IGSS It is a powerful simulation software designed to generate received signals from a variety of simulated scenarios, allowing for the labeling and saving of the resulting data.
These labeled signals can be used for machine learning (ML) training, enabling the development of intelligent algorithms capable of recognizing and interpreting signals from ground-penetrating radar (GPR) systems.
IGSS provides a graphical user interface (GUI) for setting up simulations and visualizing the results. It can simulate a variety of GPR scenarios, including changes in subsurface materials, ground conditions, and electromagnetic wave propagation characteristics. The resulting data from IGSS can be saved and labeled, making it useful for training machine learning algorithms.
IGSS is particularly useful for developing intelligent GPR systems capable of detecting and interpreting signals from subsurface structures or materials. By using the labeled data generated by IGSS, ML algorithms can be trained to recognize patterns in GPR signals and interpret them to identify the presence and characteristics of subsurface materials.
In order to use IGSS, users need to have Python 3.6 or higher installed, as well as a number of additional packages including gprMax, NumPy, Matplotlib, and Scikit-learn. The software is compatible with computers that have at least 8GB of RAM.
Overall, IGSS is an essential tool for anyone working in the field of GPR. With its powerful simulation capabilities and ability to generate labeled data for machine learning, IGSS provides users with a powerful and flexible platform for developing intelligent GPR systems. Whether you are working in academia or industry, IGSS can help you to gain new insights into subsurface structures and materials, and to develop cutting-edge technology for detecting and interpreting GPR signals.
Requirements IGSS requires the following software and hardware:
Python 3.6 or higher gprMax (https://github.com/gprMax/gprMax)
NumPy (http://www.numpy.org/)
Matplotlib (https://matplotlib.org/)
Scikit-learn (https://scikit-learn.org/)
A computer with at least 8GB of RAM
To install IGSS, follow these steps:
Clone or download the IGSS repository. Install gprMax, NumPy, Matplotlib, and Scikit-learn using pip
pip install gprMax numpy matplotlib scikit-learn
python igss.py
Usage To use IGSS, follow these steps:
1: Launch the IGSS GUI by running the igss.py scrip
python igss.py
2:Use the GUI to set up your GPR simulation scenario. 3:Run the simulation and generate the received signal. 4:Save the received signal and its corresponding label. 5:Repeat steps 2-4 for additional simulation scenarios. 6:Use the saved received signals and labels for ML training.
Contributing If you find any issues or have suggestions for new features, please open an issue or submit a pull request on the IGSS GitHub repository.