北苏门答腊气候站基于物联网的数字土壤温度监测系统的设计与开发

Royston Manurung, Tulus Ikhsan Nasution, Syahrul Humaidi, Immanuel Jhonson A. Saragih, Khindi Aufa Hibatullah, M. Situmorang, Yahya Darmawan
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引用次数: 0

摘要

土壤温度是监测和了解气候与土壤生态系统的一个重要参数。它在农业、生态学和地球科学等多个环境方面发挥着重要作用。监测土壤温度对于规划和管理农业及自然资源十分必要。目前,BMKG 对土壤温度的时间观测有限,仅在当地时间 07:55、13:55 和 18:55 进行。这种局限性导致难以进行详细的土壤温度分析。这项研究旨在设计一种可通过互联网访问的数字土壤温度监测设备。使用了 7 个 DS18B20 传感器,深度分别为 0 厘米、2 厘米、5 厘米、10 厘米、20 厘米、50 厘米和 100 厘米,并结合使用 Arduino 系统的 ESP8266 模块。这一设计的实施产生了一个实时土壤温度监测系统,每 10 秒钟更新一次数据。观测数据显示在 20x4 LCD 上,并发送到云端,可在网页 http://monitoringsuhutanah.my.id 上访问。校准结果表明,本研究中使用的 DS18B20 传感器可提供准确一致的温度测量值,平均修正范围为 (-0.20) 至 0.24,因此适合实际使用。现场测试表明,数字数据准确,与传统数据对应(线性相关)。相关值为 0.7,均方根误差范围为 0.5 至 2.18,偏差范围为 (-0.69) 至 0.08。
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Design and Development of A Digital Soil Temperature Monitoring System Based on The Internet of Things at North Sumatra Climatological Station
Soil temperature is a crucial parameter in monitoring and understanding climate and soil ecosystems. It plays a vital role in various environmental aspects, including agriculture, ecology, and geoscience. Monitoring soil temperature is necessary for planning and managing agriculture and natural resources. Currently, temporal observations of soil temperature by BMKG are limited, conducted only at 07:55, 13:55, and 18:55 local time. This limitation makes it difficult to perform detailed soil temperature analysis. This research was conducted to design a digital soil temperature monitoring device accessible via the internet. Seven DS18B20 sensors were used at depths of 0 cm, 2 cm, 5 cm, 10 cm, 20 cm, 50 cm, and 100 cm, combined with an ESP8266 module using the Arduino system. The implementation of this design resulted in a real-time soil temperature monitoring system with data updates every 10 seconds. The observed data are displayed on a 20x4 LCD and sent to the cloud, making them accessible on the webpage http://monitoringsuhutanah.my.id. Calibration results indicate that the DS18B20 sensors used in this study provide accurate and consistent temperature measurements, with an average correction range of (-0.20) to 0.24, thus suitable for operational use. Field tests show that the digital data are accurate and correspond (linearly correlate) with conventional data. This is based on a correlation value of 0.7, while the RMSE values range from 0.5 to 2.18 and the bias ranges from (-0.69) to 0.08.
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