A review and analysis of communication logic between PL and PS in ZYNQ AP SoC

Ramagond, Sunita; Yellampalli, Siva; Kanagasabapathi, C.

doi:10.1109/smarttechcon.2017.8358511

Cited by 13 publications

(2 citation statements)

References 2 publications

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“…In these boards, the PL segment and the ARM processor are connected by an AXI bus. As a result, certain parts of the system can be implemented as logic circuits in the PL segment and other components can run as PS applications [37]. Using PL and PS parts, Ali Altuncu et al [38] implemented a real-time image processing system on Xilinx boards.…”

Section: Real-time Embedded Systemsmentioning

confidence: 99%

Real-Time Activity Recognition and Intention Recognition Using a Vision-based Embedded System

Darafsh,

Ghidary,

Zamani

2021

Preprint

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With the rapid increase in digital technologies, most fields of study include recognition of human activity and intention recognition, which are essential in smart environments. In this study, we equipped the activity recognition system with the ability to recognize intentions by affecting the pace of movement of individuals in the representation of images. Using this technology in various environments such as elevators and automatic doors will lead to identifying those who intend to pass the automatic door from those who are passing by. This system, if applied in elevators and automatic doors, will save energy and increase efficiency. For this study, data preparation is applied to combine the spatial and temporal features with the help of digital image processing principles. Nevertheless, unlike previous studies, only one AlexNet neural network is used instead of two-stream convolutional neural networks. Our embedded system was implemented with an accuracy of 98.78% on our intention recognition dataset. We also examined our data representation approach on other datasets, including HMDB-51, KTH, and Weizmann, and obtained accuracy of 78.48%, 97.95%, and 100%, respectively. The image recognition and neural network models were simulated and implemented using Xilinx simulators for the Xilinx ZCU102 board. The operating frequency of this embedded system is 333 MHz, and it works in real-time with 120 frames per second (fps).

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Section: Real-time Embedded Systemsmentioning

confidence: 99%

Real-Time Activity Recognition and Intention Recognition Using a Vision-based Embedded System

Darafsh,

Ghidary,

Zamani

2021

Preprint

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“…It is an all programmable SOC to combine both hardware and software in to single device, and provides high performance, flexibility, scalability, low power. Zedboard has Processing System (PS) [2] and Programmable Logic (PL) [3]. Dual-core ARM CORTEX A9 is the Processing system which operates at 1 GHZ.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Embedded Audio System based on Zynq-SOC

Vissampalli¹,

Kodali²

2019

IJITEE

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Nowadays smart world requires, Embedded audio system with optimum design metrics for smart applications in various fields like smart car, intelligent systems and Robotics etc. This paper describes the Design and implementation of embedded Audio system for real-time applications on SOC-FPGA with optimized design metrics (low power, low-cost, low development time, low area, high speed). An electret microphone / line in are used to feed the audio input. An audio codec from Analog devices named ADAU1761 which is integrated on the zynq-7020 board. In the proposed embedded audio system, the block design in Vivado2017.2 has been modeled with VHDL; application software developed using C language in SDK2017.2. This Audio system is the optimized solution for a wide range of smart applications.

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