Haokai Zhao, Kevin A. Kam, I. Kymissis, P. Culligan
{"title":"基于lorawan的城市树木健康监测环境传感器系统","authors":"Haokai Zhao, Kevin A. Kam, I. Kymissis, P. Culligan","doi":"10.1109/SENSORS47087.2021.9639788","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":6775,"journal":{"name":"2021 IEEE Sensors","volume":"41 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A LoRaWAN-Based Environmental Sensor System for Urban Tree Health Monitoring\",\"authors\":\"Haokai Zhao, Kevin A. Kam, I. Kymissis, P. Culligan\",\"doi\":\"10.1109/SENSORS47087.2021.9639788\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":6775,\"journal\":{\"name\":\"2021 IEEE Sensors\",\"volume\":\"41 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Sensors\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SENSORS47087.2021.9639788\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Sensors","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SENSORS47087.2021.9639788","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.