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The PyDisaster project uses a master function that extracts GPS location and EXIF data from photos submitted to our Flask application platform, and opens a Google Maps search of the location. This project is geared towards helping FEMA conduct damage assessments in areas effected by natural disasters.
[WIP] Get smart insights, alerts & warnings about predicted natural disasters and take precautions before they arrive to keep family, friends & yourself safe.
Prediction of market premiums for property damage and business interruption insurance products. Added natural hazard data and stacked 3 best models as the final model.
The objective of the project is to predict whether a particular tweet, of which the text (occasionally the keyword and the location as well) is provided, indicates a real disaster or not. We use various NLP techniques and classification models for this purpose and objectively compare these models by means of appropriate evaluation metric.
A Google Trends Sentiment Analysis integrated with FEMA emergency declarations data. I attempt to correlate isolated natural disasters with a change in search patterns for climate change. Emphasis on FL hurricanes and CA wildfires over the past 5 years.
Registro de desaparecidos, proyecto que es una solución a los desastres naturales en Bolivia, es un sistema que trabaja persistencia con archivos, estructura de datos y programación orientada a objetos. Además, contiene una interfaz gráfica para interactuar con el registro el cual está hecho en JavaFx