Impact of Earthquakes based on Satellite Images using IoT and Sensor Networks
2020 International Conference on COMmunication Systems and NETworkS, COMSNETS 2020
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.
cnn, disaster impact index, earthquake, masking, polygon, segmentation
Information Systems and Technology
Sameer Rajput, Amar Ippili, Divya Puraswani, Shubh Johri, Aarathi Nadathur, and Subhankar Dhar. "Impact of Earthquakes based on Satellite Images using IoT and Sensor Networks" 2020 International Conference on COMmunication Systems and NETworkS, COMSNETS 2020 (2020): 551-554. https://doi.org/10.1109/COMSNETS48256.2020.9027380