youmin
    Wu, Bo
    EUROPEAN JOURNAL OF CONTROL, 2020, 51 : 95 - 109
  • [34] An intelligent system control method based on visual sensor
    Diao H.
    Yin L.
    Liang B.
    Chen Y.
    Measurement: Sensors, 2023, 29
  • [35] Research on the sliding mode control based on the network control system
    Zhang, Gang
    Bu, Ting
    Jiao, Wentan
    Ge, Yunwang
    BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2020, 126 : 135 - 136
  • [36] Fuzzy intelligent combustion control based on trend analysis
    Xiao, Bing
    Ye, Lenian
    Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science), 1998, 26 (05): : 86 - 89
  • [37] Analysis of data upload mode in intelligent temperature control system based on CAN
    Chen, Haihong
    Wang, Xuefeng
    Wang, Peng
    Dong, Jie
    Gu, Yazhen
    2016 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT HUMAN-MACHINE SYSTEMS AND CYBERNETICS (IHMSC), VOL. 1, 2016, : 239 - 242
  • [38] Intelligent position control for pneumatic servo system based on predictive fuzzy control
    Mu, Shenglin
    Goto, Seigo
    Shibata, Satoru
    Yamamoto, Tomonori
    COMPUTERS & ELECTRICAL ENGINEERING, 2019, 75 : 112 - 122
  • [39] The Research of Intelligent Vehicle's Steering Control System Based on Fuzzy Control
    Liu, Qingqian
    Wang, Bo
    Ma, Xiaowei
    2012 IEEE FIFTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI), 2012, : 474 - 478
  • [40] Intelligent Daylight Panel Control System based on Fuzzy Control for Green Buildings
    Kuo, T. C.
    Lin, J. S.
    Takeuchi, Y.
    Huang, Y. J.
    WORLD CONGRESS ON ENGINEERING 2009, VOLS I AND II, 2009, : 357 - +