The main idea was to develop a multiplatform web application to allow users to upload possible new wildfires, which would then be analyzed by a machine learning protocol via IBM's Watson, so that such a claim could be confirmed and later on added onto the main database.
Our main pitch proposed to add further functionality by allowing users to click on already existing fires (represented in the world map by red dots), which would then open a small dialog window with a small resume of images taken in the surrounding area, and a comment section where users would be able to add additional feedback.
Finally, the project consists of a Laravel backend app, connected to a MySQL instance, that feeds an API to a frontend app developed in Vue.js. The web app is completely multiplatform and responsive, and, if given enough time, could be added to a Docker image, and possibly deployed later to a Kubernetes cluster for greater scalability and load balance.
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