Matching Items (17)
Description
The ubiquity of embedded computational systems has exploded in recent years impacting everything from hand-held computers and automotive driver assistance to battlefield command and control and autonomous systems. Typical embedded computing systems are characterized by highly resource constrained operating environments. In particular, limited energy resources constrain performance in embedded systems often reliant on independent fuel or battery supplies. Ultimately, mitigating energy consumption without sacrificing performance in these systems is paramount. In this work power/performance optimization emphasizing prevailing data centric applications including video and signal processing is addressed for energy constrained embedded systems. Frameworks are presented which exchange quality of service (QoS) for reduced power consumption enabling power aware energy management. Power aware systems provide users with tools for precisely managing available energy resources in light of user priorities, extending availability when QoS can be sacrificed. Specifically, power aware management tools for next generation bistable electrophoretic displays and the state of the art H.264 video codec are introduced. The multiprocessor system on chip (MPSoC) paradigm is examined in the context of next generation many-core hand-held computing devices. MPSoC architectures promise to breach the power/performance wall prohibiting advancement of complex high performance single core architectures. Several many-core distributed memory MPSoC architectures are commercially available, while the tools necessary to effectively tap their enormous potential remain largely open for discovery. Adaptable scalability in many-core systems is addressed through a scalable high performance multicore H.264 video decoder implemented on the representative Cell Broadband Engine (CBE) architecture. The resulting agile performance scalable system enables efficient adaptive power optimization via decoding-rate driven sleep and voltage/frequency state management. The significant problem of mapping applications onto these architectures is additionally addressed from the perspective of instruction mapping for limited distributed memory architectures with a code overlay generator implemented on the CBE. Finally runtime scheduling and mapping of scalable applications in multitasking environments is addressed through the introduction of a lightweight work partitioning framework targeting streaming applications with low latency and near optimal throughput demonstrated on the CBE.
ContributorsBaker, Michael (Author) / Chatha, Karam S. (Thesis advisor) / Raupp, Gregory B. (Committee member) / Vrudhula, Sarma B. K. (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2011
Description
Deep neural network-based methods have been proved to achieve outstanding performance on object detection and classification tasks. Deep neural networks follow the ``deeper model with deeper confidence'' belief to gain a higher recognition accuracy. However, reducing these networks' computational costs remains a challenge, which impedes their deployment on embedded devices. For instance, the intersection management of Connected Autonomous Vehicles (CAVs) requires running computationally intensive object recognition algorithms on low-power traffic cameras. This dissertation aims to study the effect of a dynamic hardware and software approach to address this issue. Characteristics of real-world applications can facilitate this dynamic adjustment and reduce the computation. Specifically, this dissertation starts with a dynamic hardware approach that adjusts itself based on the toughness of input and extracts deeper features if needed. Next, an adaptive learning mechanism has been studied that use extracted feature from previous inputs to improve system performance. Finally, a system (ARGOS) was proposed and evaluated that can be run on embedded systems while maintaining the desired accuracy. This system adopts shallow features at inference time, but it can switch to deep features if the system desires a higher accuracy. To improve the performance, ARGOS distills the temporal knowledge from deep features to the shallow system. Moreover, ARGOS reduces the computation furthermore by focusing on regions of interest. The response time and mean average precision are adopted for the performance evaluation to evaluate the proposed ARGOS system.
ContributorsFarhadi, Mohammad (Author) / Yang, Yezhou (Thesis advisor) / Vrudhula, Sarma (Committee member) / Wu, Carole-Jean (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2022
Description
The purpose of this thesis is to create and evaluate an honors project for the CSE 325 Embedded Microprocessor Systems course at Arizona State University (ASU). It encourages students to expand upon the skills they learn in class and practice new skills that prove to be useful in industry. This is accomplished through implementing an Adafruit mini sound board using the UART communication protocol. The project’s success was measured with a survey taken by the participating students. The results indicated that the project was enriching and provided valuable experience. After further improvements, the goal is for this project to be offered each semester for students of Barrett, the Honors College in CSE 325 to complete as an honors contract.
ContributorsArnold, Elizabeth (Author) / Meuth, Ryan (Thesis director) / Indela, Soumya (Committee member) / Barrett, The Honors College (Contributor) / School of Music, Dance and Theatre (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
Description
Portable health diagnostic systems seek to perform medical grade diagnostics in non-ideal environments. This work details a robust fault tolerant portable health diagnostic design implemented in hardware, firmware and software for the detectionof HPV in low-income countries. The device under device under test (DUT) is a fluorescence based lateral flow assay (LFA) point-of-care (POC) device. This work’s contributions are: firmware and software development, calibration routine implementation, device performance characterization and a proposed method of in-software fault detection. Firmware was refactored from the original implementation of the POC fluorescence reader to expose an application programming interface (API) via USB. Companion software available for desktop environments (Windows, Mac and Linux) was created to interface with this firmware API and conduct macro level routines to request and receive fluorescence data while presenting a user-friendly interface to clinical technicians. Lastly, an environmental chamber was constructed to conduct sequential diagnostic reads in order to observe sensor drift and other deviations that might present themselves in real-world usage. The results from these evaluations show a standard deviation of less than 1% in fluorescence readings in nominal temperature environments (approx. 25C) suggesting that this system will have a favorable signal-to-noise (SNR) ratio in such a setting. In non-ideal over heated environments (≥38C), the evaluation results showed performance degradation with standard deviations as large as 15%.
ContributorsLue Sang, Christopher David (Author) / Blain Christen, Jennifer M (Thesis advisor) / Ozev, Sule (Committee member) / Goryll, Michael (Committee member) / Raupp, Gregory (Committee member) / Arizona State University (Publisher)
Created2022
Description
According to the Center for Disease Control and Prevention report around 29,668 United States residents aged greater than 65 years had died as a result of a fall in 2016. Other injuries like wrist fractures, hip fractures, and head injuries occur as a result of a fall. Certain groups of people are more prone to experience falls than others, one of which being individuals with stroke. The two most common issues with individuals with strokes are ankle weakness and foot drop, both of which contribute to falls. To mitigate this issue, the most popular clinical remedy given to these users is thermoplastic Ankle Foot Orthosis. These AFO's help improving gait velocity, stride length, and cadence. However, studies have shown that a continuous restraint on the ankle harms the compensatory stepping response and forward propulsion. It has been shown in previous studies that compensatory stepping and forward propulsion are crucial for the user's ability to recover from postural perturbations. Hence, there is a need for active devices that can supply a plantarflexion during the push-off and dorsiflexion during the swing phase of gait. Although advancements in the orthotic research have shown major improvements in supporting the ankle joint for rehabilitation, there is a lack of available active devices that can help impaired users in daily activities. In this study, our primary focus is to build an unobtrusive, cost-effective, and easy to wear active device for gait rehabilitation and fall prevention in individuals who are at risk. The device will be using a double-acting cylinder that can be easily incorporated into the user's footwear using a novel custom-designed powered ankle brace. The device will use Inertial Measurement Units to measure kinematic parameters of the lower body and a custom control algorithm to actuate the device based on the measurements. The study can be used to advance the field of gait assistance, rehabilitation, and potentially fall prevention of individuals with lower-limb impairments through the use of Active Ankle Foot Orthosis.
ContributorsRay, Sambarta (Author) / Honeycutt, Claire (Thesis advisor) / Dasarathy, Gautam (Thesis advisor) / Redkar, Sangram (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2020
Description
Children's hospitals can be a scary place for children and their parents. Patients are stressed and anxious because they are in a space that is unfamiliar to them, and being forced to be in a confined space feels like a punishment. Parents accompanying their children in hospitals are also emotionally stressed due to the overwhelming parental and financial responsibilities. There is a product opportunity gap which allows the patients to interact with the environment to make it more familiar to them and interact with the people around them to alleviate stress anxiety. This project aims to use the user-inspired engineering process to close that product opportunity gap.
ContributorsWang, Yujia (Author) / Brown, Hannah (Co-author) / Hedges, Craig (Thesis director) / Fischer, Adelheid (Committee member) / Barrett, The Honors College (Contributor) / Engineering Programs (Contributor) / Electrical Engineering Program (Contributor) / Software Engineering (Contributor) / WPC Graduate Programs (Contributor)
Created2023-05
Description
Pollution is an increasing problem around the world, and one of the main forms it takes is air pollution. Air pollution, from oxides and dioxides to particulate matter, continues to contribute to millions of deaths each year, which is more than the next three leading causes of environment-related death combined. Plus, the problem is only growing as industrial plants, factories, and transportation continues to rapidly increase across the globe. Those most affected include less developed countries and individuals with pre-existing respiratory conditions. Although many citizens know about this issue, it is often unclear what times and locations are worst in terms of pollutant concentration as it can vary on the time of day, local activity, and other variable factors. As a result, citizens lack the knowledge and resources to properly combat or avoid air pollution, as well as the data and evidence to support any sort of regulatory change. Many companies and organizations have tried to address this through Air Quality Indexes (AQIs) but are not focused enough to help the everyday citizen, and often fail to include many significant pollutants. Thus, we sought to address this issue in a cost-effective way through creating a network of IoT (Internet of Things) devices and deploying them in a select area of Tempe, Arizona. We utilized Arduino Microprocessors and Wireless Radio Frequency Transceivers to send and receive air pollution data in real time. Then, displayed this data in such a way that it could be released to the public via web or mobile app. Furthermore, the product is cheap enough to be reproduced and sold in bulk as well as scaled and customized to be compatible with dozens of different air quality sensors.
ContributorsCoury, Abrahm Philip (Co-author) / Gillespie, Cody (Co-author) / Ren, Fengbo (Thesis director) / Shrivastava, Aviral (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05