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.
Highlights
IntroductionA modern agricultural management strategy and operational technology system based on spatial information management and mutation analysis, is of great significance for improving the efficiency of utilization of agricultural resources and ensuring sustainable agricultural development
In view of the complex and changeable wireless environment in the precision agriculture systems, this paper proposes a novel energy-efficient networking algorithm by dynamically adjusting the network architecture and the signal transmitting power of each node based on the particle swarm optimization (PSO) algorithm, which fully considers the residual energy variation of nodes during communication
This study presents an energy-saving networking algorithm for a precision agriculture system that combines the characteristics of the wireless sensor devices and the advantages of the particle swarm optimization technique
Summary
A modern agricultural management strategy and operational technology system based on spatial information management and mutation analysis, is of great significance for improving the efficiency of utilization of agricultural resources and ensuring sustainable agricultural development. In view of the complex and changeable wireless environment in the precision agriculture systems, this paper proposes a novel energy-efficient networking algorithm by dynamically adjusting the network architecture and the signal transmitting power of each node based on the particle swarm optimization (PSO) algorithm, which fully considers the residual energy variation of nodes during communication. In the precision agriculture system for ginseng cultivation in a farm field, the influence of the cristate leaf on the transmission of wireless signals should not be ignored during its growing process due to the diversity of the collection parameters such as light, soil moisture, and pH value, and the deployment of sensors at different heights. This study presents an energy-saving networking algorithm for a precision agriculture system that combines the characteristics of the wireless sensor devices and the advantages of the particle swarm optimization technique
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