Development of a wireless communication system for monitoring crop condition with leaf wetness sensor
Abstract
Abstract: Wireless sensor networks play an essential role in smart agriculture, especially on the future farms without farmers. This paper presents a new wireless communication system (WCS) for crop leaf wetness monitoring using a nRF905 wireless transmit module together with a STM32 controller, a data acquisition board and developed software. The further developed nRF905 wireless module was used to transmit crop canopy leaf wetness data collected by LWS (Leaf Wetness Sensor) in the field to the monitoring central station. A simple graphical user interface has been developed and implemented to display crop canopy moisture by LWS. The WCS was tested and validated in LabVIEW2013. The 3-day time series model of wetness was built based on the data collected by the monitoring system. In this paper, the structure of this system was introduced, and the system performance evaluation in field was described. The results show that the wireless system has promise to have a higher accuracy for crop canopy leaf wetness monitoring and application which will improve the efficiency of smart agriculture application.
Keywords: wireless communication system, nRF905, leaf wetness sensor, crop condition, canopy moisture, smart agriculture
DOI:Â 10.33440/j.ijpaa.20200301.68
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Citation: Zhu H, Li H Z, Lan Y B.  Development of a wireless communication system for monitoring crop condition with leaf wetness sensor.  Int J Precis Agric Aviat, 2020; 3(1): 54–58.
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Yemeserach M, Srikanth N, Lamar B, et al. Review—Machine learning techniques in wireless sensor network based precision agriculture. Journal of the Electrochemical Society, 2020, 167(037522). doi: 10.1149/2.0222003JES
Tracy R, Mark G, Paulo S, et al. Reconsidering leaf wetness duration determination for plant disease management. Plant Disease, 2015, 99(03): 310-319. doi: 10.1094/ PDIS-05-14-0529-FE
Simone B, Marcello D, Roberto C, et al. Multi metric evaluation of leaf wetness models for large-area application of plant disease models. Agricultural and Forest Meteorology, 2011, 151: 1163–1172. doi: 10.1016/j.agrformet.2011.04.003
Gemma H, Jorge E. Gaitán-Pitre, Ernesto Serrano-Finetti, et al. A novel low-cost smart leaf wetness sensor. Computers and Electronics in Agriculture, 2017, 11(1): 1–8. doi: 10.1016/j. compag. 2017.11.001
Guan W, Wang C, Cai Y, et al. Design and implementation of wireless monitoring network for temperature-humidity measurement. J Ambient Intel Human Computer, 2016, 7: 131–138. doi: 10.1007/s12652-015-0314-7
Hong W, Qing L, Hui L, et al. Based on the LabVIEW frequency modulation continuous wave radar signal acquisition and processing. Advanced Materials Research, 2012, 542–543: 818–821. doi: 10.4028/www.scientific.net/AMR.542-543.818
Park D. H., Kang B. J., Cho K. R., et al. A Study on Greenhouse
Automatic Control System Based on Wireless Sensor Network. Wireless Pers Commun, 2011(56): 117–130. doi: 10.1007/s11277-009-9881-2
Wang, Q. Wireless Transmission Network Application System Design in Mine Pressure Monitoring of Coal Face. Third International Symposium on Intelligent Information Technology Application, 2009. doi: 10.1109/IITA.2009.399
Son J, Shin W, Cho J. Laboratory and Field Assessment of the Decagon 5TE and GS3 Sensors for Estimating Soil Water Content in Saline-Alkali Reclaimed Soils. Communications in Soil Science and Plant Analysis, 2017,48: 2268–2279. doi: 10.1080/00103624.2017.1411501
Fernando V, Jose M, Delfina M, et al. Laboratory and field assessment of the capacitance sensors Decagon 10HS and 5TE for estimating the water content of irrigated soils. Agricultural Water Management, 2014, 132(31). doi: 10.1016/j.agwat.2013.10.005
Divyansh T, Yuga lK, Arvind K, et al. Applicability of Wireless Sensor Networks in Precision Agriculture: A Review. Wireless Personal Communications, 2019, 107: 471–512. doi: 10.1007/s11277-019-06285-2
Zhuang L, Chen H. Design of a Synchronous Control System for Mobile Lift Based on Wireless Network. Journal of Physics: Conference Series, 2019, 1267: 012051. doi: 10.1088/1742-6596/1267/1/012051
Huang J, Liu D, Yuan Y. An Anthurium Growth Environment Monitoring System Based on Wireless Sensor Network. International Journal of Online Engineering, 2019, 15(5): 69–85. doi:10.3991/ ijoe.v15i05.9382
Katja E, Lin H, Joachim B, et al. Comparison of wetness sensors and the development of a new sensor for apple scab prognosis. Journal of Plant Diseases and Protection, 2019, 126: 429–436. doi: 10.1007/ s41348-019-00239-3
Liu G, Mao L. The Wireless Communication System Based on NRF905. Advances in Engineering and Automation, 2012, 139: 87–91. doi: 10.1007/978-3-642-27951-5_13
Yang W, Qiao S, Song Q, et al. The design and implementation of wireless temperature and humidity control system based on nRF905. 2015 IEEE 10th Conference on Industrial Electronics and Applications, 2015. doi: 10.1109/ICIEA.2015.7334209
Zhuang L, Chen H. Design of a Synchronous Control System for Mobile Lift Based on Wireless Network. Journal of Physics: Conference Series, 2019, 1267: 012051. doi: 10.1088/1742-6596/1267/1/012051
Wagner T, Marcelo A, Jose A, et al. Estimation of soybean leaf wetness from meteorological variables. Pesq. Agropec. Bras., 2018, 53(10): 1087–1092. doi: 10.1590/S0100-204X2018001000001
Paulo C.S., Terry J.G., Eduardo A.S. Leaf wetness duration measurement: comparison of cylindrical and flat plate sensors under different field conditions. Int J Biometeorology, 2007, 51: 265–273. doi: 10.1007/ s00484-006-0070-7
Alexandru L, Anders K, Merete E. Volatile organic compounds as markers of quality changes during the storage of wild rocket. Food Chemistry, 2017, 232: 579–586. doi: 10.1016/j.foodchem.2017.04.035
Ehlert K, Himmelmann L, Beinhorn J. Comparison of wetness sensors and the development of a new sensor for apple scab prognosis. Journal of Plant diseases and protection, 2019, 126(5): 429–436. doi: 10.1007/ s41348-019-00239-3
Sharanya S, Saipushpita V, Anand P. Real time control data for styrene acrylonitrile copolymerization system in a batch reactor for the optimization of molecular weight. Data in brief, 2020, 28(104878). doi: 10.1016/j.dib.2019.104878
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