通过使用无人机和水下机器人拯救非洲的淡水湖

F. Mekuria, E. Nigussie, E. Schmitt, A. Gonzalez, Tesfa Tegegne, G. Fettweis
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引用次数: 1

摘要

本文提出了一种利用新兴技术实时监测、预测和控制淡水水体中入侵水葫芦的概念系统架构。拟议中的系统计划作为保护非洲淡水湖的救援工作之一部署。本文中介绍的案例研究和系统基于位于埃塞俄比亚巴希尔达尔市附近的塔纳湖。到目前为止,塔纳湖的救援工作主要集中在手工清除杂草和使用收割机器。随着杂草的入侵每两周翻一番,目前的方法将无法控制杂草的快速入侵,这造成了相当大的社会经济损失。提出的系统架构采用联网水下机器人、空中无人机和其他环境传感器,更好地实时绘制杂草覆盖范围,预测杂草的漂浮路径,并了解湖泊的有利环境条件,以根除入侵杂草。所提出的技术干预的优势不仅在于准确监测和快速清除杂草,还在于便于数据收集,以便更好地了解促进入侵杂草快速侵袭和生长的潜在环境和化学条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rescuing the Fresh Water Lakes of Africa through the Use of Drones and Underwater Robots
In this paper, we present a conceptual system architecture for real-time monitoring, predicting and controlling of invasive water hyacinth in freshwater bodies through the use of emerging technologies. The proposed system is planned to be deployed as one of the rescue efforts to preserve the fresh water lakes of Africa. The case study and the system presented in this paper are based on the Lake Tana, situated near the city of Bahir Dar, in Ethiopia. The rescuing efforts of Lake Tana so far focused on removal of the weed by hand and using harvesting machines. With the weed invasion doubling every two weeks, the current approaches will not be able to control the rapid invasion of the weed, which is causing considerable socioeconomic losses. The proposed system architecture employs networked underwater robots, aerial drones and other environmental sensors for better mapping of the weed coverage in real-time, predicting the floating paths of the weed, and learning the favourable environmental conditions of the lake for eradicating the invasive weed. The advantages of the proposed technical intervention lie not only in accurate monitoring and fast removal of the weed, but also in facilitating data collection for better understanding of the underlying environmental and chemical conditions that facilitate the rapid infestation and growth of the invasive weed.
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