Exposit team has developed an information network designed to collect and spread information for analysis and warning about forest fires.

The solution consists of the following components:

• The network itself; a blockchain network to store the history of fire notifications;
  
• A NASA analytics module to supply data to the network (NodeJS application to process NASA data and send information on the global state of affairs regarding fires);
  
• A Facebook chat bot fulfilling 2 functions:
  
• Fire notifications;
  
• Gathering of messages and photographic materials from eyewitnesses;
  
• A module to analyze the photographic materials obtained by the chatbot (Java application that carries out filtration of photographs that are posted by the users to the chat bot. Integration with the chat bot is done in order to obtain eyewitness photos, and the Google Vision service in order to detect forest fires via photographs with a certain degree of probability);
  
• A website with the visualization of active forest fires (Angular 2.0 web-application for the fire data visualization by means of an interactive map (Cesium open source framework) provides an interface familiar to users of Google Maps with additional interactivity (3D, 2.5D, 2D)).
  

The main component of the system is a distributed network based on blockchain technology with the possibility of connecting an unlimited number of new elements, each of which has a verified SSL certificate. The network performs the functions of aggregation, accumulation and exchange of data and notifications.

Why blockchain?

• Distribution – there is no need for centralized storage and a source of notifications. This, in turn, ensures good scalability and stable working capacity;
  
• Permanence of the notification history within the network, an idea within the idea itself
  
• Verification of new data is carried out taking into account the encryption results of the previous data. This allows avoiding data loss and tampering. If necessary, it’s possible to locate the source of misinformation, even if measures have been taken to cover one’s tracks.