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Wireless channel propagation characteristics and models are important to ensure the communication quality of wireless sensor networks in agriculture. Wireless channel attenuation experiments were carried out at different node antenna heights (0.8 m, 1.2 m, 1.6 m, and 2.0 m) in the tillering, jointing, and grain filling stages of rice fields. We studied the path loss variation trends at different transmission distances and analyzed the differences between estimated values and measured values of path loss in a free space model and a two-ray model. Regression analysis of measured path loss values was used to establish a one-slope log-distance model and propose a modified two-slope log-distance model. The attenuation speed in wireless channel propagation in rice fields intensified with rice developmental stage and the transmission range had monotone increases with changes in antenna height. The relative error (RE) of estimation in the free space model and the two-ray model under four heights ranged from 6.48–15.49% and 2.09–13.51%, respectively, and these two models were inadequate for estimating wireless channel path loss in rice fields. The ranges of estimated RE for the one-slope and modified two-slope log-distance models during the three rice developmental stages were 2.40–2.25% and 1.89–1.31%, respectively. The one-slope and modified two-slope log-distance model had better applicability for modeling of wireless channels in rice fields. The estimated RE values for the modified two-slope log-distance model were all less than 2%, which improved the performance of the one-slope log-distance model. This validates that the modified two-slope log-distance model had better applicability in a rice field environment than the other models. These data provide a basis for modeling of sensor network channels and construction of wireless sensor networks in rice fields. Our results will aid in the design of effective rice field WSNs and increase the transmission quality in rice field sensor networks.
Zhenran Gao; Weijing Li; Yan Zhu; Yongchao Tian; Fangrong Pang; Weixing Cao; Jun Ni. Wireless Channel Propagation Characteristics and Modeling Research in Rice Field Sensor Networks. Sensors 2018, 18, 3116 .
AMA StyleZhenran Gao, Weijing Li, Yan Zhu, Yongchao Tian, Fangrong Pang, Weixing Cao, Jun Ni. Wireless Channel Propagation Characteristics and Modeling Research in Rice Field Sensor Networks. Sensors. 2018; 18 (9):3116.
Chicago/Turabian StyleZhenran Gao; Weijing Li; Yan Zhu; Yongchao Tian; Fangrong Pang; Weixing Cao; Jun Ni. 2018. "Wireless Channel Propagation Characteristics and Modeling Research in Rice Field Sensor Networks." Sensors 18, no. 9: 3116.
To meet the demand of intelligent irrigation for accurate moisture sensing in the soil vertical profile, a soil profile moisture sensor was designed based on the principle of high-frequency capacitance. The sensor consists of five groups of sensing probes, a data processor, and some accessory components. Low-resistivity copper rings were used as components of the sensing probes. Composable simulation of the sensor’s sensing probes was carried out using a high-frequency structure simulator. According to the effective radiation range of electric field intensity, width and spacing of copper ring were set to 30 mm and 40 mm, respectively. A parallel resonance circuit of voltage-controlled oscillator and high-frequency inductance-capacitance (LC) was designed for signal frequency division and conditioning. A data processor was used to process moisture-related frequency signals for soil profile moisture sensing. The sensor was able to detect real-time soil moisture at the depths of 20, 30, and 50 cm and conduct online inversion of moisture in the soil layer between 0–100 cm. According to the calibration results, the degree of fitting (R2) between the sensor’s measuring frequency and the volumetric moisture content of soil sample was 0.99 and the relative error of the sensor consistency test was 0–1.17%. Field tests in different loam soils showed that measured soil moisture from our sensor reproduced the observed soil moisture dynamic well, with an R2 of 0.96 and a root mean square error of 0.04. In a sensor accuracy test, the R2 between the measured value of the proposed sensor and that of the Diviner2000 portable soil moisture monitoring system was higher than 0.85, with a relative error smaller than 5%. The R2 between measured values and inversed soil moisture values for other soil layers were consistently higher than 0.8. According to calibration test and field test, this sensor, which features low cost, good operability, and high integration, is qualified for precise agricultural irrigation with stable performance and high accuracy.
Zhenran Gao; Yan Zhu; Cheng Liu; Hongzhou Qian; Weixing Cao; Jun Ni. Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers. Sensors 2018, 18, 1648 .
AMA StyleZhenran Gao, Yan Zhu, Cheng Liu, Hongzhou Qian, Weixing Cao, Jun Ni. Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers. Sensors. 2018; 18 (5):1648.
Chicago/Turabian StyleZhenran Gao; Yan Zhu; Cheng Liu; Hongzhou Qian; Weixing Cao; Jun Ni. 2018. "Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers." Sensors 18, no. 5: 1648.