Self-powered Time-Keeping and Time-of-Occurrence Sensing

Self-powered and passive Internet-of-Things (IoT) devices (e.g. RFID tags, financial assets, wireless sensors and surface-mount devices) have been widely deployed in our everyday and industrial applications. While diverse functionalities have been implemented in passive systems, the lack of a reference clock limits the design space of such devices used for applications such as time-stamping sensing, recording and dynamic authentication. Self-powered time-keeping in passive systems has been challenging because they do not have access to continuous power sources. While energy transducers can harvest power from ambient environment, the intermittent power cannot support continuous operation for reference clocks. The thesis of this dissertation is to implement self-powered time-keeping devices on standard CMOS processes. In this dissertation, a novel device that combines the physics of quantum tunneling and floating-gate (FG) structures is proposed for self-powered time-keeping in CMOS process. The proposed device is based on thermally assisted Fowler-Nordheim (FN) tunneling process across high-quality oxide layer to discharge the floating-gate node, therefore resulting in a time-dependent FG potential. The device was fully characterized in this dissertation, and it does not require external powering during runtime, making it feasible for passive devices and systems. Dynamic signature based on the synchronization and desynchronization behavior of the FN timer is proposed for authentication of IoT devices. The self-compensating physics ensure that when distributed timers are subjected to identical environment variances that are common-mode noise, they can maintain synchronization with respect to each other. On the contrary, different environment conditions will desynchronize the timers creating unique signatures. The signatures could be used to differentiate between products that belong to different supply-chains or products that were subjected to malicious tampering. SecureID type dynamic authentication protocols based on the signature generated by the FN timers are proposed and they are proven to be robust to most attacks. The protocols are further analyzed to be lightweight enough for passive devices whose computational sources are limited. The device could also be applied for self-powered sensing of time-of-occurrence. The prototype was verified by integrating the device with a self-powered mechanical sensor to sense and record time-of-occurrence of mechanical events. The system-on-chip design uses the timer output to modulate a linear injector to stamp the time information into the sensing results. Time-of-occurrence can be reconstructed by training the mathematical model and then applying that to the test data. The design was verified to have a high reconstruction accuracy

Low Power Circuits for Miniature Sensor Systems.

With the development of VLSI technologies, the sensor systems of all kinds of applications have entered our everyday's life. For specific applications such as medical implants, the form factor of such systems is the crucial concern. In order to minimize of size of the power sources with a given lifetime, the ability to operate the system with low power consumption is the key. An effective way of lowering the active power dissipation is through aggressive voltage scaling. For minimal energy operation, the optimum supply voltage is typical lower than the subthreshold voltage. On the other hand, a sensor system spends most of the time idling while only actively obtaining data in a short period of time. As a result, strong power gating is needed for reducing the leakage power. We discuss the design challenges for several building blocks for the sensor system that have not been gotten much emphasis in term of power consumption. To monitor the period for idle time and to wake up the system periodically, two types of ultra low power timers are proposed. The first one utilizes the gate leakage of a MOS transistor to achieve low temperature dependency and large time constant. The second one implements a program-and-hold technique to compensate for the temperature coefficient of a one-shot oscillator with 150pW of average power. We propose a low power temperature sensor that is suitable for passive RFID transponder. To retrieve the data out of the sensor chip, two passive proximity communication schemes are presented. Capacitive coupling can be used for chips on a stack where the key challenge is misalignment. A alignment detection and microplate reconfiguration method is proposed to solve the problem. We also propose a passive inductive coupling scheme using pulse signaling. Compared to the traditional backscattering technique, the limitations on the quality factor of the inductor and the signal sensitivity of the receiver can be relaxed.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/61782/1/yushiang_1.pd

Understanding and Countermeasures against IoT Physical Side Channel Leakage

With the proliferation of cheap bulk SSD storage and better batteries in the last few years we are experiencing an explosion in the number of Internet of Things (IoT) devices flooding the market, smartphone connected point-of-sale devices (e.g. Square), home monitoring devices (e.g. NEST), fitness monitoring devices (e.g. Fitbit), and smart-watches. With new IoT devices come new security threats that have yet to be adequately evaluated. We propose uLeech, a new embedded trusted platform module for next-generation power scavenging devices. Such power scavenging devices are already widely deployed. For instance, the Square point-of-sale reader uses the microphone/speaker interface of a smartphone for communications and as a power supply. Such devices are being used as trusted devices in security-critical applications, without having been adequately evaluated. uLeech can securely store keys and provide cryptographic services to any connected smartphone. Our design also facilitates physical side-channel security analysis by providing interfaces to facilitate the acquisition of power traces and clock manipulation attacks. Thus uLeech empowers security researchers to analyze leakage in next- generation embedded and IoT devices and to evaluate countermeasures before deployment. Even the most secure systems reveal their secrets through secret-dependent computation. Secret- dependent computation is detectable by monitoring a system’s time, power, or outputs. Common defenses to side-channel emanations include adding noise to the channel or making algorithmic changes to mitigate specific side-channels. Unfortunately, existing solutions are not automatic, not comprehensive, or not practical. We propose an isolation-based approach for eliminating power and timing side-channels that is automatic, comprehensive, and practical. Our approach eliminates side-channels by leveraging integrated decoupling capacitors to electrically isolate trusted computation from the adversary. Software has the ability to request a fixed- power/time quantum of isolated computation. By discretizing power and time, our approach controls the granularity of side-channel leakage; the only burden on programmers is to ensure that all secret-dependent execution differences converge within a power/time quantum. We design and implement three approaches to power/time-based quantization and isolation: a wholly-digital version, a hybrid version that uses capacitors for time tracking, and a full- custom version. We evaluate the overheads of our proposed controllers with respect to software implementations of AES and RSA running on an ARM- based microcontroller and hardware implementations AES and RSA using a 22nm process technology. We also validate the effectiveness and real-world efficiency of our approach by building a prototype consisting of an ARM microcontroller, an FPGA, and discrete circuit components. Lastly, we examine the root cause of Electromagnetic (EM) side-channel attacks on Integrated Circuits (ICs) to augment the Quantized Computing design to mitigate EM leakage. By leveraging the isolation nature of our Quantized Computing design, we can effectively reduce the length and power of the unintended EM antennas created by the wire layers in an IC

Theory, Design and Implementation of Energy-Efficient Biotelemetry using Ultrasound Imaging

This dissertation investigates the fundamental limits of energy dissipation in establishing a communication link with implantable medical devices using ultrasound imaging-based biotelemetry. Ultrasound imaging technology has undergone a revolution during the last decade due to two primary innovations: advances in ultrasonic transducers that can operate over a broad range of frequencies and progresses in high-speed, high-resolution analog-to-digital converters and signal processors. Existing clinical and FDA approved bench-top ultrasound systems cangenerate real-time high-resolution images at frame rates as high as 10000 frames per second. On the other end of the spectrum, portable and hand-held ultrasound systems can generate high-speed real-time scans, widely used for diagnostic imaging in non-clinical environments. This dissertation’s fundamental hypothesis is to leverage the massive data acquisition and computational bandwidth afforded on these devices to establish energy-efficient bio-telemetry links with multiple in-vivo implanted devices. In the first part of the dissertation, I investigate using a commercial off-the-shelf (COTS) diagnostic ultrasound reader to achieve reliable in-vivo wireless telemetry with millimeter-sized piezoelectric crystal transducers. I propose multi-access biotelemetry methods in which several of these crystals simultaneously transmit the data using conventional modulation and coding schemes. I validated the feasibility of in-vivo operation using two piezoelectric crystals tethered to the tricuspid valve and the skin’s surface in a live ovine model. I demonstrated data rates close to 800 Kbps while consuming microwatts of power even in the presence of respiratory and cardiac motion artifacts. In the second part of the dissertation, I investigate the feasibility of energy harvesting from cardiac valvular perturbations to self-power the wireless implantable device. In this study, I explored using piezoelectric sutures implanted in proximity to the valvular regions compared to the previous studies involving piezoelectric patches or encasings attached to the cardiac or aortic surface to exploit nonlinearity in the valvular dynamics and self-power the implanted device. My study shows that power harvested from different annular planes of the tricuspid valve could range from nano-watts to milli-watts. In the final part of this dissertation, I investigate beamforming in B-scan ultrasound imaging to further reduce the biotelemetry energy-budget. In this context, I will study variance-based informatics in which the signal representation takes a form of signal variance instead of the signal mean for encoding and decoding. Using a modeling study, I show that compared to the mean-based logic representation, the variance-based representation can theoretically achieve a superior performance trade-off (in terms of energy dissipation) when operating at fundamental limits imposed by thermal-noise. I will then discuss how to extend variance-based representation to higher signal dimensions. I show that when applying variance-based encoding/decoding to B-scan biotelemetry, the power-dissipation requirements can be reducedto 100 pW even while interrogating from depths greater than 10 cm in a water medium

Wearable, low-power CMOS ISFETs and compensation circuits for on-body sweat analysis

Complementary metal-oxide-semiconductor (CMOS) technology has been a key driver behind the trend of reduced power consumption and increased integration of electronics in consumer devices and sensors. In the late 1990s, the integration of ion-sensitive field-effect transistors (ISFETs) into unmodified CMOS helped to create advancements in lab-on-chip technology through highly parallelised and low-cost designs. Using CMOS techniques to reduce power and size in chemical sensing applications has already aided the realisation of portable, battery-powered analysis platforms, however the possibility of integrating these sensors into wearable devices has until recently remained unexplored. This thesis investigates the use of CMOS ISFETs as wearable electrochemical sensors, specifically for on-body sweat analysis. The investigation begins by evaluating the ISFET sensor for wearable applications, identifying the key advantages and challenges that arise in this pursuit. A key requirement for wearable devices is a low power consumption, to enable a suitable operational life and small form factor. From this perspective, ISFETs are investigated for low power operation, to determine the limitations when trying to push down the consumption of individual sensors. Batteryless ISFET operation is explored through the design and implementation of a 0.35 \si{\micro\metre} CMOS ISFET sensing array, operating in weak-inversion and consuming 6 \si{\micro\watt}. Using this application-specific integrated circuit (ASIC), the first ISFET array powered by body heat is demonstrated and the feasibility of using near-field communication (NFC) for wireless powering and data transfer is shown. The thesis also presents circuits and systems for combatting three key non-ideal effects experienced by CMOS ISFETs, namely temperature variation, threshold voltage offset and drift. An improvement in temperature sensitivity by a factor of three compared to an uncompensated design is shown through measured results, while adding less than 70 \si{\nano\watt} to the design. A method of automatically biasing the sensors is presented and an approach to using spatial separation of sensors in arrays in applications with flowing fluids is proposed for distinguishing between signal and sensor drift. A wearable device using the ISFET-based system is designed and tested with both artificial and natural sweat, identifying the remaining challenges that exist with both the sensors themselves and accompanying components such as microfluidics and reference electrode. A new ASIC is designed based on the discoveries of this work and aimed at detecting multiple analytes on a single chip. %Removed In the latter half of the thesis, Finally, the future directions of wearable electrochemical sensors is discussed with a look towards embedded machine learning to aid the interpretation of complex fluid with time-domain sensor arrays. The contributions of this thesis aim to form a foundation for the use of ISFETs in wearable devices to enable non-invasive physiological monitoring.Open Acces

Energy harvesting methods for transmission lines: a comprehensive review

Humanity faces important challenges concerning the optimal use, security, and availability of energy systems, particularly electrical power systems and transmission lines. In this context, data-driven predictive maintenance plans make it possible to increase the safety, stability, reliability, and availability of electrical power systems. In contrast, strategies such as dynamic line rating (DLR) make it possible to optimize the use of power lines. However, these approaches require developing monitoring plans based on acquiring electrical data in real-time using different types of wireless sensors placed in strategic locations. Due to the specific conditions of the transmission lines, e.g., high electric and magnetic fields, this a challenging problem, aggravated by the harsh outdoor environments where power lines are built. Such sensors must also incorporate an energy harvesting (EH) unit that supplies the necessary electronics. Therefore, the EH unit plays a key role, so when designing such electronic systems, care must be taken to select the most suitable EH technology, which is currently evolving rapidly. This work reviews and analyzes the state-of-the-art technology for EH focused on transmission lines, as it is an area with enormous potential for expansion. In addition to recent advances, it also discusses the research needs and challenges that need to be addressed. Despite the importance of this topic, there is still much to investigate, as this area is still in its infancy. Although EH systems for transmission lines are reviewed, many other applications could potentially benefit from introducing wireless sensors with EH capabilities, such as power transformers, distribution switches, or low- and medium-voltage power lines, among others.This research was funded by Ministerio de Ciencia e Innovación de España, grant number PID2020-114240RB-I00 and by the Generalitat de Catalunya, grant number 2017 SGR 967.Peer ReviewedPostprint (author's final draft

A User Programmable Battery Charging System

Rechargeable batteries are found in almost every battery powered application. Be it portable, stationary or motive applications, these batteries go hand in hand with battery charging systems. With energy harvesting being targeted in this day and age, high energy density and longer lasting batteries with efficient charging systems are being developed by companies and original equipment manufacturers. Whatever the application may be, rechargeable batteries, which deliver power to a load or system, have to be replenished or recharged once their energy is depleted. Battery charging systems must perform this replenishment by using very fast and efficient methods to extend battery life and to increase periods between charges. In this regard, they have to be versatile, efficient and user programmable to increase their applications in numerous battery powered systems. This is to reduce the cost of using different battery chargers for different types of battery powered applications and also to provide the convenience of rare battery replacement and extend the periods between charges. This thesis proposes a user programmable charging system that can charge a Lithium ion battery from three different input sources, i.e. a wall outlet, a universal serial bus (USB) and an energy harvesting system. The proposed charging system consists of three main building blocks, i.e. a pulse charger, a step down DC to DC converter and a switching network system, to extend the number of applications it can be used for. The switching network system is to allow charging of a battery via an energy harvesting system, while the step down converter is used to provide an initial supply voltage to kick start the energy harvesting system. The pulse charger enables the battery to be charged from a wall outlet or a USB network. It can also be reconfigured to charge a Nickel Metal Hydride battery. The final design is implemented on an IBM 0.18µm process. Experimental results verify the concept of the proposed charging system. The pulse charger is able to be reconfigured as a trickle charger and a constant current charger to charge a Li-ion battery and a Nickel Metal Hydride battery, respectively. The step down converter has a maximum efficiency of 90% at an input voltage of 3V and the charging of the battery via an energy harvesting system is also verified

A POWER DISTRIBUTION SYSTEM BUILT FOR A VARIETY OF UNATTENDED ELECTRONICS

A power distribution system (PDS) delivers electrical power to a load safely and effectively in a pre-determined format. Here format refers to necessary voltages, current levels and time variation of either as required by the empowered system. This formatting is usually referred as "conditioning". The research reported in this dissertation presents a complete system focusing on low power energy harvesting, conditioning, storage and regulation. Energy harvesting is a process by which ambient energy present in the environment is captured and converted to electrical energy. In recent years, it has become a prominent research area in multiple disciplines. Several energy harvesting schemes have been exploited in the literature, including solar energy, mechanic energy, radio frequency (RF) energy, thermal energy, electromagnetic energy, biochemical energy, radioactive energy and so on. Different from the large scale energy generation, energy harvesting typically operates in milli-watts or even micro-watts power levels. Almost all energy harvesting schemes require stages of power conditioning and intermediate storage - batteries or capacitors that reservoir energy harvested from the environment. Most of the ambient energy fluctuates and is usually weak. The purpose of power conditioning is to adjust the format of the energy to be further used, and intermediate storage smoothes out the impact of the fluctuations on the power delivered to the load. This dissertation reports an end to end power distribution system that integrates different functional blocks including energy harvesting, power conditioning, energy storage, output regulation and system control. We studied and investigated different energy harvesting schemes and the dissertation places emphasis on radio frequency energy harvesting. This approach has proven to be a viable power source for low-power electronics. However, it is still challenging to obtain significant amounts of energy rapidly and efficiently from the ambient. Available RF power is usually very weak, leading to low voltage applied to the electronics. The power delivered to the PDS is hard to utilize or store. This dissertation presents a configuration including a wideband rectenna, a switched capacitor voltage boost converter and a thin film flexible battery cell that can be re-charged at an exceptionally low voltage. We demonstrate that the system is able to harvest energy from a commercially available hand-held communication device at an overall efficiency as high as 7.7 %. Besides the RF energy harvesting block, the whole PDS includes a solar energy harvesting block, a USB recharging block, a customer selection block, two battery arrays, a control block and an output block. The functions of each of the blocks have been tested and verified. The dissertation also studies and investigates several potential applications of this PDS. The applications we exploited include an ultra-low power tunable neural oscillator, wireless sensor networks (WSNs), medical prosthetics and small unmanned aerial vehicles (UAVs). We prove that it is viable to power these potential loads through energy harvesting from multiple sources

Energy Efficiency in Communications and Networks

The topic of "Energy Efficiency in Communications and Networks" attracts growing attention due to economical and environmental reasons. The amount of power consumed by information and communication technologies (ICT) is rapidly increasing, as well as the energy bill of service providers. According to a number of studies, ICT alone is responsible for a percentage which varies from 2% to 10% of the world power consumption. Thus, driving rising cost and sustainability concerns about the energy footprint of the IT infrastructure. Energy-efficiency is an aspect that until recently was only considered for battery driven devices. Today we see energy-efficiency becoming a pervasive issue that will need to be considered in all technology areas from device technology to systems management. This book is seeking to provide a compilation of novel research contributions on hardware design, architectures, protocols and algorithms that will improve the energy efficiency of communication devices and networks and lead to a more energy proportional technology infrastructure

Intelligent Power Aware Algorithms for Traffic Sensors

The Internet of Things (IoT) is reshaping our world. Soon our world will be based on smart technologies. According to IHS Markit forecasts, the number of connected devices will grow from 15.4 billion in 2015 to 30.7 billion in 2020. Forrester Research predicts that fleet management and the transportation sectors lead others in IoT growth. This may come as no surprise, since the infrastructure (roadways, bridges, airports, etc.) is a prime candidate for sensor integration, providing real-time measurements to support intelligent decisions. The energy cost required to support the anticipated enormous number of predicted deployed devices is unknown. Currently, experts estimate that 2 to 4% of worldwide carbon emissions can be attributed to power consumption in the information and communication industry [1]. This thesis presents several algorithms to optimize power consumption of an intelligent vehicle counter and classifier sensor (iVCCS) based on an event-driven methodology wherein a control block orchestrates the work of various components and subsystems. Data buffering and triggered vehicle detection techniques were developed to reduce duty cycle of corresponding components (e.g., microSD card, magnetometer, and processor execution). A sleep mode is also incorporated and activated by an artificial intelligence-enabled, reinforcement learning algorithm that utilizes the field environment to select proper processor mode (e.g., run or sleep) relative to traffic flow conditions. Sensor life was extended from 48 hours to more than 200 days when leveraging 2300 mAh battery along with algorithms and techniques introduced in this thesis