Research on Aerobics Movement Choreography Based on Embedded Network Technology

2014 ◽  
Vol 556-562 ◽  
pp. 5685-5689 ◽  
Author(s):  
Li Lv
Keyword(s):  
Embedded System ◽  
Video Compression ◽  
Clustering Algorithm ◽  
Network System ◽  
Embedded Internet ◽  
Embedded Computer ◽  
Embedded Network ◽  
Compression Time ◽  
Teachers And Students ◽  
Communication Module

Embedded Internet has preset functions and strong adaptability, which can be used in household appliances, medical equipment, and industrial machinery and so on. Through the method of embedded network, it completely changed the way of people live. In this paper we use clustering algorithm to improve the embedded network system, and use JSP technology to enhance the real-time and interactive of system, develop the aerobics visualization movement system, which realizes the interactive action between teachers and students. In order to test the performance of the system, we use AMBE-2000 as communication module to test the video compression and processing functions of embedded system. The results show that the compression ratio is big, the flow is small, and compression time is short. It is a stable and reliable network system. It provides a new method for embedded computer system in sports teaching.

Design of an Intelligent Entrance Guard System with Multiple Identity Authentication

2013 ◽  
Vol 706-708 ◽  
pp. 1116-1119
Author(s):  
Hong He ◽  
Li Li ◽  
Zhi Hong Zhang
Keyword(s):  
Embedded System ◽  
Identity Authentication ◽  
Rfid Technology ◽  
Security And Protection ◽  
Multiple Identity ◽  
Camera Module ◽  
Communication Module

This paper has proposed a kind of intelligent entrance guard system, which is based on 32 bit ARM7TDMI embedded system combined with RFID technology. By expanding sound alarm, display and communication module inside, RF, camera module and fingerprint module outside, it can realize multiple identity authentication, so the security and protection ability of the entrance guard system get enhanced.

scholarly journals The Hyper-spectral Image Compression Based on K-Means Clustering and Parallel Prediction Algorithm*

2018 ◽  
Vol 173 ◽  
pp. 03071
Author(s):  
Wu Wenbin ◽  
Yue Wu ◽  
Jintao Li
Keyword(s):  
Image Compression ◽  
Clustering Algorithm ◽  
Compression Algorithm ◽  
Prediction Algorithm ◽  
Two Dimensional ◽  
Spectral Image ◽  
Compression Algorithms ◽  
Serial Processing ◽  
Compression Time ◽  
Hyper Spectral

In this paper, we propose a lossless compression algorithm for hyper-spectral images with the help of the K-Means clustering and parallel prediction. We use K-Means clustering algorithm to classify hyper-spectral images, and we obtain a number of two dimensional sub images. We use the adaptive prediction compression algorithm based on the absolute ratio to compress the two dimensional sub images. The traditional prediction algorithm is adopted in the serial processing mode, and the processing time is long. So we improve the efficiency of the parallel prediction compression algorithm, to meet the needs of the rapid compression. In this paper, a variety of hyper-spectral image compression algorithms are compared with the proposed method. The experimental results show that the proposed algorithm can effectively improve the compression ratio of hyper-spectral images and reduce the compression time effectively.

Status Monitoring and Fault Diagnosis Network System Based on UPnP

2007 ◽  
Vol 353-358 ◽  
pp. 2632-2635
Author(s):  
Pei Yu Li ◽  
Da Peng Tan ◽  
Tao Qing Zhou ◽  
Bo Yu Lin
Keyword(s):  
Fault Diagnosis ◽  
Embedded System ◽  
Real Time ◽  
Data Storage ◽  
Network Architecture ◽  
Network System ◽  
Time Data ◽  
Status Monitoring ◽  
Self Recognition ◽  
Real Time Data

Aiming at some problems in the fields of industry monitoring technology (IMT) such as bad dynamic ability and poor versatility, this paper brought forward a kind of intelligent Status monitoring and Fault diagnosis Network System (SFNS) based on UPnP-Universal Plug and Play. The model for fault diagnosis network system was established according to characteristics and requirements of IMT network, and system network architecture was designed and realized by UPnP. Using embedded system technology, real-time data collection node, monitoring center node and data storage server were designed, and that supplies powerful real-time data support for SFNS. Industry fields experiments proved that this system can realize self recognition, seamless linkage and other self adapting ability, and can break through the limitation of real IP address to achieve real-time remote monitoring on line.

scholarly journals Fractal Video Coding Using Fast Normalized Covariance Based Similarity Measure

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Ravindra E. Chaudhari ◽  
Sanjay B. Dhok
Keyword(s):  
Video Compression ◽  
Similarity Measure ◽  
Compression Ratio ◽  
Prediction Error ◽  
Experimental Result ◽  
Gray Level ◽  
Search Window ◽  
Target Level ◽  
Compression Time ◽  
Fractal Encoding

Fast normalized covariance based similarity measure for fractal video compression with quadtree partitioning is proposed in this paper. To increase the speed of fractal encoding, a simplified expression of covariance between range and overlapped domain blocks within a search window is implemented in frequency domain. All the covariance coefficients are normalized by using standard deviation of overlapped domain blocks and these are efficiently calculated in one computation by using two different approaches, namely, FFT based and sum table based. Results of these two approaches are compared and they are almost equal to each other in all aspects, except the memory requirement. Based on proposed simplified similarity measure, gray level transformation parameters are computationally modified and isometry transformations are performed using rotation/reflection properties of IFFT. Quadtree decompositions are used for the partitions of larger size of range block, that is, 16 × 16, which is based on target level of motion compensated prediction error. Experimental result shows that proposed method can increase the encoding speed and compression ratio by 66.49% and 9.58%, respectively, as compared to NHEXS method with increase in PSNR by 0.41 dB. Compared to H.264, proposed method can save 20% of compression time with marginal variation in PSNR and compression ratio.

Design and Implementation of Embedded System Based on Modbus TCP/IP

2012 ◽  
Vol 532-533 ◽  
pp. 667-671
Author(s):  
Yan Xia Li ◽  
Mo Li Zhang ◽  
Dan Mei Niu ◽  
Xiao Ling Zhang
Keyword(s):  
Embedded System ◽  
System Design ◽  
Communication System ◽  
Limited Resources ◽  
Network Communication ◽  
The Internet ◽  
Design And Implementation ◽  
Modbus Protocol ◽  
Embedded Network ◽  
Made In

It is the requirements of limited resources and realtime in embedded system. Design of network communication system based on embedded system is hard. In this paper, we propose the architecture of embedded network using Modbus TCP/IP protocol, analyze the composition of Modbus TCP/IP protocol. It is that Modbus protocol information can be made in the TCP/IP protocol of the Internet transmission, and thus extend the application of Modbus protocol. The network communication system is designed and implemented on the ARM platform using non-blanking socket in Linux. The system is available, stable and worthy of popularization.

scholarly journals Deep Learning-Based Embedded System for Carabao Mango (Mangifera Indica L.) Sorting

2019 ◽  
Vol 8 (2) ◽  
pp. 5456-5462
Keyword(s):  
Deep Learning ◽  
Embedded System ◽  
Mangifera Indica ◽  
Raspberry Pi ◽  
Single Shot ◽  
Embedded Computer ◽  
Quality Classification ◽  
Learning Techniques ◽  
Multiple Classification ◽  
Basic Quality

This paper presents the design and development of an embedded system for ‘Carabao’ or Philippine mango sorting utilizing deep learning techniques. In particular, the proposed system initially takes as input a top view image of the mango, which is consequently rolled over to evaluate every sides. The input images were processed by Single Shot MultiBox Detector (SSD) MobileNet for mango detection and Multi-Task Learning Convolutional Neural Network (MTL-CNN) for classification/sorting ripeness and basic quality, running on an embedded computer, i.e. Raspberry Pi 3. Our dataset consisting of 2800 mango images derived from about 270 distinct mango fruits were annotated for multiple classification tasks, namely, basic quality (defective or good) and ripeness (green, semi-ripe, and ripe). The mango detection results achieved a total precision score of 0.92 and a mean average precision (mAP) of over 0.8 in the final checkpoint. The basic quality classification accuracy results were 0.98 and 0.92, respectively, for defective and good quality, while the ripeness classification for green, ripe, and semi-ripe were 1.0, 1.0, and 0.91, respectively. Overall, the results demonstrated the feasibility of our proposed embedded system for image-based Carabao mango sorting using deep learning techniques.

System Design and Implementation of a Transient-Motion-Powered IoT Sensor Node

2020 ◽  
Author(s):  
Xin Li ◽  
Hong Tang ◽  
Junrui Liang
Keyword(s):  
Wireless Communication ◽  
Embedded System ◽  
Motion Detection ◽  
Sensor Node ◽  
Low Cost ◽  
Successful Implementation ◽  
Interface Circuit ◽  
Transient Motion ◽  
Communication Module ◽  
Self Powered

Abstract In this paper, we introduce ViPSN-E: a transient-motion-powered IoT sensor node. It carries out motion detection and wireless communication by making good use of the energy harvested from an instantaneous motion. In our design, a piezo-magneto-elastic structure, which is composed of a low-cost piezoelectric cantilever and a pair of magnets, is used to induce a plucking excitation and power generation under a transient and one-way movement. An energy management circuit, which is composed of a self-powered synchronized switch harvesting on inductor (SP-SSHI) interface circuit and a voltage regulator is utilized for efficient energy conversion. Through the sophisticated collaboration between mechatronic design and computer program, the motion information can also be identified and sent out by a wireless communication module. The cyber-electromechanical synergy among mechanical dynamics, power conditioning circuit, and the low-power embedded system is emphasized towards the successful implementation of such a motion-powered IoT device. The prototyped ViPSN-E has done a good job by making good use of the energy associated with each transient plucking motion. With only one plucking excitation, the system can realize motion detection and several rounds of wire-less transmission. The study on ViPSN-E provides valuable guidance towards the self-powered ubiquitous motion-sensing systems.

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