Enhancing the Accuracy of Wi-Fi Tomographic Imaging Using a Human-Interference Model

Since the reconstruction process of Wi-Fi Tomographic imaging is an ill-posed inverse problem and due to the unstable nature of the measurements, converting the signal strength measurements into a two dimensional image is computationally expensive. Therefore this research is intended to propose a human-interference model that can be used to enhance the accuracy of the tomographic imaging process while reducing the computational cost. This paper discusses the application of human-interference model to improve the Wi-Fi tomographic imaging, and also the paper includes details about implementation of the algorithm and improved image reconstruction process along with results. The proposed novel methodology uses both regularization and the human interference model to enhance the accuracy of the imaging process.