Integrated Circuits and Systems for Smart Sensory Applications

Connected intelligent sensing reshapes our society by empowering people with increasing new ways of mutual interactions. As integration technologies keep their scaling roadmap, the horizon of sensory applications is rapidly widening, thanks to myriad light-weight low-power or, in same cases even self-powered, smart devices with high-connectivity capabilities. CMOS integrated circuits technology is the best candidate to supply the required smartness and to pioneer these emerging sensory systems. As a result, new challenges are arising around the design of these integrated circuits and systems for sensory applications in terms of low-power edge computing, power management strategies, low-range wireless communications, integration with sensing devices. In this Special Issue recent advances in application-specific integrated circuits (ASIC) and systems for smart sensory applications in the following five emerging topics: (I) dedicated short-range communications transceivers; (II) digital smart sensors, (III) implantable neural interfaces, (IV) Power Management Strategies in wireless sensor nodes and (V) neuromorphic hardware

Ultra-Low-Power IoT Solutions for Sound Source Localization: Combining Mixed-Signal Processing and Machine Learning

With the prevalence of smartphones, pedestrians and joggers today often walk or run while listening to music. Since they are deprived of auditory stimuli that could provide important cues to dangers, they are at a much greater risk of being hit by cars or other vehicles. We start this research into building a wearable system that uses multichannel audio sensors embedded in a headset to help detect and locate cars from their honks and engine and tire noises. Based on this detection, the system can warn pedestrians of the imminent danger of approaching cars. We demonstrate that using a segmented architecture and implementation consisting of headset-mounted audio sensors, front-end hardware that performs signal processing and feature extraction, and machine-learning-based classification on a smartphone, we are able to provide early danger detection in real time, from up to 80m distance, with greater than 80% precision and 90% recall, and alert the user on time (about 6s in advance for a car traveling at 30mph). The time delay between audio signals in a microphone array is the most important feature for sound-source localization. This work also presents a polarity-coincidence, adaptive time-delay estimation (PCC-ATDE) mixed-signal technique that uses 1-bit quantized signals and a negative-feedback architecture to directly determine the time delay between signals in the analog inputs and convert it to a digital number. This direct conversion, without a multibit ADC and further digital-signal processing, allows for ultra low power consumption. A prototype chip in 0:18μm CMOS with 4 analog inputs consumes 78nW with a 3-channel 8-bit digital time-delay output while sampling at 50kHz with a 20μs resolution and 6.06 ENOB. We present a theoretical analysis for the nonlinear, signal-dependent feedback loop of the PCC-ATDE. A delay-domain model of the system is developed to estimate the power bandwidth of the converter and predict its dynamic response. Results are validated with experiments using real-life stimuli, captured with a microphone array, that demonstrate the technique’s ability to localize a sound source. The chip is further integrated in an embedded platform and deployed as an audio-based vehicle-bearing IoT system. Finally, we investigate the signal’s envelope, an important feature for a host of applications enabled by machine-learning algorithms. Conventionally, the raw analog signal is digitized first, followed by feature extraction in the digital domain. This work presents an ultra-low-power envelope-to-digital converter (EDC) consisting of a passive switched-capacitor envelope detector and an inseparable successive approximation-register analog-to-digital converter (ADC). The two blocks integrate directly at different sampling rates without a buffer between them thanks to the ping-pong operation of their sampling capacitors. An EDC prototype was fabricated in 180nm CMOS. It provides 7.1 effective bits of ADC resolution and supports input signal bandwidth up to 5kHz and an envelope bandwidth up to 50Hz while consuming 9.6nW

Low-Power and Programmable Analog Circuitry for Wireless Sensors

Embedding networks of secure, wirelessly-connected sensors and actuators will help us to conscientiously manage our local and extended environments. One major challenge for this vision is to create networks of wireless sensor devices that provide maximal knowledge of their environment while using only the energy that is available within that environment. In this work, it is argued that the energy constraints in wireless sensor design are best addressed by incorporating analog signal processors. The low power-consumption of an analog signal processor allows persistent monitoring of multiple sensors while the device\u27s analog-to-digital converter, microcontroller, and transceiver are all in sleep mode. This dissertation describes the development of analog signal processing integrated circuits for wireless sensor networks. Specific technology problems that are addressed include reconfigurable processing architectures for low-power sensing applications, as well as the development of reprogrammable biasing for analog circuits

Low-Power and Programmable Analog Circuitry for Wireless Sensors

Embedding networks of secure, wirelessly-connected sensors and actuators will help us to conscientiously manage our local and extended environments. One major challenge for this vision is to create networks of wireless sensor devices that provide maximal knowledge of their environment while using only the energy that is available within that environment. In this work, it is argued that the energy constraints in wireless sensor design are best addressed by incorporating analog signal processors. The low power-consumption of an analog signal processor allows persistent monitoring of multiple sensors while the device\u27s analog-to-digital converter, microcontroller, and transceiver are all in sleep mode. This dissertation describes the development of analog signal processing integrated circuits for wireless sensor networks. Specific technology problems that are addressed include reconfigurable processing architectures for low-power sensing applications, as well as the development of reprogrammable biasing for analog circuits

Récolte d'énergie provenant des bus ARINC825 pour les applications en avionique

RÉSUMÉ Les avions modernes sont systématiquement équipés d’un certain nombre de systèmes qui demandent un grand nombre de capteurs pour leur fonctionnement optimal. Les câbles sont nécessaires pour procurer l’énergie et transmettre les données vers et à partir de ces capteurs. Le nombre croissant de capteurs demande encore plus de câbles. L’utilisation de plusieurs câbles entraîne plus de poids, d’espace et de complexité causant une consommation supplémentaire de carburant et donc plus d’émissions de CO2. Par conséquent, le câblage est l’une des principales difficultés dans les avions et l’industrie d’avionique explore des nouvelles techniques pour réduire le nombre des câbles pour construire des avions plus légers et plus économes en carburant. Nous nous intéressons dans ce mémoire à récolter de l’énergie dissipée par les lignes de données présentes dans les systèmes avioniques. L’énergie récoltée serait disposée pour alimenter les capteurs et actuateurs qui seront branchés sur ces lignes de données dans les avions. Cette récolte d’énergie se ferait par le biais d’interface intégré sur puce. L’approche de récolte énergétique proposée est basée sur le protocole d’échange de données par le bus ARINC 825 qui regroupe des périodes d’inactivité (inoccupé) mais maintient des niveaux de tension que nous récupérons comme une source d’alimentation par une chaîne de conversion de puissance. Cette interface de récolte d’énergie proposée comprend des circuits simples, un temps de stabilisation bas, une ondulation de tension réduite, une consommation d’énergie faible, une efficacité énergétique haute. Une conception au niveau de transistor est réalisée en technologie CMOSP 0.35 μm (AMS) 3.3 V/5 V et la performance du système est étudiée dans diverses conditions pour améliorer son efficacité. Ensuite, le système est intégré sur une puce qui a été fabriquée et testée. Les résultats expérimentaux consistent en une efficacité globale de 60%, une tension de sortie de 5.02 V, un temps de stabilisation de 3.6 ms et une ondulation de tension de 0.2 V. Le dispositif complété fournit une puissance de sortie de 10.08 mW pour l’alimentation des capteurs. Les résultats obtenus prouvent que l’interface proposée pourrait servir à alimenter des capteurs avioniques à partir de l’énergie récolté du bus ARINC 825.----------ABSTRACT Modern aircraft are systematically equipped with various systems that require a large number of sensors for their optimum operation. Cables are needed to provide power and transfer data to and from these sensors. The wired connection however, introduces complexity issues to the systems and it is also prone to damage due to wear. The growing numbers of sensors in aircrafts is associated with installation of even more cables. This leads to an enhanced weight of aerial-vehicle wiring and consequently, increased payload capacity, fuel consumption and CO2 emissions. As a result, cabling is one of the major challenges in aircraft and the avionics industry is exploring new techniques to reduce the number of cables to build lighter and more fuel-efficient aircraft. In this study, we are interested in harvesting the dissipated energy through data lines in avionic systems. The harvested energy can potentially be used for feeding the sensors and activators branching off the data lines in aircrafts. The implemented power harvesting approach is based on the data exchange protocol in ARINC 825 field (data) bus and consists of identifying the field bus idle periods are using their voltage level as the power source in the power conversion chain. This proposed energy harvesting interface features simple design of circuit components, short settling time and low-power consumption. A transistor-level design is carried out in CMOSP 0.35 μm (AMS) 3.3 V/5 V technology and the system performance is investigated under various conditions to improve its efficiency. The system is integrated on a microchip and it is fabricated. The experimental results consist of an overall efficiency of 60%, an output voltage of 5.02 V, a settling time of 3.6 ms and a voltage ripple of 0.2 V. Furthermore, the harvesting device provided an output power of 10.08 mW for feeding the sensors. The results proved that the proposed interface could serve as a powering unit of the avionic sensors through the harvested energy from ARINC 825 bus

NASA Tech Briefs, March 2013

Topics covered include: Remote Data Access with IDL Data Compression Algorithm Architecture for Large Depth-of-Field Particle Image Velocimeters Vectorized Rebinning Algorithm for Fast Data Down-Sampling Display Provides Pilots with Real-Time Sonic-Boom Information Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery Monitoring and Acquisition Real-time System (MARS) Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End Micro-Textured Black Silicon Wick for Silicon Heat Pipe Array Robust Multivariable Optimization and Performance Simulation for ASIC Design; Castable Amorphous Metal Mirrors and Mirror Assemblies; Sandwich Core Heat-Pipe Radiator for Power and Propulsion Systems; Apparatus for Pumping a Fluid; Cobra Fiber-Optic Positioner Upgrade; Improved Wide Operating Temperature Range of Li-Ion Cells; Non-Toxic, Non-Flammable, -80 C Phase Change Materials; Soft-Bake Purification of SWCNTs Produced by Pulsed Laser Vaporization; Improved Cell Culture Method for Growing Contracting Skeletal Muscle Models; Hand-Based Biometric Analysis; The Next Generation of Cold Immersion Dry Suit Design Evolution for Hypothermia Prevention; Integrated Lunar Information Architecture for Decision Support Version 3.0 (ILIADS 3.0); Relay Forward-Link File Management Services (MaROS Phase 2); Two Mechanisms to Avoid Control Conflicts Resulting from Uncoordinated Intent; XTCE GOVSAT Tool Suite 1.0; Determining Temperature Differential to Prevent Hardware Cross-Contamination in a Vacuum Chamber; SequenceL: Automated Parallel Algorithms Derived from CSP-NT Computational Laws; Remote Data Exploration with the Interactive Data Language (IDL); Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals; Partitioned-Interval Quantum Optical Communications Receiver; and Practical UAV Optical Sensor Bench with Minimal Adjustability

Energy Harvesting and Energy Storage Systems

This book discuss the recent developments in energy harvesting and energy storage systems. Sustainable development systems are based on three pillars: economic development, environmental stewardship, and social equity. One of the guiding principles for finding the balance between these pillars is to limit the use of non-renewable energy sources

Communication and energy delivery architectures for personal medical devices

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 219-232).Advances in sensor technologies and integrated electronics are revolutionizing how humans access and receive healthcare. However, many envisioned wearable or implantable systems are not deployable in practice due to high energy consumption and anatomically-limited size constraints, necessitating large form-factors for external devices, or eventual surgical re-implantation procedures for in-vivo applications. Since communication and energy-management sub-systems often dominate the power budgets of personal biomedical devices, this thesis explores alternative usecases, system architectures, and circuit solutions to reduce their energy burden. For wearable applications, a system-on-chip is designed that both communicates and delivers power over an eTextiles network. The transmitter and receiver front-ends are at least an order of magnitude more efficient than conventional body-area networks. For implantable applications, two separate systems are proposed that avoid reimplantation requirements. The first system extracts energy from the endocochlear potential, an electrochemical gradient found naturally within the inner-ear of mammals, in order to power a wireless sensor. Since extractable energy levels are limited, novel sensing, communication, and energy management solutions are proposed that leverage duty-cycling to achieve enabling power consumptions that are at least an order of magnitude lower than previous work. Clinical measurements show the first system demonstrated to sustain itself with a mammalian-generated electrochemical potential operating as the only source of energy into the system. The second system leverages the essentially unlimited number of re-charge cycles offered by ultracapacitors. To ease patient usability, a rapid wireless capacitor charging architecture is proposed that employs a multi-tapped secondary inductive coil to provide charging times that are significantly faster than conventional approaches.by Patrick Philip Mercier.Ph.D

Analysis, Design and implementation of Energy Harvesting Systems for Wireless Sensor Nodes.

Ph.DDOCTOR OF PHILOSOPH