Safety, Security, and Health Care

(Thrust leader: Yiorgos Makris, University of Texas at Dallas)

TxACE is developing analog technologies that enhance public safety and security, and health care. The thrust is working to reduce the cost of millimeter wave imaging and on-vehicle radar technology for automotive safety by researching signal processing techniques that reduce system complexity and transmitter architecture that can efficiently adapt to changing antenna characteristics. This thrust is also investigating vibration sensors, CO2 sensors and sensing techniques to monitor health of motors and mixed signal circuits including power devices, as well as, sensor fusion techniques that can enable monitoring behaviors of a driver in an automobile. This thrust also includes research tasks on mixed signal hardware security utilizing machine learning techniques.

Figure 3. (Top left) Reconfigurable mm-Wave transmitter with active impedance synthesis using a multi-port node-conjugated combiner (K. Sengupta, Princeton), (Top center) A driver wearing a Fi-Cap, a helmet with fiducial markers designed for head pose estimation (C. Busso, UT Dallas), (Bottom left) SEM image of a failed E-mode GaN HEMT, showing electrical discharge and cracks on the gate/source side (M. Kim and S. Shichijo, UT Dallas), (Bottom center) Energy level indicator used to realize secure intermittent microprocessor architecture. A 2-bit indicator is used to adapt the computations of the load based on the availability of energy in the energy storage unit, such as a super capacitor (P. Schaumont, Virginia Tech), (Right) Image formed using a commercial 77-GHz CMOS radar module (M. Torlak, UT Dallas).

Safety, Security and Health Care Thrust

Category Accomplishment
Safety, Security and Health Care (Systems) Impedance mismatch resulting from variations of antenna impedance reduces the power delivered by mm-Wave power amplifiers. This project seeks to overcome this limitation and the concomitant VSWR events using a multi-port architecture which exploits mutual load-pulling to synthesize optimal impedances under VSWR events. Measurements from a fabricated prototype demonstrate broadband Doherty-like operation with Psat>19dBm and PAEpeak>20% across 28GHz to 39GHz, as well as robust tolerance to VSWR events. (2712.013 Sengupta, Princeton)
Safety, Security and Health Care (Systems) The limited energy storage capacity of IoT devices calls for solutions both for energy harvesting and for efficient uses of the energy soon after the harvest. This task seeks to use such energy for pre-computing various aspects required for performing cryptographic operations at IoT nodes. Pre-computation has been used to demonstrate inherent operations of internet security protocols, such as random number generation and as well as cryptographic key exchange, thereby maximizing energy utilization without sacrificing security. (2712.019 Schaumont, Virginia Tech)
Safety, Security and Health Care (Systems) This task focuses on head pose estimation, which is paramount for gaze identification, in order to facilitate coordination between the vehicle and driver. Specifically, this project explores the use of deep learning-based algorithms in fusing multiple sensor modalities (i.e., various types of cameras) to estimate the driver’s visual attention in real-world conditions. Results using data collected across 5 drivers confirm the efficacy of the proposed models. (2810.014, Busso & Al-Dahir, UT Dallas)