<p>With the emergence of 5G/mm-Wave communication, there is a growing need for novel front-end electromechanical devices in filtering and carrier generation applications. CMOS-MEMS resonators fabricated using state-of-the-art Integrated Circuit (IC) manufacturing processes provide a significant advantage for power, area and cost savings. In this work, a comprehensive physics-based compact model capable of capturing the non-linear behaviour and other non-idealities has been developed for MEMS resonators seamlessly integrated in CMOS. As the first large signal model for CMOS-embedded resonators, it enables holistic design of MEMS components with advanced CMOS circuits as well as system-level performance evaluation within the framework of modern IC design tools. Global Foundries 14nm FinFET (GF14LPP) Resonant Body Transistors (fRBT) operating at 11.8 GHz are demonstrated and benchmarked against this large-signal electromechanical model. </p> <p><br></p> <p>Additionally, there is a growing interest in CMOS-integrable ferroelectric materials such as Hafnium Dioxide (HfO2) and Aluminum Scandium Nitride (AlScN) for next-generation memory and computation, as well as electromechanical transduction in CMOS-MEMS devices. This work also explores the performance of 700 MHz Ferroelectric Capacitor-based resonators in the Texas Instruments HPE035 process under high-power operating conditions. Identification of previously unreported characteristics, together with the first nonlinear large signal model for integrated ferroelectric resonators, provides insights on the design of frequency references and acoustic filters using ferroelectric transducers. </p> <p><br></p> <p>Extending the range of unreleased CMOS-MEMS resonators to lower frequency using novel design, we also investigate embedded transducers in chip-scale devices for physical sensing. We have simulated and modeled the transducer coupling for low-frequency propagating modes and benchmarked their projected performance against state-of-the-art conventional MEMS sensors. A new approach to phononic crystal (PnC) Interdigitated Transducers (IDTs) is presented emulating the acoustic dispersion in conventional ICs. Unloaded quality factors up to 15,000 have been measured in $\sim$80 MHz resonators, demonstrating their capacity for resonant rotation sensing. We present a unique methodology to amplify and collimate acoustic waves using CMOS-design-rule-compliant Graded Index (GRIN) Phononic IDTs. Ultimately, the CMOS-MEMS techniques presented in this work for both RF applications and physical sensing can facilitate additional functionality in standard CMOS and emerging 3D heterogeneously integrated (3DHI) ICs with minor or no modifications to manufacturing and packaging. This enables new paradigms in next-generation communications, internet of things (IoT), and hardware security.</p>

<p>Precision livestock farming (PLF) has emerged as a solution to address global challenges related to food scarcity, increasing demand for animal products, slim profit margins in livestock production, and growing societal concerns regarding farm animal welfare. By offering individualized care for animals, PLF aims to provide labor savings, enhanced monitoring, and improved control capabilities within complex farming systems, enabled by digital technologies. The adoption of an individual-centric approach to farming through PLF is anticipated to enhance farm productivity and ensure ethical treatment of animals while mitigating concerns associated with labor shortages in modern intensive farming operations. Real-time continuous monitoring of each animal enables precise and accurate health and well-being management. However, to achieve these benefits, large-scale animal farms require commercially viable technological solutions for individualized care and welfare. Cyber-physical systems (CPSs) offer precise monitoring and control and present a promising avenue for PLF but pose significant implementation challenges.</p> <p>  In this work, a generalizable CPS architecture was formalized with active robotic nodes that can realize adaptive continuous real-time animal health monitoring to maximize productivity, animal welfare, and sustainability. Taking the example of dairy farming, a resource- and criticality-aware CPS was developed that enables real-time resource-aware sensing, adaptive control, and agile networking with an emphasis on handling emergencies autonomously. Using a decentralized approach, each node was made capable of optimizing its operation to be resource conscious, while also being able to identify emergency conditions in real-time. In this novel design, we accommodate the social dynamics of the herd and effectively address the various types of emergencies possible in PLF. Moreover, the communication was customized for the unique needs of animal agriculture, wherein it reduced latency and power consumption while ensuring collision-free two-way synchronization with adaptive range extension for emergency conditions. Further, since the CPS was centered around animals, a special robust security layer was also developed and implemented to protect the active embodied nodes against known and unknown malicious attacks. The proposed CPS reference architecture provides a foundation for implementing individualized care and welfare, ultimately improving the efficiency and sustainability of livestock operations.</p>

<p dir="ltr">The design of hardware platform in acoustic sensing is critical. The number and the spatial arrangement of microphones play a huge role in sensing performance. All microphones should be properly processed for simultaneous recording. This work introduces an FPGA-based acoustic transceiver system supporting acoustic sensing with custom acoustic signals. The system contains 16 microphones and a speaker synchronized during sensing processes. The microphones were arranged into an ‘L’ shape with eight microphones on each line for a better resolution of angle estimation on two dimensions. The microphones were placed on a specifically designed PCB to achieve an optimal distance of the half-wavelength of acoustic signals for optimized sensing performance. A microphone interface was implemented on Ultra96-V2 FPGA for handling the simultaneous high-speed data streams. The system features an implementation of full-level data transmission up to the top-level Python program. To evaluate the sensing performance of the system, we conducted an experiment used Frequency Modulated Continuous Wave (FMCW) as the transmitted acoustic signal. The result of evaluation shown the accurate sensing of range, velocity and relative angle of a moving hand on the two dimensions corresponding to the microphone groups.</p>

Aufgrund der steigenden Verkehrsnachfrage und der begrenzten Resourcen zum Ausbau der Straßenverkehrsnetze werden zukünftig größere Anforderungen an die Effektivität von Telematikanwendungen gestellt. Die Erhebung und Bereitstellung aktueller Verkehrsdaten durch geeignete Sensoren ist dazu eine entscheidende Voraussetzung. Gegenstand dieser Arbeit ist die großflächige Analyse des Straßenverkehrs auf der Basis bodengebundener und verteilter opto-elektronischer Sensoren. Es wird ein Konzept vorgestellt, dass eine von der Bilddatenerhebung bis zur Bereitstellung der Daten für Verkehrsanwendungen durchgehende Verarbeitungskette enthält. Der interdisziplinäre Ansatz bildet die Basis zur Verknüpfung eines solchen Sensorsystems mit Verkehrstelematik. Die Abbildung des Verkehrsgeschehens erfolgt im Gegensatz zu herkömmlichen bodengebundenen Messsystemen innerhalb größerer zusammenhängender Ausschnitte des Verkehrsraums. Dadurch können streckenbezogene Verkehrskenngrößen direkt bestimmt werden. Die Georeferenzierung der Verkehrsobjekte ist die Grundlage für eine optimale Verkehrsanalyse und Verkehrssteuerung. Die generierten Daten sind Basis zur Findung und Verifizierung von Theorien und Modellen sowie zur Entwicklung verkehrsadaptiver Steuerungsverfahren auf mikroskopischer Ebene. Es wird gezeigt, wie aus der Fusion gleichzeitig erhaltener Daten mehrerer Sensoren, die im Bereich des Sichtbaren und im thermalen Infrarot sensitiv sind, ein zusammengesetztes Abbildungsmosaik eines vergrößerten Verkehrsraums erzeugt werden kann. In diesem Abbildungsmosaik werden Verkehrsdatenmodelle unterschiedlicher räumlicher Kategorien abgeleitet. Die Darstellung des Abbildungsmosaiks mit seinen Daten erfolgt auf unterschiedlichen Informationsebenen in geokodierten Karten. Die Bewertung mikroskopischer Verkehrsprozesse wird durch die besondere Berücksichtigung der Zeitkomponente bei der Visualisierung möglich. Die vorgestellte Verarbeitungskette beinhaltet neue Anwendungsbereiche für geografische Informationssysteme (GIS). Der beschriebene Ansatz wurde konzeptionell bearbeitet, in der Programmiersprache IDL realisiert und erfolgreich getestet. / The growing demand of urban and interregional road traffic requires an improvement regarding the effectiveness of telematics systems. The use of appropriate sensor systems for traffic data acquisition is a decisive prerequisite for the efficiency of traffic control. This thesis focuses on analyzing road traffic based on stationary and distributed ground opto-electronic matrix sensors. A concept which covers all parts from image data acquisition up to traffic data provision is presented. This interdisciplinary approach establishes a basis for the integration of such a sensor system into telematics systems. Unlike conventional ground stationary sensors, the acquisition of traffic data is spread over larger areas in this case. As a result, road specific traffic data can be measured directly. Georeferencing of traffic objects is the basis for optimal road traffic analysis and road traffic control. This approach will demonstrate how to generate a spatial mosaic consisting of traffic data generated by several sensors with different spectral resolution. For traffic flow analysis the realisation of special 4D data visualisation methods on different information levels was an essential need. The data processing chain introduces new areas of application for geographical information systems (GIS). The approach utilised in this study has been worked out conceptually and also successfully tested and applied in the programming language IDL.

<p>Passive chipless wireless sensors have gained great attention in Radio Frequency Identification (RFID) applications, inventory tracking, and structural health monitoring, as they offer a prospective low-cost, scalable alternative to the state-of-the-art active sensors. While the popularity and demand for chipless sensors are on the rise, their applications are limited to low-noise environments and their caliber as low-cost, scalable devices has not been explored to a successful degree in challenging domains, such as precision agriculture, healthcare, and food packaging. Size, cost of materials, and complexity of the manufacturing process are the main obstacles to progress in the large-scale production of chipless sensors for practical applications. </p> <p><br></p> <p>Conventional manufacturing processes, such as photolithography, are costly, cumbersome, and time intensive. While additive manufacturing techniques, such as printing technologies, have circumvented some of these challenges, printing techniques require costly inks and complex post-processing steps, such as drying and sintering, which limit their large-scale utilization. To overcome these challenges, this dissertation focuses on investigating the possibility of utilizing laser processing of conventional metalized films and polymers to develop cost-effective chipless sensors. This Scalable Laser Assisted Manufacturing (SLAM) process offers a platform for large-scale roll-to-roll production of high-resolution sensors for precision agriculture, healthcare, and food packaging applications. </p> <p><br></p> <p>In this pursuit, the first study explores combining the SLAM process with 3D printing to develop a miniaturized, biodegradable, chipless sensor for soil moisture monitoring. In the second study, the SLAM process is further explored in the development of metalized stickers for healthcare applications focusing on urine bag management and early risk detection of urinary tract infections. In the third study, the capability of the SLAM process to form moisture-sensitive metal nanoparticles as a co-product of metal patterning is harnessed to develop a chipless humidity sensor. The SLAM process is further expanded in the fourth study by functionalizing metalized films with stimuli-responsive polymers to achieve specificity in detecting unique biomarkers of food spoilage. The SLAM platform described in this work opens up new avenues toward processing metalized fabric for the future of wearable electronics and implementing multi-functional sensors for precision agriculture.</p> <p>  </p>

<p>To facilitate indoor air quality (IAQ) monitoring, the research described herein develops and implements methods for the electronic integration of two types of gas sensor, each functionalized with a polymer blend tailored for CO₂ detection. A highly sensitive and tunable electronic chemiresistive sensor interface was developed and experimentally validated. This device achieved analog-to-digital conversion (ADC) through a pulse width modulated (PWM) signal, temporary data storage with an efficient data buffering system, and noise reduction and signal amplification utilizing an instrumentation amplifier integrator circuit. These techniques can used beyond CO₂-specific applications to compensate for certain undesirable chemiresistive sensor characteristics, such as low response magnitude and signal noise. Additionally, resonant mass sensing circuitry was combined with an on-chip field programmable gate array (FPGA) implemented frequency counter. Hz-level resolution was achieved with an Alorium Snō FPGA board and a Verilog data acquisition and communication program. This device can monitor up to 16 sensor channels simultaneously and has a straightforward interface with a controllable output. Furthermore, the functionality of each integrated sensor was experimentally validated. With additional work, these integrated designs have the potential to be inexpensive, low-power, highly sensitive devices that are suitable for practical use in IAQ monitoring applications.</p>

<p>  </p> <p>Cold chain logistics comprise a large portion of transported pharmaceutical medications and raw materials which must be preserved at specified temperatures to maintain consumer safety and efficacy. An immutable record of temperatures of transported pharmaceutical goods allows for mitigation of temperature-related issues of such drugs and their raw components. The recording of this information on a blockchain creates such an immutable record of this information which can be readily accessed by any relevant party. This can allow for any components which have not been kept at the appropriate temperatures to be removed from production. These data can also be used as inputs for smart contracts or for data analytic purposes. </p> <p>A theoretical framework for such a system, referred to as “TempEnsure” is described, which provides digital capture of the internal temperature of temperature-controlled shipping containers. The data are recorded in a blockchain system. Real world testing of this system was not possible due to monetary constraints, but the functional elements of the system, as well as potential improvements for the system, are discussed.</p>

<p>Multifunctional additive manufacturing has the immense potential of addressing present needs within structural health monitoring by enabling a new additive manufacturing paradigm that redefines what a sensor is, or what sensors should resemble. To achieve this, the properties of printed components must be precisely tailored to meet structure specific and application specific requirements. However due to the limited number of commercially available multifunctional filaments, this research investigates the in-house creation of adaptable piezoresistive multifunctional filaments and their potential within structural health monitoring applications based upon their characterized piezoresistive responses. To do so, a rigid polylactic acid based-filament and a flexible thermoplastic polyurethane based-filament were modified to impart piezoresistive properties using carbon nanofibers. The filaments were produced using different mixing techniques, nanoparticle concentrations, and optimally selected manufacturing parameters from a design of experiments approach. The resulting filaments exhibited consistent resistivity values which were found to be less variable under specific mixing techniques than commercially available multifunctional filaments. This improved consistency was found to be a key factor which held back currently available piezoresistive filaments from fulfilling needs within structural health monitoring. To demonstrate the ability to meet these needs, the piezoresistive responses of three dog-bone shaped sensor sizes were measured under monotonic and cyclic loading conditions for the optimally manufactured filaments. The characterized piezoresistive responses demonstrated high strain sensitivities under both tensile and compressive loads. These piezoresistive sensors demonstrated the greatest sensitivity in tension, where all three sensor sizes exhibited gauge factors over 30. Cyclic loading supported these results and further demonstrated the accuracy and reliability of the printed sensors within SHM applications.</p>

<p>The last few decades have witnessed unprecedented growth in multiple areas of electronics spanning low-power sensing, intelligent computing and high-speed wireless connectivity. In the foreseeable future, there would be hundreds of billions of computing devices, sensors, things and people, wherein the technology will become intertwined with our lives through continuous interaction and collaboration between humans and machines. Such human-centric ideas give rise to the concept of internet of bodies (IoB), which calls for novel and energy-efficient techniques for sensing, processing and secure communication for resource-constrained IoB nodes.As we have painfully learnt during the pandemic, point-of-care diagnostics along with continuous sensing and long-term connectivity has become one of the major requirements in the healthcare industry, further emphasizing the need for energy-efficiency and security in the resource-constrained devices around us.</p> <p>  </p> <p>  With this vision in mind, I’ll divide this dissertation into the following chapters. The first part (Chapter 2) will cover time-domain sensing techniques which allow inherent energy-resolution scalability, and will show the fundamental limits of achievable resolution. Implementations will include 1) a radiation sensing system for occupational dosimetry in healthcare and mining applications, which can achieve 12-18 bit resolution with 0.01-1 µJ energy dissipation, and 2) an ADC-less neural signal acquisition system with direct Analog to Time Conversion at 13pJ/Sample. The second part (Chapters 3 and 4) of this dissertation will involve the fundamentals of developing secure energy-efficient electro-quasistatic (EQS) communication techniques for IoB wearables as well as implants, and will demonstrate  2 examples: 1) Adiabatic Switching for breaking the αCV^2f limit of power consumption in capacitive voltage mode human-body communication (HBC), and 2) Bi-Phasic Quasistatic Brain Communication (BP-QBC) for fully wireless data transfer from a sub-6mm^3, 2 µW brain implant. A custom modulation scheme, along with adiabatic communication enables wireline-like energy efficiencies (<5pJ/b) in HBC-based wireless systems, while the BP-QBC node, being fully electrical in nature, demonstrates sub-50pJ/b efficiencies by eliminating DC power consumption, and by avoiding the transduction losses observed in competing technologies, involving optical, ultrasound and magneto-electric modalities. Next in Chapter 5, we will show an implementation of a reconfigurable system that would include 1) a human-body communication transceiver and 2) a traditional wireless (MedRadio) transceiver on the same integrated circuit (IC), and would demonstrate methods to switch between the two modes by detecting the placement of the transmitter and receiver devices (on-body/away from the body). Finally, in Chapter 6, we shall show a technique of augmenting security in resource-constrained devices through authentication using the Analog/RF properties of the transmitter, which are usually discarded as non-idealities in a digital transceiver chain. This method does not require any additional hardware in the transmitter, making it an extremely promising technique to augment security in highly resource-constrained scenarios. Such energy-efficient intelligent sensing and secure communication techniques, when combined with intelligent in-sensor-analytics at the resource-constrained nodes, can potentially pave the way for perpetual, and even batteryless systems for next-generation IoT, IoB and healthcare applications.</p>

<p><strong>The Energy Monitoring Framework</strong>, designed and developed by IAC, IUPUI, aims to provide a cloud-based solution that combines business analytics with sensors for real-time energy management at the plant level using wireless sensor network technology.</p> <p>The project provides a platform where users can analyze the functioning of a plant using sensor data. The data would also help users to explore the energy usage trends and identify any energy leaks due to malfunctions or other environmental factors in their plant. Additionally, the users could check the machinery status in their plant and have the capability to control the equipment remotely.</p> <p>The main objectives of the project include the following:</p> <ul> <li>Set up a wireless network using sensors and smart implants with a base station/ controller.</li> <li>Deploy and connect the smart implants and sensors with the equipment in the plant that needs to be analyzed or controlled to improve their energy efficiency.</li> <li>Set up a generalized interface to collect and process the sensor data values and store the data in a database.</li> <li>Design and develop a generic database compatible with various companies irrespective of the type and size.</li> <li> Design and develop a web application with a generalized structure. Hence the database can be deployed at multiple companies with minimum customization. The web app should provide the users with a platform to interact with the data to analyze the sensor data and initiate commands to control the equipment.</li> </ul> <p>The General Structure of the project constitutes the following components:</p> <ul> <li>A wireless sensor network with a base station.</li> <li>An Edge PC, that interfaces with the sensor network to collect the sensor data and sends it out to the cloud server. The system also interfaces with the sensor network to send out command signals to control the switches/ actuators.</li> <li>A cloud that hosts a database and an API to collect and store information.</li> <li>A web application hosted in the cloud to provide an interactive platform for users to analyze the data.</li> </ul> <p>The project was demonstrated in:</p> <ul> <li>Lecture Hall (https://iac-lecture-hall.engr.iupui.edu/LectureHallFlask/).</li> <li>Test Bed (https://iac-testbed.engr.iupui.edu/testbedflask/).</li> <li>A company in Indiana.</li> </ul> <p>The above examples used sensors such as current sensors, temperature sensors, carbon dioxide sensors, and pressure sensors to set up the sensor network. The equipment was controlled using compactable switch nodes with the chosen sensor network protocol. The energy consumption details of each piece of equipment were measured over a few days. The data was validated, and the system worked as expected and helped the user to monitor, analyze and control the connected equipment remotely.</p> <p><br></p>