Suppr超能文献

低成本、基于LoRa的河流水位数据采集系统。

Low cost, LoRa based river water level data acquisition system.

作者信息

Kabi Jason N, Wa Maina Ciira, Mharakurwa Edwell T, Mathenge Stephen W

机构信息

Centre for Data Science and Artificial Intelligence, Dedan Kimathi University of Technology. P.O. BOX, PRIVATE BAG, 10143, Dedan Kimathi, Nyeri, Kenya.

Department of Electrical and Electronic Engineering, Dedan Kimathi University of Technology. P.O. BOX, PRIVATE BAG, 10143, Dedan Kimathi, Nyeri, Kenya.

出版信息

HardwareX. 2023 Mar 17;14:e00414. doi: 10.1016/j.ohx.2023.e00414. eCollection 2023 Jun.

Abstract

In recent years, climate change and catchment degradation have negatively affected stage patterns in rivers which in turn have affected the availability of enough water for various ecosystems. To realize and quantify the effects of climate change and catchment degradation on rivers, water level monitoring is essential. Various effective infrastructures for river water level monitoring that have been developed and deployed in developing countries over the years, are often bulky, complex and expensive to build and maintain. Additionally, most are not equipped with communication hardware components which can enable wireless data transmission. This paper presents a river water level data acquisition system that improves on the effectiveness, size, deployment design and data transmission capabilities of systems being utilized. The main component of the system is a river water level sensor node. The node is based on the MultiTech mDot - an ARM-Mbed programmable, low power RF module - interfaced with an ultrasonic sensor for data acquisition. The data is transmitted via LoRaWAN and stored on servers. The quality of the stored raw data is controlled using various outlier detection and prediction machine learning models. Simplified firmware and easy to connect hardware make the sensor node design easy to develop. The developed sensor nodes were deployed along River Muringato in Nyeri, Kenya for a period of 18 months for continuous data collection. The results obtained showed that the developed system can practically and accurately obtain data that can be useful for analysis of river catchment areas.

摘要

近年来,气候变化和集水区退化对河流的水位模式产生了负面影响,进而影响了各种生态系统获得充足水源的情况。为了认识和量化气候变化和集水区退化对河流的影响,水位监测至关重要。多年来在发展中国家开发和部署的各种有效的河流水位监测基础设施,往往体积庞大、结构复杂,建设和维护成本高昂。此外,大多数都没有配备能够实现无线数据传输的通信硬件组件。本文介绍了一种河流水位数据采集系统,该系统在现有系统的有效性、尺寸、部署设计和数据传输能力方面有所改进。该系统的主要组件是一个河流水位传感器节点。该节点基于MultiTech mDot——一种ARM-Mbed可编程、低功耗射频模块——与一个超声波传感器相连以进行数据采集。数据通过LoRaWAN传输并存储在服务器上。使用各种异常值检测和预测机器学习模型来控制所存储的原始数据的质量。简化的固件和易于连接的硬件使传感器节点设计易于开发。所开发的传感器节点部署在肯尼亚涅里的穆林加托河沿岸,持续采集了18个月的数据。所获得的结果表明,所开发的系统能够切实准确地获取对河流集水区分析有用的数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9058/10050633/a97e6b258665/ga1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验