为减灾实施物联网和机器学习

Nur Laily, Muktar Redy Susila, Juwita Sari, Pontjo Bambang Mahargiono
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引用次数: 0

摘要

该原型输出研究旨在创建一个用于监测河流水位的仪表盘。创建的仪表盘将实时显示数据和预测结果。该仪表盘的用途是在河水泛滥造成洪水泛滥时将风险降至最低。该原型的工作方式是从安装在多个点的传感器中获取数据。记录的数据将利用物联网的工作原理存储在数据库中。在预测方面,将使用机器学习来生成未来的河水水位数据。机器学习使用的是时间序列回归法,输入为降雨量,输出为河水水位。由于需要长期的输出数据,因此采用了混合法来预测未来的降雨量。传感器生成的数据和预测结果都存储在一个数据库中。从数据库中可视化显示数据以及用于河流溢流情报的重要数据。因此,该仪表盘对生活在河流周围的人们非常有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IMPLEMENTING IOT AND MACHINE LEARNING FOR DISASTER MITIGATION
This prototype output research has the aim of creating a dashboard that is used to monitor river water levels. The dashboard created will display data in real-time and prediction results. The use of the dashboard is to minimize the risk in the event of flooding caused by river overflow. The way this prototype works is to take data from sensors that have been installed at several points. The recorded data will be stored in a database using the working principles of the Internet of Things. For predictions, machine learning is used to produce future river water level figures. The machine learning used is using time series regression with rainfall input and river water level output. Long-term output data is needed, therefore to forecast future rainfall the Hybrid method is used. Data generated from sensors as well as from prediction results are stored in one database. From the database, data visualization is displayed along with important figures used for river overflow intelligence. Therefore, the dashboard is very useful for people living around the river flow.
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