The primary focus of autonomous driving research is to improve driving accuracy and reliability. While great progress has been made, state-of-the-art algorithms still fail at times and some of these failures are due to the faults in sensors. Such failures may have fatal consequences. It therefore is important that automated cars foresee problems ahead as early as possible. By using real-world data and artificial injection of different types of sensor faults to the healthy signals, data models can be trained using machine learning techniques. This paper proposes a novel fault detection, isolation, identification and prediction (based on detection) architecture for multi-fault in multi-sensor systems, such as autonomous vehicles.Our detection, identification and isolation platform uses two distinct and efficient deep neural network architectures and obtained very impressive performance. Utilizing the sensor fault detection system’s output, we then introduce our health index measure and use it to train the health index forecasting network.

The potential of terahertz (THz) spectroscopy and imaging in skin cancer detection and mainly basal cell carcinoma (BCC), the most common type of skin cancer, was previously studied. Thanks to the significant absorption of THz waves by hydrogen bonds of water and the higher hydration of tumors than normal skin, it is considered an ideal non-invasive tool for early cancer detection. Despite this potential, there is a lack of study on the THz characterization of treated tumors with anticancer drugs to constitute innovative approaches for chemotherapeutic research, and this is an inspiration for the current study. Previous THz spectroscopy measurements are based on freshly excised tissue and suffer from environmental impacts on tissue and also limit performing a thorough analysis of the effect of different biological parameters. Thus, we have cultured a three-dimensional (3D) organotypic model of BCC tumor to study the THz electromagnetic parameters of tumor in different stages along with the impact of AG1478 anticancer drug on its THz spectra. Measurements are performed in the frequency range of 0.4 to 1.6 THz, and the corresponding refractive index, absorption coefficient, and complex permittivity of normal skin, BCC, and treated BCC have been compared. Furthermore, an enhanced combinational optimization algorithm is developed to calculate the parameters of the double Debye (DD) dielectric model to explain better the discrimination of treated and untreated tumors with normal skin.