LoRa物联网设计及其甘蔗生物量预测可行性研究
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摘要
为了充分挖掘物联网的潜力,设计了基于LoRa技术的农田物联网系统,该系统可实现田间环境数据的采集,并进行了田间通信试验。选取空地及两块甘蔗地进行试验,分别获取了不同发射功率、不同通信距离、不同天气状况下的共3 000个接收信号强度指示(Received signal strength indication,RSSI)数据。试验结果表明,在蔗田通信中,发射功率15 dB,晴天的通信品质比发射功率10、20 d B及黎明、出现露水等潮湿条件下更稳定,甘蔗密度明显影响通信品质。建立了发射功率15 dB、晴天条件下RSSI值与通信距离的关系模型,其决定系数R~2达到0. 929 1。
LoRa technology is a low-power LAN wireless standard,which is increasingly used in the agricultural internet of things due to its advantages of low power consumption and long communication distance. LoRa nodes can not only be equipped with sensors for environmental monitoring but also figure out received signal strength indication( RSSI) of each node by checking the quality of received data packets. RSSI value has a strong relationship with signal transmission intensity,communication distance and communication media. A farmland internet of things system was designed and developed based on LoRa technology, and the relationship between LoRa communication quality, transmission power,communication distance and sugarcane plant population density was preliminarily explored,and the feasibility of using RSSI value to predict sugarcane population density was evaluated. In the communication experiment,a total of 3000 RSSI data were collected at 20 different distances in the open field and two sugarcane fields. The results showed that under the transmission power of 15 dB,the communication quality on sunny days was more stable than that of 10 dB,20 dB,rain,dew and other humidity,and the sugarcane density obviously affected the communication quality. The main factors affecting the communication quality in sugarcane field were analyzed based on these data,and the model of LoRa signal strength and communication distance was preliminarily established,the tests showed that its R~2 reached 0. 929 1. The results showed that the system designed can provide important guidance for sugarcane growth monitoring,management and yield prediction.
LoRa technology is a low-power LAN wireless standard,which is increasingly used in the agricultural internet of things due to its advantages of low power consumption and long communication distance. LoRa nodes can not only be equipped with sensors for environmental monitoring but also figure out received signal strength indication( RSSI) of each node by checking the quality of received data packets. RSSI value has a strong relationship with signal transmission intensity,communication distance and communication media. A farmland internet of things system was designed and developed based on LoRa technology, and the relationship between LoRa communication quality, transmission power,communication distance and sugarcane plant population density was preliminarily explored,and the feasibility of using RSSI value to predict sugarcane population density was evaluated. In the communication experiment,a total of 3000 RSSI data were collected at 20 different distances in the open field and two sugarcane fields. The results showed that under the transmission power of 15 dB,the communication quality on sunny days was more stable than that of 10 dB,20 dB,rain,dew and other humidity,and the sugarcane density obviously affected the communication quality. The main factors affecting the communication quality in sugarcane field were analyzed based on these data,and the model of LoRa signal strength and communication distance was preliminarily established,the tests showed that its R~2 reached 0. 929 1. The results showed that the system designed can provide important guidance for sugarcane growth monitoring,management and yield prediction.
引文
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[20]MARDINI W,KHAMAYSEH Y,ALMODAWAR A A,et al.Adaptive RSSI-based localization scheme for wireless sensor networks[J].Peer-to-Peer Networking and Applications,2016,9(6):991-1004.
[21]鄂月胜,王新生,汪全芳,等.湖北省一季稻种植面积遥感监测方法研究[J].湖北大学学报(自然科学版),2012,34(1):116-119.E Yuesheng,WANG Xinsheng,WANG Quanfang,et al.Research on remote sensing monitoring methods of single-crop rice planting area in Hubei Province[J].Journal of Hubei University(Natural Science),2012,34(1):116-119.(in Chinese)
[22]ZHANG Minghua,QIN Zhizhao,LIU Xue,et al.Detection of stress in tomatoes induced by late blight disease in California,USA,using hyperspectral remote sensing[J].International Journal of Applied Earth Observations and Geoinformation,2003,4(4):295-310.
[23]SINDHUIA S,LAV R,CARLOS Z,et al.Low-altitude,high-resolution aerial imaging system for row and field crop phenotyping:a review[J].European Journal of Agronomy,2015,70:112-123.
[2]葛文杰,赵春江.农业物联网研究与应用现状及发展对策研究[J].农业机械学报,2014,45(7):222-230.GE Wenjie,ZHAO Chunjiang.State-of-the-art and developing strategies of agricultural internet of things[J].Transactions of the Chinese Society for Agricultural Machinery,2014,45(7):222-230.(in Chinese)
[3]孙雷.上海农业物联网探索与实践[M].上海:上海科学技术出版社,2015.
[4]政纪业,阮怀军,封文杰,等.农业物联网体系结构与应用领域研究进展[J].中国农业科学,2017,50(4):657-668.ZHENG Jiye,RUAN Huaijun,FENG Wenjie,et al.Agricultural IOT architecture and application model research[J].Scientia Agricultura Sinica,2017,50(4):657-668.(in Chinese)
[5]何勇,聂鹏程,刘飞.农业物联网与传感器研究进展[J].农业机械学报,2013,44(10):216-226.HE Yong,NIE Pengpeng,LIU Fei.Advancement and trend of internet of things in agriculture and sensing instrument[J].Transactions of the Chinese Society for Agricultural Machinery,2013,44(10):216-226.(in Chinese)
[6]AUGUSTIN A,YI J,Cl AUSEN T,et al.A study of LoRa:long range&low power networks for the internet of things[J].Sensors,2016,16(9):1466.
[7]徐松松,周西峰,郭前岗.基于ARM平台的Zig Bee网关设计[J].微型机与应用,2013,32(16):51-53.XU Songsong,ZHOU Xifeng,GUO Qiangang.Design of Zig Bee gateway system based on ARM[J].Microcomputer&Its Applications,2013,32(16):51-53.(in Chinese)
[8]MOHAMED A,AXEL S.Free space range measurements with Semtech LoRa TM technology[C]∥2014 2nd International Symposium on Technology and Applications(IDAACS-SWS).Offenburg,2014:19-23.
[9]LEWARK U,ANTES J,WALHEIM J,et al.Link budget analysis for future E-band gigabit sate communication links[J].CEAS Space Journal,2013,4(1):41-46.
[10]陆游,禹素萍,姜华,等.一种能量可计算的星型无线传感器网络协议[J].天津工业大学学报,2013,32(4):60-65.
[11]肖凌,梁玉莲,杨宇红,等.南宁市甘蔗气候产量预测模型[J].广东农业科学,2013,40(4):174-176,238.XIAO Ling,LIANG Yulian,YANG Yuhong,et al.Sugarcane climatic yield prediction model of Nanning[J].Guangdong Agricultural Sciences,2013,40(4):174-176,238.(in Chinese)
[12]段维兴.广西蔗糖产业发展现状及对策[J].中国糖料,2016,38(1):65-72.
[13]徐立鸿,早明华,蔚瑞华,等.温室无线传感器网络节点发射功率自适应控制算法[J].农业工程学报,2014,30(8):142-148.XU Lihong,ZAO Minghua,WEI Ruihua,et al.Adaptive control algorithms of transmitting power for greenhouse WSN nodes[J].Transactions of the CSAE,2014,30(8):142-148.(in Chinese)
[14]詹杰,刘宏立,刘述刚,等.基于RSSI的动态权重定位算法研究[J].电子学报,2011,39(1):82-88.
[15]马永兵.基于RSSI信号强度定位的夜间采摘作业机器人设计[J].农机化研究,2017,39(1):212-216.
[16]周渝,杨福增,朱海,等.基于WI-FI的麦田无线信道传播性能试验[J].农机化研究,2015,37(2):155-160.
[17]文韬,洪添胜,李震,等.橘园无线传感器网络不同节点部署方式下的射频信号传播试验[J].农业工程学报,2010,26(6):211-215.WEN Tao,HONG Tiansheng,LI Zhen,et al.Test of wireless sensor network radio frequency signal propagation based on different node deployments in citrus orchards[J].Transactions of the CASE,2010,26(6):211-215.(in Chinese)
[18]郭秀明,赵春江,杨信廷,等.苹果园中2.4 GHz无线信道在不同高度的传播特性[J].农业工程学报,2012,28(12):195-200.GUO Xiuming,ZHAO Chunjiang,YANG Xinting,et al.Propagation characteristics of 2.4 GHz wireless channel at different heights in apple orchard[J].Transactions of the CSAE,2012,28(12):195-200.(in Chinese)
[19]岳学军,王叶夫,洪添胜,等.基于信道测试的橘园WSN网络部署试验[J].农业机械学报,2013,44(5):213-218.YUE Xuejun,WANG Yefu,HONG Tiansheng,et al.WSN layout experiment based on radio frequency propagation tests in citrus orchard[J].Transactions of the Chinese Society for Agricultural Machinery,2013,44(5):213-218.(in Chinese)
[20]MARDINI W,KHAMAYSEH Y,ALMODAWAR A A,et al.Adaptive RSSI-based localization scheme for wireless sensor networks[J].Peer-to-Peer Networking and Applications,2016,9(6):991-1004.
[21]鄂月胜,王新生,汪全芳,等.湖北省一季稻种植面积遥感监测方法研究[J].湖北大学学报(自然科学版),2012,34(1):116-119.E Yuesheng,WANG Xinsheng,WANG Quanfang,et al.Research on remote sensing monitoring methods of single-crop rice planting area in Hubei Province[J].Journal of Hubei University(Natural Science),2012,34(1):116-119.(in Chinese)
[22]ZHANG Minghua,QIN Zhizhao,LIU Xue,et al.Detection of stress in tomatoes induced by late blight disease in California,USA,using hyperspectral remote sensing[J].International Journal of Applied Earth Observations and Geoinformation,2003,4(4):295-310.
[23]SINDHUIA S,LAV R,CARLOS Z,et al.Low-altitude,high-resolution aerial imaging system for row and field crop phenotyping:a review[J].European Journal of Agronomy,2015,70:112-123.
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