4.4 Article

LoRa-Based WSNs Construction and Low-Power Data Collection Strategy for Wetland Environmental Monitoring

Journal

WIRELESS PERSONAL COMMUNICATIONS
Volume 114, Issue 2, Pages 1533-1555

Publisher

SPRINGER
DOI: 10.1007/s11277-020-07437-5

Keywords

Multi-sensor combination module; Wsns; LoRaWan; Fuzzy comprehensive evaluation; STM32; sx1278

Funding

  1. Hebei Graduate Innovation, Hebei Province, China [CXZZBS201811]
  2. National Natural Science Foundation, China [31801782]
  3. Baoding Science Technology Research and Development Guidance Program, Baoding, Hebei, China [15ZG023]

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The wetland that known as the kidney of the earth is an ecological system with many resources. Monitoring of wetland environment includes the monitoring of water quality, air and soil. The parameters of temperature, pH value, turbidity, dissolved oxygen (DO), water level, conductivity of water, illuminance, PM2.5, harmful gas, and soil moisture is particularly important for the survival of animals in wetland. Real-time monitoring wetland environment is conducive to understanding the causes and trends of environmental change in the whole region, so as to make environmental change emergency strategies timely. The author introduces a real-time monitoring system based on Multi-sensor Combination Module (MSCM) and LoRa. This system has two types of MSCM, one is for water and the other is for air. The MSCM for water consists of six sensors, such as water temperature sensor, pH sensor, turbidity sensor, dissolved oxygen sensor, conductivity sensor, and water level sensor, and stm32 core processor, which has the advantages of low power consumption and high speed. The data collection node uploads the collected data to the base station through a LoRa module with low power consumption, high speed and wide coverage. The base station and the collection node are connected in a star. The LoRaWan protocol is used to realize the communication between acquisition nodes and sink. In the case of code rate is 4/5, bandwidth is 500 kHz and spreading factor is 12, the effective throughput of the system can reach 1172 bps. At the same time, a data fusion algorithm based on fuzzy decision is designed for data processing on the acquisition nodes to reduce the amount of uploaded data, reduce power consumption and improve network throughput. Experiments show that the system has strong stability, flexible networking, low power consumption, long communication distance, and is suitable for wetland environmental monitoring.

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