Unified Fire Protection Units and System-UFPUS

The main scope of the invention is to provide an Artificial Intelligence system and method for fire identification and extinguishing in real time, by combining and embodying existing tools, technology systems and products puzzle referred to as an innovation algorithm. This technology in the future should serve to protect the planet from natural fire emergencies and is ready to be test first in Albania by developing a pilot testing area/zone in one of our national forest parks in the country.
Technology validated in relevant environment.
Fidelity of breadboard technology increases significantly. The basic technological components are integrated with reasonably realistic supporting elements so they can be tested in a simulated environment. Examples include “high-fidelity” laboratory integration of components.
After we concluded on the AI theoretical model, we achieved its code implementation (a prototype), and because we are lacking a NRT fire map feed, we tried to simulate it by using conventional methods of online maps. Furthermore, on the hardware side, we have achieved to operate the drone programmatically (with computer code), thus the AI system is able to automatically give coordinates to the drone (or also known as Planning a flight route). Below is a list of our main achievements until now, regarding the software and hardware communication side: • AI theoretic model • AI implementation of the model (software prototype) • AI simulations, feedback and calibration of the model • AI notification system for personnel • Software communication with drones • Programmatical plan of drone flight path from AI. With further effort, we plan for the AI system to also be able to command the drones to drop the fire-extinguishing materials on the fire, once the drone has arrived at the coordinates, as one of our main goals is to make the whole system automatic. Note that the drones, once arrive to the fire location, they don’t need any more guidance from the satellite, as they are able to “see” it by themselves. Again, this is how we design to complete our AI model and system to automatically coordinate the drone to drop the material exactly on the fire source.

How does it work?

We intend to make use of an existing satellite technology, which provides NRT (Near-Real-Time) map feed with information about fires on the terrain. These satellites, technologically speaking, are able to detect and reflect fires on the map with red-dots. Now this is where comes the AI model that we designed, which, provided a real-time map feed, is able to detect little red-dots on the map as fire by itself, with no need to be supervised by human factor. After it has identified the fire/s, it notifies for its finding/s and provides the drone with coordinates for it to follow. The AI system, provided a near-real-time fire feed map, is able to scan, identify and automatically coordinate drones with the location of the fires.

January, 2019
- URL path renamed - Web link restored by Sergio Contreras (WP3 leader)