基于lorawan的城市树木健康监测环境传感器系统

Haokai Zhao, Kevin A. Kam, I. Kymissis, P. Culligan
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摘要

作为城市生态系统的重要组成部分,树木提供了许多环境、社会和经济效益。为了更好地了解微气候对树木健康和生长的影响,研究人员在哥伦比亚大学晨边校区的一棵椴树上开发了一个基于lorawan的环境传感器系统,该系统由土壤温度传感器、土壤湿度传感器和空气温湿度传感器组成,并对其进行了测试,该系统配备了点式树径计,以测量树干的径向生长。LoRa技术的使用使系统能够以低功耗运行,并在远距离与互联网连接的网关进行无线通信。网关覆盖整个校园480米× 260米区域,平均接收信号强度指标(RSSI)在-120.0 ~ -83.0dBm之间。在9天的试验期内收集了系统的生态和气候数据。结果表明,气温与空气湿度呈高度负相关,Pearson相关系数r=-0.65, P<0.0001。土壤温度与空气温度呈交叉相关,滞后时间为390min (6.5hrs), r=0.33, P<0.0001。从树径计中,发现树干的生长速度约为20.53μm/d。树径的逐小时径向变化与空气湿度呈负相关,r=- 0.21, P<0.01。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A LoRaWAN-Based Environmental Sensor System for Urban Tree Health Monitoring
As an important component of the urban ecosystem, trees provide many environmental, social and economic benefits. To help better understand the impact of micro-climate effects on tree health and growth, a LoRaWAN-based environmental sensor system consisting of a soil temperature sensor, a soil moisture sensor, and an air temperature/humidity sensor was developed and tested on Columbia University’s Morningside Campus at the site of a linden tree, which was instrumented with a point dendrometer in order to measure the tree trunk’s radial growth. The use of LoRa technology enabled the system to operate with low-power and to wirelessly communicate with the internet-connected gateway at long distances. The gateway’s coverage was established throughout the entire 480m × 260m area of the campus, with an average received signal strength indicator (RSSI) between -120.0 and -83.0dBm. Ecological and climate data were collected over a 9-day test period of the system. The results show that the air temperature and the air humidity were highly negatively correlated, with a Pearson’s correlation coefficient r=-0.65, P<0.0001. Additionally, the soil and air temperatures were found to be cross correlated, with a time lag of 390mins (or 6.5hrs), and with r=0.33, P<0.0001. From the dendrometer, the tree trunk was found to grow at a rate of about 20.53μm/day. The hourly radial change of the tree diameter was found to be negatively correlated with the air humidity, with r=- 0.21, P<0.01.
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