Current Issue : April-June Volume : 2024 Issue Number : 2 Articles : 5 Articles
Taking ARM as the hardware platform, the embedded system is built from both hardware and software aspects with the application as the center. In the hardware design, build the hardware platform scheme, design the schematic diagram as well as PCB, complete the hardware debugging, and ensure the system hardware platform function; in the software design, optimize the three-stage pipeline structure of ARM instruction system, design the instruction set, install the embedded system on the virtual machine, build the cross-toolchain, and set up the correct NFS network file system. Finish the design of the ARM-based embedded system platform, combined with the hardware requirements of the experimental platform, transplant the powerful Uboot as the Bootloader of the system, and further transplant the Linux-2.6. 32 kernel to the system start the operation normally, and finally, build the root file to finish the study of its portability....
With the expansion of electronics in recent decades, it is notorious to observe that embedded systems are increasingly necessary to improve people’s quality of life and to facilitate the diagnosis of systems in general, ranging from pacemakers to control systems. The increased use of electronic components for technological support, such as telemetry systems, electronic injection, and automotive diagnostic scanners, enhances the perspective of data analysis through an embedded system aimed at vehicular systems. Thus, this work aims to design and implement an embedded data acquisition system for the analysis of vehicle vertical dynamics. The methodology for this study was structured into several stages: mathematical modeling of a motorcycle’s mass-spring-damper system, coding for the Arduino microcontroller, computational data analysis supported by MATLAB software version 9.6, electronic prototyping of the embedded system, implementation on the vehicle, and the analysis of motorcycle vertical dynamics parameters. In addition, a mathematical modeling of the massspring- damper system was performed using the state-space method. The system was implemented on the Arduino microcontroller platform, enabling real-time data transfer from a motorcycle. The experimental results have successfully validated the proposed data acquisition system....
This study aims to examine the dynamic response of a polyvinylidene fluoride (PVDF) piezoelectric sensor which is embedded into an aluminum coupon using ultrasonic additive manufacturing (UAM). Traditional manufacturing techniques used to attach smart materials to metals on the surface have drawbacks, including the potential of exposing the sensor to adverse environments or physical degradation during manufacture. UAM can avoid these issues by integrating solid-state metal joining with subtractive processes to enable the fabrication of smart structures. A commercial PVDF sensor is embedded in aluminum with a compression technique to provide frictional coupling between the sensor and the metallic matrix. The PVDF sensor’s frequency bandwidth and impact detection performance are evaluated by conducting cantilever and axial impact tests, as well as harmonic excitation tests with an electrodynamic shaker. Under axial loading, the embedded sensor displays high linearity with a sensitivity of 43.7 mV/N, whereas impact tests in the cantilever configuration exhibit a steady decay rate of 0.13%. Finally, bending tests show good agreement between theoretical and experimental natural frequencies with percentage errors under 6% in two different clamping positions, and correspond to the maximum voltage output obtained from the embedded PVDF sensor at resonance....
This paper focuses on the alignment of Graphical- User-Interface (GUI) applications and embedded devices. The main contribution is a benchmark approach that enables measuring and comparing the GUI rendering capability of embedded devices and provides a performanceoriented GUI design recommendation for an embedded device. The benchmark is tailored to common GUI applications and resource-limited devices, which are usually mounted in mobile machines. GUI applications can only be rendered smoothly if these devices have sufficient performance. A general benchmark concept is described and modeled in Unified Modeling Language (UML) at first, followed by a prototypical implementation and evaluation. It is demonstrated that the benchmark approach is applicable to GUI applications with different levels of complexity as well as embedded devices of different performance classes....
Embedded applications are increasingly prevalent in various domains, from consumer electronics to industrial automation and smart cities. With the advances in integrated circuit manufacturing technologies, low-power chips can now execute complex algorithms, including machine learning models. However, the computational constraints of embedded devices require compact and efficient neural network models, as well as software frameworks and optimisation techniques tailored to their hardware resources. This study investigates the implementation of Convolutional Neural Network (CNN) models for gesture recognition on an STM32F4 microcontroller, by exploring the impact of freezing layers, fine-tuning and pruning techniques on pre-trained CNN models. The results demonstrate that fine-tuning and freezing layers improve accuracy by up to 18 %. Finally, this study demonstrates that pruning reduced the model size by 90 % with a 30 % accuracy impact, when compared to the uncompressed model, enabling it to perform gesture recognition on small devices. These findings are significant for developing software and optimisation techniques for embedded systems, particularly in the context of the Internet of Things....
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