Fig 1.
Proposed power and control system: (a) the PV powering system (b) the decision making control unit details.
Fig 2.
Proposed IoT communication system.
Fig 3.
Single diode equivalent circuit of a solar cell.
Fig 4.
DC/DC boost converter schematic diagram.
Fig 5.
DC/DC bidirectional converter schematic diagram.
Fig 6.
Waveforms of the Bidirectional DC/DC Converter: (a) positive energy flow (b) negative energy flow.
Fig 7.
Pearson correlation coefficients of each input parameter (dIX, dCX, dDX, dVX, SINRth, PI) and the output (Pint and EE).
Fig 8.
Proposed deep learning model.
Fig 9.
Steady-State Simulation Performance at 1000 W/m2 (a) Conventional P&O Algorithm, (b) Proposed SF Algorithm.
Fig 10.
Transient Simulation Performance at 800W/m2 and 400W/m2 (a) Conventional P&O Algorithm, (b) Proposed SF Algorithm.
Table 1.
PV panel specifications.
Table 2.
Parameters of DC/DC boost converter.
Fig 11.
Smart traffic system simulation by any logic program.
Fig 12.
Smart traffic system simulation by any logic program.
Fig 13.
MATLAB Simulink for a standard vehicle.
Fig 14.
Fuel Economy by MATLAB Simulink.
Fig 15.
Statistics of any logic simulation.
Fig 16.
Curves of petrol used based on statistical data.
Fig 17.
Training and validation mean absolute error generated during training the proposed model.
Fig 18.
Maximum required SINRth vs Maximum required interference power.
Fig 19.
Maximum required SINRth vs maximum energy efficiency (EE).
Fig 20.
Maximum IoT transmission power vs maximum energy efficiency (EE).