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Towards a crop pest control system based on the Internet of Things and fuzzy logic

Author

Listed:
  • Xuhui Wang

    (Beijing University of Posts and Telecommunications)

  • Vahid Jannesari

    (Wichita State University)

Abstract

Smart agriculture is an emerging concept that helps modern farm management using technologies such as the Internet of Things (IoT), robotics, drones, and artificial intelligence, so that this leads to an increase in the quantity and quality of farm products and optimization of human resources. Efforts have been made in the past to control pests and plant diseases, and this has led to an increase in agricultural products. Control and prevention of crop diseases is the least expensive method of pest control, which also has good results in reducing insect pests. This study develops a crop pest control system based on IoT technology, which includes two parts: (1) hardware as a plant protection machine, and (2) software as an information management system. Here, light trap technology and ozone sterilization are incorporated in the proposed system to control insect pests and diseases of agricultural crops. The information management system consists of IoT technology and a mobile app, which provides remote control capability. In this system, several IoT-based sensor devices are responsible for collecting environmental information in real time. The basic routing protocol for the system implementation is Open Shortest Path First . We present a fuzzy logic-based method for energy-aware routing. We proved the effectiveness of the proposed system through implementation on a greenhouse facility.

Suggested Citation

  • Xuhui Wang & Vahid Jannesari, 2024. "Towards a crop pest control system based on the Internet of Things and fuzzy logic," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 85(4), pages 665-677, April.
    • Handle: RePEc:spr:telsys:v:85:y:2024:i:4:d:10.1007_s11235-024-01106-9
    DOI: 10.1007/s11235-024-01106-9
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    References listed on IDEAS

    as
    1. Yumeng Cao & Ning Xu & Huanqing Wang & Xudong Zhao & Adil M. Ahmad, 2023. "Neural networks-based adaptive tracking control for full-state constrained switched nonlinear systems with periodic disturbances and actuator saturation," International Journal of Systems Science, Taylor & Francis Journals, vol. 54(14), pages 2689-2704, October.
    2. Wang, Hongzhang & Ren, Hao & Han, Kun & Li, Geng & Zhang, Lihua & Zhao, Yali & Liu, Yuee & He, Qijin & Zhang, Jiwang & Zhao, Bin & Ren, Baizhao & Liu, Peng, 2023. "Improving the net energy and energy utilization efficiency of maize production systems in the North China Plain," Energy, Elsevier, vol. 274(C).
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