LoRa物联网设计及其甘蔗生物量预测可行性研究
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国家自然科学基金项目(31760342、31760603)和广西科技重大专项(桂科AA18118037)


Design of LoRa IoTs and Its Feasibility on Prediction of Sugarcane Plant Population Biomass
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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15dB,晴天的通信品质比发射功率10、20dB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15dB、晴天条件下RSSI值与通信距离的关系模型,其决定系数R2达到0.9291。

    Abstract:

    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.

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李修华,张云皓,李婉,张木清,黄豪,农梦玲. LoRa物联网设计及其甘蔗生物量预测可行性研究[J].农业机械学报,2019,50(Supp):228-232. LI Xiuhua, ZHANG Yunhao, LI Wan, ZHANG Muqing, HUANG Hao, NONG Mengling. Design of LoRa IoTs and Its Feasibility on Prediction of Sugarcane Plant Population Biomass[J]. Transactions of the Chinese Society for Agricultural Machinery,2019,50(Supp):228-232

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  • 收稿日期:2019-04-21
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  • 在线发布日期: 2019-07-10
  • 出版日期: 2019-07-10