Design and Simulation of Portable Data Terminal for Agriculture Equipment

2013 ◽  
Vol 336-338 ◽  
pp. 383-387
Author(s):  
Yan Xin Yin ◽  
Yu Tan ◽  
Shu Mao Wang
Keyword(s):  
Communication Protocol ◽  
Absolute Error ◽  
Wireless Sensor ◽  
Error Measurement ◽  
Average Absolute Error ◽  
Wireless Communication Protocol ◽  
Data Acquisition Software ◽  
Terminal Design ◽  
Data Terminal ◽  
Reliability And Availability

A portable data terminal design based on wireless sensor network was came up for agriculture equipment working status monitor, a JN5139 module was used as the hardware core of the terminal and Zigbee as the wireless communication protocol. Effect caused by time-delay and pocket loss was simulated and analyzed with Truetime1.5 under matlab, data acquisition software was developed according to the simulation that effectively reduced the influence. Error measurement test showed the analog average absolute error was 6.33mv and frequency average absolute error was 0.56Hz, that indicated the reliability and availability in agriculture application.

Design of Tungsten Tailing Reservoir Safety Monitoring and Warning System Based on Wireless Sensor Networks and LabVIEW

2013 ◽  
Vol 427-429 ◽  
pp. 1268-1271
Author(s):  
Xue Wen He ◽  
Ying Fei Sheng ◽  
Kuan Gang Fan ◽  
Le Ping Zheng ◽  
Qing Mei Cao
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Communication Protocol ◽  
Warning System ◽  
Safety Monitoring ◽  
Wireless Sensor ◽  
Serial Port ◽  
Rf Transceiver ◽  
New Type

In view of the existing flaws of traditional manual observations, a new type of tailing reservoir safety monitoring and warning system based on ZigBee and LabVIEW was designed. The system chose SoC chip CC2530 as the RF transceiver and designed the low-power wireless sensor networks nodes to collect and process the data of tailing reservoir. It chose ZigBee 2007 as the network communication protocol, and uploaded the data to PC by RS232 serial port. The monitoring and warning interface of PC was completed with LabVIEW. The testing results show that the data transmission of the network is stable and the system is suitable for real-time monitoring and warning of the tungsten tailing reservoir.

Design and Application of the Indoor Environment Monitoring & Control System at Tianjin First Central Hospital

2013 ◽  
Vol 380-384 ◽  
pp. 635-638
Author(s):  
Chen Chen
Keyword(s):  
Control System ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Indoor Environment ◽  
Communication Protocol ◽  
Automatic Monitoring ◽  
Wireless Sensor ◽  
Environment Monitoring ◽  
Human Beings ◽  
Central Hospital

With advance of our human beings science and technology and enhance of the living standards, more and more people have addressed higher requirements on the environmental conditions in a hospital, therefore, the traditional and no-intelligent monitoring devices are being replaced by the automated and networked monitoring systems gradually. In this case, application of the wireless sensor network just fits this need. This paper proposes the Tianjin First Central Hospital indoor environment monitoring & control system of distributed acquisition and execution, and centralized management by focusing on the needs for the technical indicators of the hospital indoor environment. During design of the system, an universal design concept was put forward, and also a non-standard communication protocol for the wireless sensor network designed independently in combination with the OSI open standard. In this paper, realization of the communication protocol among the nodes with embedded software and the operation mechanism of the modes themselves are discussed, also a console panel has been developed for the data center. Several software design algorithms are proposed with respect to the network layout. This paper also describes the test platform of the Tianjin First Central Hospital indoor environment monitoring & control system established with the network components designed, and provides the test and verification results, including the monitored data of the various gases, corresponding automatic control functions, and underlay BER analysis. The results show that this system can basically realize automatic monitoring on the Tianjin First Central Hospital indoor environment. At present, the sensitive gases include CO, CO2, O2, NH3 and formaldehyde, sensitive environments temperature, humidity and light intensity, and controlled targets ventilation and lighting. This paper offers an optional solution for environment monitoring and has certain theoretical value and engineering significance.

Application Research of Wireless Communication Technology in Remote Meter Reading System

2014 ◽  
Vol 513-517 ◽  
pp. 1494-1498 ◽  
Author(s):  
Zhang Hong ◽  
Jun Jie Wang ◽  
Ai Sheng Ma
Keyword(s):  
Circuit Design ◽  
Test Results ◽  
Application Research ◽  
Remote Transmission ◽  
Zigbee Technology ◽  
Design Requirements ◽  
Terminal Design ◽  
Reading System ◽  
Hardware Circuit ◽  
Data Terminal

In view of the problems in the current domestic and international remote wireless meter reading system, propose the remote wireless meter reading terminal system based on ZigBee technology combined with GPRS technology, carry out the hardware circuit design of each module, establish ZigBee wireless meter reading network based on 802.15.4 layer networking protocol, design a more practical remote wireless meter reading protocol and data transmission format. Test results show that it has realized the formation of ZigBee network, collection and remote transmission of meter data, terminal equipment parameters modification and other functions to achieve the terminal design requirements.

scholarly journals Hidden Semi-Markov Models for Predictive Maintenance

2015 ◽  
Vol 2015 ◽  
pp. 1-23 ◽  
Author(s):  
Francesco Cartella ◽  
Jan Lemeire ◽  
Luca Dimiccoli ◽  
Hichem Sahli
Keyword(s):  
Markov Models ◽  
Real Data ◽  
Information Criterion ◽  
Absolute Error ◽  
Predictive Maintenance ◽  
Average Absolute Error ◽  
Current State ◽  
Automatic Model Selection ◽  
State Duration ◽  
Useful Lifetime

Realistic predictive maintenance approaches are essential for condition monitoring and predictive maintenance of industrial machines. In this work, we propose Hidden Semi-Markov Models (HSMMs) with (i) no constraints on the state duration density function and (ii) being applied to continuous or discrete observation. To deal with such a type of HSMM, we also propose modifications to the learning, inference, and prediction algorithms. Finally, automatic model selection has been made possible using the Akaike Information Criterion. This paper describes the theoretical formalization of the model as well as several experiments performed on simulated and real data with the aim of methodology validation. In all performed experiments, the model is able to correctly estimate the current state and to effectively predict the time to a predefined event with a low overall average absolute error. As a consequence, its applicability to real world settings can be beneficial, especially where in real time the Remaining Useful Lifetime (RUL) of the machine is calculated.

scholarly journals Cost Effectual Distributed Cooperative Cluster based Communication Protocol in Wireless Sensor Network

2020 ◽  
Vol 8 (6) ◽  
pp. 5652-5656
Keyword(s):  
Communication Protocol ◽  
Wireless Sensor ◽  
Team Leaders ◽  
Great Strength ◽  
Second Stage ◽  
Remote Sensor ◽  
Channel Distortion ◽  
Two Stages ◽  
Intense Research

Theoretical energy recognition in remote sensor systems has received intense research interest in the late years. Radio variation, channel distortion, and blockage bring great strength and responsiveness to packets broadcast over a remote channel. A twin innovation is effective communication that can drastically increase the channel range and reduce transmission vigor consumption in disrupting channel. Growth in the direct range brings with it a reduced fault rate. In this paper, an acceptable correspondence method is proposed for each tab with active sending and receiving clusters. It consists of two stages, the precise routing phase, the selective and transmitting stage. In the routing phase, the basic route between the source and the sink hub is started. In the second stage, centers of fundamental development toward flattering team leaders select additional touch centers with minimal biomass costs from their surroundings, and then spread from bundle to cluster to the recently established endurance cluster. Reductions in error rate and regeneration are proven by the fact that malpractice funds become long-term obligation systems.

scholarly journals Study of a Privacy Preserving Logistic Regression Algorithm (PPLRA) For Data Privacy in the Context of Big Data

2021 ◽  
Vol 2083 (3) ◽  
pp. 032059
Author(s):  
Qiang Chen ◽  
Meiling Deng
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
Privacy Protection ◽  
Data Privacy ◽  
Absolute Error ◽  
Average Absolute Error ◽  
Regression Algorithms ◽  
Hadoop Platform ◽  
Logistic Regression Algorithm ◽  
Computing Speed

Abstract Regression algorithms are commonly used in machine learning. Based on encryption and privacy protection methods, the current key hot technology regression algorithm and the same encryption technology are studied. This paper proposes a PPLAR based algorithm. The correlation between data items is obtained by logistic regression formula. The algorithm is distributed and parallelized on Hadoop platform to improve the computing speed of the cluster while ensuring the average absolute error of the algorithm.

scholarly journals Short-Term Traffic Flow Forecasting Model Based on GA-TCN

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Rongji Zhang ◽  
Feng Sun ◽  
Ziwen Song ◽  
Xiaolin Wang ◽  
Yingcui Du ◽  
...  
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Convolutional Neural Network ◽  
Traffic Flow ◽  
Absolute Error ◽  
Forecasting Model ◽  
Average Absolute Error ◽  
Short Term ◽  
Traffic Flow Forecasting ◽  
Fitness Value

Traffic flow forecasting is the key to an intelligent transportation system (ITS). Currently, the short-term traffic flow forecasting methods based on deep learning need to be further improved in terms of accuracy and computational efficiency. Therefore, a short-term traffic flow forecasting model GA-TCN based on genetic algorithm (GA) optimized time convolutional neural network (TCN) is proposed in this paper. The prediction error was considered as the fitness value and the genetic algorithm was used to optimize the filters, kernel size, batch size, and dilations hyperparameters of the temporal convolutional neural network to determine the optimal fitness prediction model. Finally, the model was tested using the public dataset PEMS. The results showed that the average absolute error of the proposed GA-TCN decreased by 34.09%, 22.42%, and 26.33% compared with LSTM, GRU, and TCN in working days, while the average absolute error of the GA-TCN decreased by 24.42%, 2.33%, and 3.92% in weekend days, respectively. The results indicate that the model proposed in this paper has a better adaptability and higher prediction accuracy in short-term traffic flow forecasting compared with the existing models. The proposed model can provide important support for the formulation of a dynamic traffic control scheme.

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