Algorithm for wireless sensor networks in ginseng field in precision agriculture

PLoS One. 2022 Feb 7;17(2):e0263401. doi: 10.1371/journal.pone.0263401. eCollection 2022.

Abstract

In the research on energy-efficient networking methods for precision agriculture, a hot topic is the energy issue of sensing nodes for individual wireless sensor networks. The sensing nodes of the wireless sensor network should be enabled to provide better services with limited energy to support wide-range and multi-scenario acquisition and transmission of three-dimensional crop information. Further, the life cycle of the sensing nodes should be maximized under limited energy. The transmission direction and node power consumption are considered, and the forward and high-energy nodes are selected as the preferred cluster heads or data-forwarding nodes. Taking the cropland cultivation of ginseng as the background, we put forward a particle swarm optimization-based networking algorithm for wireless sensor networks with excellent performance. This algorithm can be used for precision agriculture and achieve optimal equipment configuration in a network under limited energy, while ensuring reliable communication in the network. The node scale is configured as 50 to 300 nodes in the range of 500 × 500 m2, and simulated testing is conducted with the LEACH, BCDCP, and ECHERP routing protocols. Compared with the existing LEACH, BCDCP, and ECHERP routing protocols, the proposed networking method can achieve the network lifetime prolongation and mitigate the decreased degree and decreasing trend of the distance between the sensing nodes and center nodes of the sensor network, which results in a longer network life cycle and stronger environment suitability. It is an effective method that improves the sensing node lifetime for a wireless sensor network applied to cropland cultivation of ginseng.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agriculture* / instrumentation
  • Agriculture* / methods
  • Agriculture* / organization & administration
  • Algorithms*
  • Biosensing Techniques / instrumentation
  • Biosensing Techniques / methods
  • China
  • Computer Communication Networks* / instrumentation
  • Computer Communication Networks* / organization & administration
  • Computer Simulation
  • Crops, Agricultural / growth & development
  • Data Collection / instrumentation
  • Data Collection / methods
  • Humans
  • Panax / growth & development*
  • Wireless Technology / instrumentation
  • Wireless Technology / organization & administration

Grants and funding

This work was supported by the National Natural Science Foundation of China (Project No. 60972127, 61072111 and 60672156) and the Key Scientific Research Project of Jilin Provincial Department of Education (Project No. JJKH20220390KJ) and Key Project of Jilin Provincial Science and Technology Department (Project No. 20100503) and the Project for Science and Technology Center and Science and Technology Service Platform (Project No. 20180623004TC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.