System and method for adaptive artificial intelligence selection at a reconfigurable metasurface device for optimizing wireless throughput and predictive maintenance

A method of adaptively enhancing a communication system within a wireless network at a reconfigurable metasurface unit cell array comprising:

• receiving, at a hardware metasurface controller, received signal strength indicator (RSSI) data, signal-to-noise-ratio (SINR) data, and metasurface environment operating data wherein the metasurface environment operating data includes data indicating radiofrequency conditions, wireless network conditions for a wireless network operating in the radiofrequency environment, data representing tasks executing on a transmitting wireless network device and a receiving wireless network device, and data representing physical environment conditions relating to placement or use of a wireless network device to operate in the radiofrequency environment;
• executing, via the hardware metasurface controller, machine readable code instructions of an inference engine module to, based on the RSSI data, the SINR data, and metasurface environment operating data, select among a plurality of machine learning algorithms for execution with a radiofrequency performance and power consumption decision module;
• and
• executing, via the hardware metasurface controller, machine readable code instructions of the radiofrequency performance and power consumption decision module with the selected machine learning algorithm to adjust phase shift for radiofrequency signals incident on a surface of one or more metasurface unit cells of the reconfigurable metasurface unit cell array via adjustment to a tunable phase delay circuit in a microwave network of the one or more metasurface unit cells to beamform reflected radiofrequency signals in directionality lobes in a radiofrequency environment, wherein the reconfigurable metasurface unit cell array includes a plurality of metasurface unit cells each having a passive set of concentric antennas formed on a dielectric substrate with a size and spacing between concentric antennas to reflect the EM waves of radiofrequency signals incident on the surface of the reconfigurable metasurface unit cell array and a microwave circuit operatively coupled to the tunable phase delay circuit.

A reconfigurable metasurface unit cell array comprising:

• a hardware metasurface controller, a metasurface memory device, and a metasurface power management unit (PMU) to provide power to the hardware metasurface processor and memory device;
• the reconfigurable metasurface unit cell array to manipulate electromagnetic (EM) waves of radiofrequency signals incident on a surface of the reconfigurable metasurface unit cell array and received within a radiofrequency environment, the reconfigurable metasurface unit cell array including a plurality of metasurface unit cells each having resonating structures formed on a substrate with a size and spacing between resonating structures to reflect the EM waves of the radiofrequency signals and a microwave circuit operatively coupled to a microwave circuit network;
• the hardware metasurface controller to receive received signal strength indicator (RSSI) data, signal-to-noise-ratio (SINR) data, and metasurface environment operating data wherein the metasurface environment operating data includes data indicating radiofrequency conditions, wireless network conditions for a wireless network operating in the radiofrequency environment, data representing tasks executing on a transmitting wireless network device and a receiving wireless network device, and data representing physical environment conditions relating to placement or use of the transmitting wireless network device and the receiving wireless network device to operate in the radiofrequency environment;
• the hardware metasurface controller executing machine readable code instructions of an inference engine module to, based on the RSSI data, the SINR data, and metasurface environment operating data, select among a plurality of machine learning algorithms for execution with a radiofrequency performance and power consumption decision module;
• and
• the hardware metasurface controller executing machine readable code instructions of the radiofrequency performance and power consumption decision module with the selected machine learning algorithm to adjust phase shift of one or more metasurface unit cells of the reconfigurable metasurface unit cell array via adjustment to a tunable phase delay circuit in the microwave network to beamform reflected radiofrequency signals in directionality lobes between the transmitting wireless network device and the receiving wireless network device in the radiofrequency environment.