Genetic programming (GP) is an evolutionary algorithm used to produce high-quality solutions to various problems. It has seen few claims in circuitry and the development of antenna designs. The application of GP in the model of embedded digital systems on multi-channel antenna arrays of subsurface imaging equipment has not yet been investigated. This study focuses on designing and developing a digital multimeter embedded with a multigene genetic programming (MGGP) model for multi-array transmitter antenna used for subsurface imaging operating at a low frequency of 3.5 kHz to 18.5 kHz using Arduino microcontroller for prototyping. The electrical outputs of a transmitter antenna system employed in a subsurface imaging device require live measurement and monitoring during operation for data logging purposes. The amount of transmitted voltage, produced current, and operating frequency are significant parameters for mapping the underground resistivity, thus the produced GP models are functions of the three parameters. GP fitness function was determined through MATLAB software. The output current signal from the transmitter were imitated in Proteus simulation software using a current source in the designed current measuring circuit. This produced linear and nonlinear relationships of the electrical outputs where GP modeling was beneficially applied. The application of GP in with the microcontroller provided an accurate reading of frequency, current and voltage produced by the multi-array transmitter antenna. These measurements were displayed using LM016L LCD display. Moreover, this embedded digital multimeter on transmitter antenna avoids utilizing costly high voltage measuring devices.

Electrical resistivity tomography (ERT) has been seen as an appropriate instrument in several works to monitor and aid in the control of seawater intrusion (SWI) in coastal groundwater systems. This study seeks to discuss the synthesis of a digital twin that couples information between the physical space through ERT as a monitoring sensor and the digital space using SWI simulations to accurately model the behavior of SWI in the present and future settings. To showcase the concept, a Python-based simulation was presented that shows (a) the joint forward modeling-simulation scheme for calculating expected ERT apparent resistivity values from simulated SWI and (b) the calibration of the digital coastal aquifer system through genetic algorithm to accurately match the outputs of the SWI simulations with the ERT measurements.