Flexible Thermoelectric Generators and 2-D Graphene pH Sensors for Wireless Sensing in Hot Spring Ecosystem

abstract: Energy harvesting from ambient is important to configuring Wireless Sensor Networks (WSN) for environmental data collecting. In this work, highly flexible thermoelectric generators (TEGs) have been studied and fabricated to supply power to the wireless sensor notes used for data collecting in hot spring environment. The fabricated flexible TEGs can be easily deployed on the uneven surface of heated rocks at the rim of hot springs. By employing the temperature gradient between the hot rock surface and the air, these TEGs can generate power to extend the battery lifetime of the sensor notes and therefore reduce multiple batteries changes where the environment is usually harsh in hot springs. Also, they show great promise for self-powered wireless sensor notes. Traditional thermoelectric material bismuth telluride (Bi2Te3) and advanced MEMS (Microelectromechanical systems) thin film techniques were used for the fabrication. Test results show that when a flexible TEG array with an area of 3.4cm2 was placed on the hot plate surface of 80°C in the air under room temperature, it had an open circuit voltage output of 17.6mV and a short circuit current output of 0.53mA. The generated power was approximately 7mW/m2. On the other hand, high pressure, temperatures that can reach boiling, and the pH of different hot springs ranging from 9 make hot spring ecosystem a unique environment that is difficult to study. WSN allows many scientific studies in harsh environments that are not feasible with traditional instrumentation. However, wireless pH sensing for long time in situ data collection is still challenging for two reasons. First, the existing commercial-off-the-shelf pH meters are frequent calibration dependent; second, biofouling causes significant measurement error and drift. In this work, 2-dimentional graphene pH sensors were studied and calibration free graphene pH sensor prototypes were fabricated. Test result shows the resistance of the fabricated device changes linearly with the pH values (in the range of 3-11) in the surrounding liquid environment. Field tests show graphene layer greatly prevented the microbial fouling. Therefore, graphene pH sensors are promising candidates that can be effectively used for wireless pH sensing in exploration of hot spring ecosystems.Dissertation/ThesisDoctoral Dissertation Exploration Systems Design 201

Ultra-Low Power IoT Smart Visual Sensing Devices for Always-ON Applications

This work presents the design of a Smart Ultra-Low Power visual sensor architecture that couples together an ultra-low power event-based image sensor with a parallel and power-optimized digital architecture for data processing. By means of mixed-signal circuits, the imager generates a stream of address events after the extraction and binarization of spatial gradients. When targeting monitoring applications, the sensing and processing energy costs can be reduced by two orders of magnitude thanks to either the mixed-signal imaging technology, the event-based data compression and the use of event-driven computing approaches. From a system-level point of view, a context-aware power management scheme is enabled by means of a power-optimized sensor peripheral block, that requests the processor activation only when a relevant information is detected within the focal plane of the imager. When targeting a smart visual node for triggering purpose, the event-driven approach brings a 10x power reduction with respect to other presented visual systems, while leading to comparable results in terms of detection accuracy. To further enhance the recognition capabilities of the smart camera system, this work introduces the concept of event-based binarized neural networks. By coupling together the theory of binarized neural networks and focal-plane processing, a 17.8% energy reduction is demonstrated on a real-world data classification with a performance drop of 3% with respect to a baseline system featuring commercial visual sensors and a Binary Neural Network engine. Moreover, if coupling the BNN engine with the event-driven triggering detection flow, the average power consumption can be as low as the sleep power of 0.3mW in case of infrequent events, which is 8x lower than a smart camera system featuring a commercial RGB imager

Analysis and design of a wide dynamic range pulse-frequency modulation CMOS image sensor

Complementary Metal-Oxide Semiconductor (CMOS) image sensor is the dominant electronic imaging device in many application fields, including the mobile or portable devices, teleconference cameras, surveillance and medical imaging sensors. Wide dynamic range (WDR) imaging is of interest particular, demonstrating a large-contrast imaging range of the sensor. As of today, different approaches have been presented to provide solutions for this purpose, but there exists various trade-offs among these designs, which limit the number of applications. A pulse-frequency modulation (PFM) pixel offers the possibility to outperform existing designs in WDR imaging applications, however issues such as uniformity and cost have to be carefully handled to make it practical for different purposes. In addition, a complete evaluation of the sensor performance has to be executed prior to fabrication in silicon technology. A thorough investigation of WDR image sensor based on the PFM pixel is performed in this thesis. Starting with the analysis, modeling, and measurements of a PFM pixel, the details of every particular circuit operation are presented. The causes of dynamic range (DR) limitations and signal nonlinearity are identified, and noise measurement is also performed, to guide future design strategies. We present the design of an innovative double-delta compensating (DDC) technique which increases the sensor uniformity as well as DR. This technique achieves performance optimization of the PFM pixel with a minimal cost an improved linearity, and is carefully simulated to demonstrate its feasibility. A quad-sampling technique is also presented with the cooperation of pixel and column circuits to generate a WDR image sensor with a reduced cost for the pixel. This method, which is verified through the field-programmable gate array (FPGA) implementation, saves considerable area in the pixel and employs the maximal DR that a PFM pixel provides. A complete WDR image sensor structure is proposed to evaluate the performance and feasibility of fabrication in silicon technology. The plans of future work and possible improvements are also presented