Impact of Earthquakes based on Satellite Images using IoT and Sensor Networks

Sameer. N. Rajput, Amar Ippili, Divya Puraswani, Shubh Johri, A. Nadathur, Subhankar Dhar
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引用次数: 3

Abstract

Technological advancements of studying images, acquired from satellites can play an important role in knowing the impact of disasters, which affects humanity in several ways. We propose an integrated framework for earthquake management helping in mitigating, preparing, responding and recovering from disasters using IoT, sensor networks and deep learning models. Our model will be built upon previous research by considering the impact of destruction, which will assist in relief efforts, rescue operations, and disaster responses. The framework will start with collecting data from publicly available sources, followed by data scrubbing, exploring, featuring and modeling using deep learning semantic-based CNN models. Various performance measures like confusion matrix will be used to evaluate our model. Data visualization will be done using Python and Tableau. Our model will quantify the impact of earthquakes using images collected pre and post-earthquake, focusing on building destruction. The results of our analysis will help humanity to measure and monitor the impact of disaster by using data science tools and techniques.
基于使用物联网和传感器网络的卫星图像的地震影响
研究从卫星获得的图像的技术进步可以在了解灾害的影响方面发挥重要作用,灾害在几个方面影响人类。我们提出了一个集成的地震管理框架,利用物联网、传感器网络和深度学习模型,帮助减轻、准备、响应和从灾害中恢复。我们的模型将建立在先前研究的基础上,考虑破坏的影响,这将有助于救灾工作、救援行动和灾难反应。该框架将从公开来源收集数据开始,然后使用基于深度学习语义的CNN模型进行数据清洗、探索、特征和建模。各种性能指标,如混淆矩阵将被用来评估我们的模型。数据可视化将使用Python和Tableau完成。我们的模型将使用地震前和地震后收集的图像来量化地震的影响,重点是建筑物的破坏。我们的分析结果将帮助人类通过使用数据科学工具和技术来衡量和监测灾害的影响。
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