Intelligent wireless network design system

A method, comprising:

• acquiring, by a design server node, aerial surveillance data of a target area from an unmanned aircraft system (UAS) flying over the target area;
• parsing, by the design server node, the aerial surveillance data to derive an at least one feature vector;
• providing, by the design server node, the at least one feature vector to a machine learning (ML) module residing on the at least one cloud server node for generating a predictive model of a wireless network for the target area;
• receiving, by the design server node, a plurality of outputs of the predictive model;
• generating a wireless network design for the target area based on the plurality of the predictive outputs;
• and
• configuring the ML module to codify deterministic base relationships characterizing known profiles and behaviors of radio frequency (RF) and other electronic elements to be used in the wireless network design for the target area.

A non-transitory computer readable medium comprising instructions, that when read by a processor, cause the processor to perform:

• acquiring aerial surveillance data of a target area from an unmanned aircraft system (UAS) flying over the target area;
• parsing the aerial surveillance data to derive an at least one feature vector;
• providing the at least one feature vector to a machine learning (ML) module residing on the at least one cloud server node for generating a predictive model of a wireless network for the target area;
• receiving a plurality of outputs of the predictive model;
• generating a wireless network design for the target area based on the plurality of the predictive outputs;
• and
• configuring the ML module to codify deterministic base relationships characterizing known profiles and behaviors of radio frequency (RF) and other electronic elements to be used in the wireless network design for the target area.