This project consists in a PWA (Progressive Web Application) developed in Python Flask. It allows to monitor and geo-localizaze the parameters of some (simulated) sensor stations distributed along a forest area. This parameters include temperature, humidity and so on. It also displays (simulated) warnings of possible fires using Deep Learning image processing technologies such as Tensorflow and Keras. We also performed a small study about the costs of deploying this system (both physical and cloud costs).

A progressive web application works like a traditional web application but, through the use of service workers, it has the ability to run like a normal native application. This type of application allows the use of its functionalities even without having an internet connection. For this, when the application is loaded, the service worker is responsible for creating the cache and saving the files necessary for its offline operation. Another key point of these applications is the manifest, which is basically a file in json format that stores relevant data for the application, such as the application icon or the name. The only requirement to implement this type of application is the use of https connections.

IoT & Protocols. PWA. Big Data. Cloud Computing. Deep Learning & Computer Vision.