Flexible embedded system for sensor integration and custom data processing in an automotive application

Author(s):  
L. Guedria ◽  
D. Hubaux ◽  
M. Ocãna ◽  
J.-D. Legat
Micromachines ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1450
Author(s):  
Xiang Wang ◽  
Zhun Zhang ◽  
Qiang Hao ◽  
Dongdong Xu ◽  
Jiqing Wang ◽  
...  

The hardware security of embedded systems is raising more and more concerns in numerous safety-critical applications, such as in the automotive, aerospace, avionic, and railway systems. Embedded systems are gaining popularity in these safety-sensitive sectors with high performance, low power, and great reliability, which are ideal control platforms for executing instruction operation and data processing. However, modern embedded systems are still exposing many potential hardware vulnerabilities to malicious attacks, including software-level and hardware-level attacks; these can cause program execution failure and confidential data leakage. For this reason, this paper presents a novel embedded system by integrating a hardware-assisted security monitoring unit (SMU), for achieving a reinforced system-on-chip (SoC) on ensuring program execution and data processing security. This architecture design was implemented and evaluated on a Xilinx Virtex-5 FPGA development board. Based on the evaluation of the SMU hardware implementation in terms of performance overhead, security capability, and resource consumption, the experimental results indicate that the SMU does not lead to a significant speed degradation to processor while executing different benchmarks, and its average performance overhead reduces to 2.18% on typical 8-KB I/D-Caches. Security capability evaluation confirms the monitoring effectiveness of SMU against both instruction and data tampering attacks. Meanwhile, the SoC satisfies a good balance between high-security and resource overhead.


2016 ◽  
Vol 6 ◽  
pp. 28 ◽  
Author(s):  
M. Steininger ◽  
C. Stephan ◽  
C. Böhm ◽  
F. Sauer ◽  
R. Zink

Motivated by the hype around driverless cars and the challenges of the sensor integration and data processing, this paper presents a model for using a XBox One Microsoft Kinect stereo camera as sensor for mapping the surroundings. Today, the recognition of the environment of the car is mostly done by a mix of sensors like LiDAR, RADAR and cameras. In the case of the outdoor delivery challenge Robotour 2016 with model cars in scale 1:5, it is our goal to solve the task with one camera only. To this end, a three-stage approach was developed. The test results show that our approach can detect and locate objects at a range of up to eight meters in order to incorporate them as barriers in the navigation process.


2014 ◽  
Vol 543-547 ◽  
pp. 2766-2769 ◽  
Author(s):  
Cheng Po Mu ◽  
Qing Xian Dong ◽  
Jie Lian ◽  
Ming Song Peng

Edge detection that is an important means to realize image segmentation has important application significance in image processing, industrial detection, artificial intelligence and the target recognition field. As the demand for real-time and rapidity in image processing, the embedded image processing technology has been widely applied. But the realization of real-time edge detection for image requires a large amount of data processing, limited system resources of embedded system is the main reason of the embedded image processing technology development. In order to shorten time embedded systems edge detection processing large amounts of data, based on adaptive threshold Canny algorithm, this paper as the FPGA data processing DSP chips and made a FPGA + DSP hardware architecture, effectively improve the system real-time, get a good edge detection results.


Author(s):  
Igal Bilik ◽  
Shahar Villeval ◽  
Daniel Brodeski ◽  
Haim Ringel ◽  
Oren Longman ◽  
...  

Author(s):  
S. Y. Zheng ◽  
L. Gui ◽  
X. N. Wang ◽  
D. Ma

In order to meet the demand of real-time spatial data processing and improve the online processing capability of photogrammetric system, a kind of real-time photogrammetry method is proposed in this paper. According to the proposed method, system based on embedded architecture is then designed: using FPGA, ARM+DSP and other embedded computing technology to build specialized hardware operating environment, transplanting and optimizing the existing photogrammetric algorithm to the embedded system, and finally real-time photogrammetric data processing is realized. At last, aerial photogrammetric experiment shows that the method can achieve high-speed and stable on-line processing of photogrammetric data. And the experiment also verifies the feasibility of the proposed real-time photogrammetric system based on embedded architecture. It is the first time to realize real-time aerial photogrammetric system, which can improve the online processing efficiency of photogrammetry to a higher level and broaden the application field of photogrammetry.


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