Ultra-Low Power Circuit Design for Cubic-Millimeter Wireless Sensor Platform.

Modern daily life is surrounded by smaller and smaller computing devices. As Bell’s Law predicts, the research community is now looking at tiny computing platforms and mm3-scale sensor systems are drawing an increasing amount of attention since they can create a whole new computing environment. Designing mm3-scale sensor nodes raises various circuit and system level challenges and we have addressed and proposed novel solutions for many of these challenges to create the first complete 1.0mm3 sensor system including a commercial microprocessor. We demonstrate a 1.0mm3 form factor sensor whose modular die-stacked structure allows maximum volume utilization. Low power I2C communication enables inter-layer serial communication without losing compatibility to standard I2C communication protocol. A dual microprocessor enables concurrent computation for the sensor node control and measurement data processing. A multi-modal power management unit allowed energy harvesting from various harvesting sources. An optical communication scheme is provided for initial programming, synchronization and re-programming after recovery from battery discharge. Standby power reduction techniques are investigated and a super cut-off power gating scheme with an ultra-low power charge pump reduces the standby power of logic circuits by 2-19× and memory by 30%. Different approaches for designing low-power memory for mm3-scale sensor nodes are also presented in this work. A dual threshold voltage gain cell eDRAM design achieves the lowest eDRAM retention power and a 7T SRAM design based on hetero-junction tunneling transistors reduces the standby power of SRAM by 9-19× with only 15% area overhead. We have paid special attention to the timer for the mm3-scale sensor systems and propose a multi-stage gate-leakage-based timer to limit the standard deviation of the error in hourly measurement to 196ms and a temperature compensation scheme reduces temperature dependency to 31ppm/°C. These techniques for designing ultra-low power circuits for a mm3-scale sensor enable implementation of a 1.0mm3 sensor node, which can be used as a skeleton for future micro-sensor systems in variety of applications. These microsystems imply the continuation of the Bell’s Law, which also predicts the massive deployment of mm3-scale computing systems and emergence of even smaller and more powerful computing systems in the near future.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91438/1/sori_1.pd

An Energy Harvesting Solution for IoT Sensors Using MEMS Technology

The significant development of IoT sensors will play a critical role in a large number of applications. It is predicted that billions of IoT sensors will be used worldwide by 2020 [1]. Batteries are commonly utilized to power on sensors, but they are depleted and they require maintenance and replacement. Battery replacement for billions of sensors is a daunting task and battery disposal for IoT sensors can become an environmental problem. Energy harvesting from ambient sources presents a viable solution to overcome these problems. Among all energy sources, light is considered as one of the best sources due to its high energy density and availability in both indoor and outdoor environments. In order to make an energy harvesting system efficient, many methods have been proposed in the literature to extract the maximum energy while minimizing the power consumption by the energy harvesting circuitry. In this work, a boost converter circuit is designed using MEMS-based switches to reduce the leakage current and power loss caused by conventional transistor-based switches. A light energy harvesting method is also proposed utilizing available components of a typical IoT sensor. The reuse of available components in the proposed solution reduces the overall power consumption and the area overhead of the energy harvesting solution

An Input Power-Aware Maximum Efficiency Tracking Technique for Energy Harvesting in IoT Applications

The Internet of Things (IoT) enables intelligent monitoring and management in many applications such as industrial and biomedical systems as well as environmental and infrastructure monitoring. As a result, IoT requires billions of wireless sensor network (WSN) nodes equipped with a microcontroller and transceiver. As many of these WSN nodes are off-grid and small-sized, their limited-capacity batteries need periodic replacement. To mitigate the high costs and challenges of these battery replacements, energy harvesting from ambient sources is vital to achieve energy-autonomous operation. Energy harvesting for WSNs is challenging because the available energy varies significantly with ambient conditions and in many applications, energy must be harvested from ultra-low power levels. To tackle these stringent power constraints, this dissertation proposes a discontinuous charging technique for switched-capacitor converters that improves the power conversion efficiency (PCE) at low input power levels and extends the input power harvesting range at which high PCE is achievable. Discontinuous charging delivers current to energy storage only during clock non-overlap time. This enables tuning of the output current to minimize converter losses based on the available input power. Based on this fundamental result, an input power-aware, two-dimensional efficiency tracking technique for WSNs is presented. In addition to conventional switching frequency control, clock nonoverlap time control is introduced to adaptively optimize the power conversion efficiency according to the sensed ambient power levels. The proposed technique is designed and simulated in 90nm CMOS with post-layout extraction. Under the same input and output conditions, the proposed system maintains at least 45% PCE at 4μW input power, as opposed to a conventional continuous system which requires at least 18.7μW to maintain the same PCE. In this technique, the input power harvesting range is extended by 1.5x. The technique is applied to a WSN implementation utilizing the IEEE 802.15.4- compatible GreenNet communications protocol for industrial and wearable applications. This allows the node to meet specifications and achieve energy autonomy when deployed in harsher environments where the input power is 49% lower than what is required for conventional operation

Ultra-Low Power Circuit Design for Miniaturized IoT Platform

This thesis examines the ultra-low power circuit techniques for mm-scale Internet of Things (IoT) platforms. The IoT devices are known for their small form factors and limited battery capacity and lifespan. So, ultra-low power consumption of always-on blocks is required for the IoT devices that adopt aggressive duty-cycling for high power efficiency and long lifespan. Several problems need to be addressed regarding IoT device designs, such as ultra-low power circuit design techniques for sleep mode and energy-efficient and fast data rate transmission for active mode communication. Therefore, this thesis highlights the ultra-low power always-on systems, focusing on energy efficient optical transmission in order to miniaturize the IoT systems. First, this thesis presents a battery-less sub-nW micro-controller for an always-operating system implemented with a newly proposed logic family. Second, it proposes an always-operating sub-nW light-to-digital converter to measure instant light intensity and cumulative light exposure, which employs the characteristics of this proposed logic family. Third, it presents an ultra-low standby power optical wake-up receiver with ambient light canceling using dual-mode operation. Finally, an energy-efficient low power optical transmitter for an implantable IoT device is suggested. Implications for future research are also provided.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145862/1/imhotep_1.pd

Energy extraction from the biologic battery in the inner ear

Endocochlear potential (EP) is a battery-like electrochemical gradient found in and actively maintained by the inner ear [superscript 1, 2]. Here we demonstrate that the mammalian EP can be used as a power source for electronic devices. We achieved this by designing an anatomically sized, ultra-low quiescent-power energy harvester chip integrated with a wireless sensor capable of monitoring the EP itself. Although other forms of in vivo energy harvesting have been described in lower organisms [superscript 3, 4, 5], and thermoelectric [superscript 6], piezoelectric [superscript 7] and biofuel [superscript 8, 9] devices are promising for mammalian applications, there have been few, if any, in vivo demonstrations in the vicinity of the ear, eye and brain. In this work, the chip extracted a minimum of 1.12 nW from the EP of a guinea pig for up to 5 h, enabling a 2.4 GHz radio to transmit measurement of the EP every 40–360 s. With future optimization of electrode design, we envision using the biologic battery in the inner ear to power chemical and molecular sensors, or drug-delivery actuators for diagnosis and therapy of hearing loss and other disorders.Focus Center Research Program. Focus Center for Circuit & System Solutions. Semiconductor Research Corporation. Interconnect Focus CenterNational Institutes of Health (U.S.) (Grant K08 DC010419)National Institutes of Health (U.S.) (Grant T32 DC00038)Bertarelli Foundatio

Energy self-sufficient systems for monitoring sewer networks

Underground infrastructure networks form the backbone of vital supply and disposal systems. However, they are under-monitored in comparison to their value. This is due, in large part, to the lack of energy supply for monitoring and data transmission. In this paper, we investigate a novel, energy harvesting system used to power underground sewer infrastructure monitoring networks. The system collects the required energy from ambient sources, such as temperature differences or residual light in sewer networks. A prototype was developed that could use either a thermoelectric generator (TEG) or a solar cell to capture the energy needed to acquire and transmit ultrasonic water level data via LoRaWAN. Real-world field trials were satisfactory and showed the potential power output, as well as, possibilities to improve the system. Using an extrapolation model, we proved that the developed solution could work reliably throughout the year.Comment: To be published in proceedings of the conference "21. ITG/GMA- Fachtagung Sensoren und Messsysteme 2022", 10.-11. Mai 2022, N\"urnberger CongressCenter, Nuremberg, Germany, or IEEE explor

A Sub-nW 2.4 GHz Transmitter for Low Data-Rate Sensing Applications

This paper presents the design of a narrowband transmitter and antenna system that achieves an average power consumption of 78 pW when operating at a duty-cycled data rate of 1 bps. Fabricated in a 0.18 μm CMOS process, the transmitter employs a direct-RF power oscillator topology where a loop antenna acts as a both a radiative and resonant element. The low-complexity single-stage architecture, in combination with aggressive power gating techniques and sizing optimizations, limited the standby power of the transmitter to only 39.7 pW at 0.8 V. Supporting both OOK and FSK modulations at 2.4 GHz, the transmitter consumed as low as 38 pJ/bit at an active-mode data rate of 5 Mbps. The loop antenna and integrated diodes were also used as part of a wireless power transfer receiver in order to kick-start the system power supply prior to energy harvesting operation.Semiconductor Research Corporation. Interconnect Focus CenterSemiconductor Research Corporation. C2S2 Focus CenterNational Institutes of Health (U.S.) (Grant K08 DC010419)National Institutes of Health (U.S.) (Grant T32 DC00038)Bertarelli Foundatio

A self-powered single-chip wireless sensor platform

Internet of things” require a large array of low-cost sensor nodes, wireless connectivity, low power operation and system intelligence. On the other hand, wireless biomedical implants demand additional specifications including small form factor, a choice of wireless operating frequencies within the window for minimum tissue loss and bio-compatibility This thesis describes a low power and low-cost internet of things system suitable for implant applications that is implemented in its entirety on a single standard CMOS chip with an area smaller than 0.5 mm2. The chip includes integrated sensors, ultra-low-power transceivers, and additional interface and digital control electronics while it does not require a battery or complex packaging schemes. It is powered through electromagnetic (EM) radiation using its on-chip miniature antenna that also assists with transmit and receive functions. The chip can operate at a short distance (a few centimeters) from an EM source that also serves as its wireless link. Design methodology, system simulation and optimization and early measurement results are presented

KRATOS: An Open Source Hardware-Software Platform for Rapid Research in LPWANs

Long-range (LoRa) radio technologies have recently gained momentum in the IoT landscape, allowing low-power communications over distances up to several kilometers. As a result, more and more LoRa networks are being deployed. However, commercially available LoRa devices are expensive and propriety, creating a barrier to entry and possibly slowing down developments and deployments of novel applications. Using open-source hardware and software platforms would allow more developers to test and build intelligent devices resulting in a better overall development ecosystem, lower barriers to entry, and rapid growth in the number of IoT applications. Toward this goal, this paper presents the design, implementation, and evaluation of KRATOS, a low-cost LoRa platform running ContikiOS. Both, our hardware and software designs are released as an open- source to the research community.Comment: Accepted at WiMob 201