Integrated vehicle dynamics control systems require real-time communication among their components to improve performance and process efficiency. This communication relies on the use of sensor data, hardware interface...
详细信息
ISBN:
(纸本)9798350358810;9798350358803
Integrated vehicle dynamics control systems require real-time communication among their components to improve performance and process efficiency. This communication relies on the use of sensor data, hardware interfaces, transmission protocols, and control strategies, which all have an impact on the system's reliability. However, as the number of functionalized electronic control units (ECUs) and wiring systems increases, advanced control systems encounter complex functional and cybersecurity issues. To mitigate this complexity, the automotive industry widely employs the Controller Area Network (CAN) communication bus. Nevertheless, the inherent vulnerabilities of CAN and the rich interfaces with external environments increase the systems' susceptibility to soft errors caused by uncertainty factors such as process changes. Therefore, detecting abnormalities in automotive CAN communication is crucial. This paper introduces a machine learning (ML)-based anomaly detection framework to identify anomalies through CAN messages, extracting key features and employing ML models for predictive analysis. It also uses Triple Modular Redundancy (TMR) for trusted ML computation in anomaly detection. The study provides a comparative analysis of various ML algorithms, highlighting the effectiveness of Deep Neural Networks in identifying anomalies within both synthetic and real Hyundai CAN data for a wheel speed control system, showcasing the framework's capability to enhance system reliability and security.
Recently, ZNS SSDs have been actively researched to handle the functions of the FTL directly on the host system. ZNS SSDs can improve the I/O performance and spatial efficiency of SSDs by eliminating GC and eliminatin...
详细信息
ISBN:
(纸本)9798350339864
Recently, ZNS SSDs have been actively researched to handle the functions of the FTL directly on the host system. ZNS SSDs can improve the I/O performance and spatial efficiency of SSDs by eliminating GC and eliminating overprovisioning. In this paper, we analyze the performance by running distributed applications on a file system which supports ZNS SSDs. We found that much of the time difference occurs in the process of executing open and unlink operations rather than the performance of read and write operations. It has been confirmed that the performance difference of read/write operations is not significant for the applications. If structural optimization is made on file system, it has been found that ZNS SSDs are better than CNS SSDs of the same capacity in terms of price.
Designing efficient neural networks for embedded devices is a critical challenge, particularly in applications requiring real-time performance, such as aerial imaging with drones and UAVs for emergency responses. In t...
详细信息
Monitoring and tracing are integral to embeddedsystems development. In context of real-timesystems, overhead is of essence as the timing behavior might be affected. In this paper we present real-time Monitor and Tra...
详细信息
In the rapidly evolving digital era, we have witnessed the rise of computation-intensive and transmission-intensive applications like multi-party real-time video communication, remote medical surgeries, and online edu...
详细信息
A new innovation called wearable assistive robotics has the potential of assisting those with sensorimotor disabilities in doing routine tasks. A lot of research is done on soft robots because of its adaptability, def...
详细信息
Sign language is the primary mode of communication for deaf and hard of hearing community. This paper discusses the development of a realtime sign language recognition system by deploying deep learning techniques. Fo...
详细信息
The feasibility of efficient scheduling of real-timeapplications with different degrees of criticality in safety-involved systems is considered. The object of the study is the scheduling of tasks the solution of whic...
详细信息
Autonomous quadcopter control based on computer vision has become one of the popular research methods. However, challenges persist due to constraints in processing speed and memory associated with embedded edge comput...
详细信息
Achieving efficient and consistent localization with a prior map remains challenging in robotics. Conventional keyframe-based approaches often suffer from sub-optimal viewpoints due to limited field of view (FOV) and/...
详细信息
ISBN:
(纸本)9798350384581;9798350384574
Achieving efficient and consistent localization with a prior map remains challenging in robotics. Conventional keyframe-based approaches often suffer from sub-optimal viewpoints due to limited field of view (FOV) and/or constrained motion, thus degrading the localization performance. To address this issue, we design a real-time tightly-coupled Neural Radiance Fields (NeRF)-aided visual-inertial navigation system (VINS). In particular, by effectively leveraging the NeRF's potential to synthesize novel views, the proposed NeRF-VINS overcomes the limitations of traditional keyframe-based maps (with limited views) and optimally fuses IMU, monocular images, and synthetically rendered images within an efficient filter-based framework. This tightly-coupled fusion enables efficient 3D motion tracking with bounded errors. We extensively validate the proposed NeRF-VINS against the state-of-the-art methods that use prior map information, and demonstrate its ability to perform real-time localization, at 15 Hz, on a resource-constrained Jetson AGX Orin embedded platform.
暂无评论