• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.9-15
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• 2021

In this paper, the Embedded MEMS system to the power apparatus used Edge Impulse machine learning tools and therefore an improved predictive system design is implemented. The proposed MEMS embedded system is developed based on nRF52840 system and the sensor with 3-Axis Digital Magnetometer, I2C interface and magnetic measurable range ±120 uT, BM1422AGMV which incorporates magneto impedance elements to detect magnetic field and the ARM M4 32-bit processor controller circuit in a small package. The MEMS embedded platform is consisted with Edge Impulse Machine Learning and system driver implementation between hardware and software drivers using SensorQ which is special queue including user application temporary sensor data. In this paper by experimenting, TensorFlow machine learning training output is applied to the power apparatus for analyzing the status such as "Normal, Warning, Hazard" and predicting the performance at level of 99.6% accuracy and 0.01 loss.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.366-373
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• 2007

In this paper we propose a multi-channel speech pickup system for calling quality enhancement of hands-free communication using ALTERA Nios-II processor. Multi-channel speech pickup system uses Delay-and-Sum beamformer with zero-padding interpolator. This paper implements speech pickup system using the Nios-II processor with real-time I/O data processing speed. The proposes speech pickup embedded system shows a good agreement with those of computer simulation(MATLAB) and conventional DSP processor(TMS320C6711) result. The proposed method is effective more than previous methods in cost and design processing time. As a result, LE(Logic Element) of hardware used 3,649/5,980(61%) on a chip.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.149-155
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• 2007

In this paper, we propose an real-time implementation of JPEG2000 codec on the ARM9 processor. The implemented codec is designed to separate control codes from data management codes in order to use effectively the system resources such as processor and memory. Especially, in embedded situations like cellular phones it is very important to provide good services using limited processor and internal memory. Since ARM9 series processors do not provide floating-point, large amount of computational time is required to perform the operation which needs highly repetitive floating-point computations like DWT(discrete wavelet transform). The proposed codec was programed using fixed-point to overcome this weakness. Also code optimization considering cache memory was applied to further improve the computational speed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.4
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• pp.315-324
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• 2005

VOD(video on demand) is a video service by users' order, that is, a video service on demand. That means the users can select and watch the video content that has been saved on sewer, out of broadcasting in the usual process like TV. At present the client of VOD system bases on PC. As the PC-based client uses the software MPEG decoder, the main processor specification has an effect on the capacity. Also people, who don't know how to use their PC, cannot be provided the VOD service. The purpose of this paper is to show the process of the development the VOD client system Into the embedded type with hardware MPEG-4 decoder. The main processor is the SC1200 of x86 Family in National Semiconductor with a built-in video processor and the memory is 128Mbyte SDRAM. Also, in order that the VOD service can be provided using the Internet, the Ethernet controller is included. As the hardware MPEG-4 decoder is used in the embedded VOD client system, which is developed, it can make the low capacity of the main processor. Therefore it is able to be developed as a low-price system. The embedded VOD client system is easy for anyone to control easily with the remote control and can be played through TV.

• Journal of Korea Multimedia Society
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• v.13 no.9
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• pp.1322-1328
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• 2010

Recently, keyword spotting system is greatly in the limelight as UI(User Interface) technology of ubiquitous home network system. Keyword spotting system is vulnerable to non-stationary noises such as TV, radio, dialogue. Especially, speech recognition rate goes down drastically under the embedded DSP(Digital Signal Processor) environments because it is relatively low in the computational capability to process input speech in real-time. In this paper, we propose a new keyword spotting system using the call-command method, which is consisted of small number of recognition networks. We select the call-command such as 'narae', 'home manager' and compose the small network as a token which is consisted of silence with the noise and call commands to carry the real-time recognition continuously for input speeches.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.420-425
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• 2009

In this paper, image detection and recognition algorithms are studied with respect to embedded carrier system. There are many suggested techniques to detect and recognize objects. But they have the propensity to need much calculation for high hit rate. Advanced and modified method needs to study for embedded systems that low power consumption and real time response are requested. The proposed methods were implemented using Intel(R) Open Source Computer Vision Library provided by Intel Corporation. And they run and tested on embedded system using a ARM920T processor by cross-compiling. They showed 1.6sec response time and 95% hit rate and supported the automated moving carrier system smoothly.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.225-229
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• 2005

We have designed micro-fuel processor system, which consists of a steam reforming area and a PROX(preferential oxidation) area. Micro-fuel processor system generates $H_2$ rich gas from a methanol. In our experiment, we have integrated micro-fuel processor system using low temperature cofired ceramics (LTCC) process because LTCC is superior to other materials principally due to their high thermal and chemical stability, simpler fabrication processes, and lower materials cost. Therefore, we have studied and integrated micro-fuel processor system containing embedded heaters, cavities, and 3D structures of micro-channel with LTCC. Also we have optimized the LTCC process.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.651-654
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• 2005

In this paper, we designed ECC(Elliptic Curve Cryptographic) Processor with Bus-splitting mothod for embedded SoC. ECC SIP is designed by VHDL RTL modeling, and implemented reusably through the procedure of logic synthesis, simulation and FPGA verification. To communicate with ARM9 core and SIP, we designed SIP bus functional model according to AMBA AHB specification. The design of ECC Processor for platform-based SoC is implemented using the design kit which is composed of many devices such as ARM9 RISC core, memory, UART, interrupt controller, FPGA and so on. We performed software design on the ARM9 core for SIP and peripherals control, memory address mapping and so on.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.13-19
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• 2011

In this paper, a visual surveillance system using SOPC based NIOS II embedded processor and C2H compiler was implemented. In this system, the IP is constructed by C2H compiler for the output of the camera images, image processing, serial communication and network communication, then, it is implemented to effectively control each IP based on the SOPC and the NIOS II embedded processor. And, an algorithm which updates the background images for high speed and robust detection of the moving objects is proposed using the Adaptive Gaussian Mixture Model(AGMM). In results, it can detecte the moving objects(pedestrians and vehicles) under day-time and night-time. It is confirmed that the proposed AGMM algorithm has better performance than the Adaptive Threshold Method(ATM) and the Gaussian Mixture Model(GMM) from our experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.201-206
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• 2004

This study attempted to develop a speech recognition module applied to a wheelchair for the physically handicapped. In the proposed speech recognition module, TMS320C32 was used as a main processor and Mel-Cepstrum 12 Order was applied to the pro-processor step to increase the recognition rate in a noisy environment. DTW (Dynamic Time Warping) was used and proven to be excellent output for the speaker-dependent recognition part. In order to utilize this algorithm more effectively, the reference data was compressed to 1/12 using vector quantization so as to decrease memory. In this paper, the necessary diverse technology (End-point detection, DMA processing, etc.) was managed so as to utilize the speech recognition system in real time