An ultra-low-power sediment concentration detecting system in runoff based on LoRa networking

YANG Pengcheng, LIU Yanyi, CHEN Shuchang, SHEN Yicong, SONG Chenyue

JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2025, Vol. 49 ›› Issue (2) : 161-168.

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南京林业大学学报（自然科学版）
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JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2025, Vol. 49 ›› Issue (2) : 161-168. DOI: 10.12302/j.issn.1000-2006.202304039

An ultra-low-power sediment concentration detecting system in runoff based on LoRa networking

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Abstract

【Objective】Soil erosion represents a critical issue in China. It is necessary to quantitatively evaluate soil erosion and the benefits of soil conservation, and to understand the situation of soil erosion and the effectiveness of treatment measures. This study involves effectively and reliably detecting the soil erosion status and providing a dependable data foundation for researchers. 【Method】The study used an internet of things (IoT) architecture to design an ultra-low-power sediment concentration detection system in runoff based on long range radio (LoRa) networking. The Standby-CAD with LoRa was employed to achieve ultra-low power consumption. 【Result】This system reduced energy consumption by 40% and increased standby time by 8.5 times compared to traditional techniques. The ECharts framework and Huawei cloud platform were utilized to design a visualization screen for data visualization. Through multiple tests, the average value of the relative error of data measured by this system was 3.08% compared to the traditional gravity method. 【Conclusion】This system can continuously detect the runoff sediment concentration and also rainfall in runoff plots on hillsides in real-time. Compared to traditional IoT technical solutions, this system demonstrates low power consumption, high testing accuracy, data visualization, and also reduced production and maintenance costs, providing accurate and effective measurement data and solutions for related production and research activities.

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sediment concentration detection / ultra-low power consumption / long rang radio (LoRa) / runofff

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YANG Pengcheng , LIU Yanyi , CHEN Shuchang , et al . An ultra-low-power sediment concentration detecting system in runoff based on LoRa networking[J]. JOURNAL OF NANJING FORESTRY UNIVERSITY. 2025, 49(2): 161-168 https://doi.org/10.12302/j.issn.1000-2006.202304039

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