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 fireextinguishing 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.