The development of a system that works similarly to navigation, but moves through different areas in different conditions with problematic or non-existent road infrastructure. Accordingly, the system's routes are designed with the aim of finding the most efficient, fastest and best routing solution.
Based on satellite data (relief data, climate change and weather data, land surface, vegetation and soil data) and using artificial intelligence, the system calculates the optimal recommended and potential route with the highest probability of successfully reaching the chosen destination in the shortest time. The system creates, and evaluates the route according to the manually entered data about the equipment, i.e. - the size of the unit, what kind of equipment is used to move ( tanks, armored vehicles, howitzers, etc.) or to move on foot. If a specific means of transport is used, each type of machinery is assessed in terms of mass and rolling stock (wheels, tracks, etc.). In addition to the type of means of transport and the route, a calculation is made of the resources required, such as the amount of fuel needed to complete a logistically feasible route.
The system evaluates the route to be built according to the geographical situation, based on the satellite data acquired: highlands and lowlands are taken into account in the route design, and the route is planned avoiding swamps and mud, which could cause difficulties in moving. If there is a water (river for example) in the route planning path, the system automatically assesses the most likely narrow and shallow point to cross it for the particular vehicle/movement type. Consequently, if heavy machinery is used as the mode of transport, the system will plan the route to avoid forests, but if on foot it can be used as the shortest route. In parallel with the route created by the system, potential hotspots (areas of land where suspicious/elevated activity has been observed) are also selected according to the level of hazard to be avoided/recommended. The system allows hotspot activity to be analyzed by comparing current data against data from the time when the hotspot activity occurred.