Research on the Real-time Monitoring System of Cow’s Rumination

Shuang Zhang,Yu Zhang,Weizheng Shen,Lu Xu,Hao Wu,Zhongbin Su 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.7

Cow’s rumination is an important process of food digestion for dairy cows which is a valuable indicator during the cow management. By measuring the cow’s rumination time, it is capable to predict the cow’s estrus, and learn the cow’s health situation. This paper uses MSP430F149 processor with a sound sensor to achieve the design of real-time monitoring system for cow’s rumination. Since the system require high accuracy of the audio signal of the cow’s rumination, the ADC acquisition module and filtering and amplification process was made a special design. For the change of the spectral characteristics of the voice when cows ruminating, this paper designed the endpoint detection algorithm and sound sequence windowed function, and FFT transform is performed on the data in the Hamming window, and then do the frequency domain analysis to the audio of cow’s rumination. Comparing the sound spectrum collected from high precision recording instrument and this system, this system has done a good job in frequency and time domain. Applying the high precision recording instrument to the simulation experiment for cow’s rumination which conduct 50 sets of different time ranging, using this system to do the real-time monitoring, the mean error was 4.38, the R2 value is 0.877, the Pearson correlation was 0.936. This system performed accurate in the acquisition of the sound signal, and more accurately in identifying cows ruminating, and it can also provide effective means for the intelligent management of the pasture on cow’s health and breeding.

A Self-Powered RFID Sensor Tag for Long-Term Temperature Monitoring in Substation

Zhongbin Chen,Fangming Deng,Yigang He,Zhen Liang,Zhihui Fu,Chaolong Zhang 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.1

Radio frequency identification (RFID) sensor tag provides several advantages including battery-less operation and low cost, which are suitable for long-term monitoring. This paper presents a self-powered RFID temperature sensor tag for online temperature monitoring in substation. The proposed sensor tag is used to measure and process the temperature of high voltage equipments in substation, and then wireless deliver the data. The proposed temperature sensor employs a novel phased-locked loop (PLL)-based architecture and can convert the temperature sensor in frequency domain without a reference clock, which can significantly improve the temperature accuracy. A twostage rectifier adopts a series of auxiliary floating rectifier to boost its gate voltage for higher power conversion efficiency. The sensor tag chip was fabricated in TSMC 0.18㎛ 1P6M CMOS process. The measurement results show that the proposed temperature sensor tag achieve a resolution of 0.15 ℃ /LSB and a temperature error of -0.6/0.7 ℃ within the range from -30 ℃ to 70 ℃. The proposed sensor tag achieves maximum communication distance of 11.8 m.

Remote Monitoring of Heading Rice Growing and Nitrogen Content Based on UAV Images

Yu Zhang,Zhongbin Su,Weizheng Shen,Renshan Jia,Jiling Luan 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.7

Rice heading is the critical stage of the growth of rice, rice plants are relatively large, field canopy, poor resistance, and coincided with the high temperature and rainy weather, pests and diseases are more prone period. Therefore, the use of UAV to monitor the growth status of rice, easy to understand rice growth and nutritional status, in order to achieve high-quality, high yield, efficient purpose. This article is the field experiments under different nitrogen levels, using UAV monitoring multispectral images of rice, by reference remote sensing spectral indices, derived green normalized difference vegetation index (GNDVI) relative to other spectral index is more suitable for rice field biomass inversion modeling. At the same time, this study is based on the inversion model, implemented the rice growing and nitrogen content graded by ISODATA methods in ENVI. Achieved classification on rice growth and nitrogen remote sensing thematic map in ArcGIS, to provide timely and accurate information for rice seedling diagnosis and management decision, has reached the purpose of rice production precise management.

Intercomparison of ADC-Lite Images on UAV and TM Simulation Data for Soybean Leaf Area Index Retrieval

Qi Zhang,Zhongbin Su,Guijun Yang,Minghui Wang,Weizheng Shen,Xiaowei Teng,Jinhui Dong 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.7

Currently, TM images has a very high practical value and widely used in all aspects of agricultural. Unmanned Aerial Vehicles (UAV) remote sensing platform mounted ADC-Lite multi-spectral sensor has consistent channels response functions with TM sensor in TM2, TM3 and TM4, demonstrated to compete with TM sensor, due to low operational cost, high operational flexibility, high spatial resolution of imagery (0.018m with flight altitude 50m) and heterogeneity both at time and spatial-scale. In order to make sure whether it has widely used as TM sensor, moreover, the aim of this work is to assess ADC-Lite performance such as its adaptability and practicability. In this paper, ADC-Lite multi-spectral data, ground truth ASD hyperspectral and Leaf area index (LAI) data were acquired in soybean planting area, Jiaxiang County, Shandong Province on September18th, 2015. Since the ADC-Lite has different spatial scales with TM, this paper used TM simulation data transformed by ground truth ASD data, constructed LAI inversion model by empirical model based on two sensors and ground measured data, using 5 vegetation indices: ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil adjust vegetation index (SAVI), difference vegetation index (DVI) and triangular vegetation index (TVI). Determination coefficient R2, root mean square error (RMSE) and the estimation accuracy (EA) 3 indicators were acquired to assess the model. This work suggests that the established model of ADC-Lite sensor with TM simulation sensor has high consistency in accuracy. NDVI linear regression model derived from both of them presented a strong correlation with ground-measured LAI. It’s preliminarily shown that ADC-Lite images assess soybean LAI is feasible. This is anticipated to have tremendous implications that ADC-Lite can be made supplement for existing satellites, aerial and ground sensing, provide important information for Crop condition monitoring and critical data to support crop maturity, nutrition monitoring and fertilization management.

A Self-Powered RFID Sensor Tag for Long-Term Temperature Monitoring in Substation

Chen, Zhongbin,Deng, Fangming,He, Yigang,Liang, Zhen,Fu, Zhihui,Zhang, Chaolong The Korean Institute of Electrical Engineers 2018 Journal of Electrical Engineering & Technology Vol.13 No.1

Radio frequency identification (RFID) sensor tag provides several advantages including battery-less operation and low cost, which are suitable for long-term monitoring. This paper presents a self-powered RFID temperature sensor tag for online temperature monitoring in substation. The proposed sensor tag is used to measure and process the temperature of high voltage equipments in substation, and then wireless deliver the data. The proposed temperature sensor employs a novel phased-locked loop (PLL)-based architecture and can convert the temperature sensor in frequency domain without a reference clock, which can significantly improve the temperature accuracy. A two-stage rectifier adopts a series of auxiliary floating rectifier to boost its gate voltage for higher power conversion efficiency. The sensor tag chip was fabricated in TSMC $0.18{\mu}m$ 1P6M CMOS process. The measurement results show that the proposed temperature sensor tag achieve a resolution of $0.15^{\circ}C$/LSB and a temperature error of $-0.6/0.7^{\circ}C$ within the range from $-30^{\circ}C$ to $70^{\circ}C$. The proposed sensor tag achieves maximum communication distance of 11.8 m.

Characteristics of Cracks in two Paddy Soils and their Impacts on Preferential Flow

Xinhua Peng,Zhongbin Zhang 한국토양비료학회 2014 한국토양비료학회 학술발표회 초록집 Vol.2014 No.6

Research on UAV Remote Sensing Image Mosaic Method Based on SIFT

Yinjiang Jia,Zhongbin Su,Qi Zhang,Yu Zhang,Yunhao Gu,Zhongqiu Chen 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.11

UAV remote sensing, as a new method of remote sensing, has the characteristics of higher spatial resolution, fine timeliness and high flexibility. It is widely used in the field of natural disaster monitoring, urban planning, resource investigation, and has become one of the indispensable method of remote sensing data acquisition. However, because the UAV remote sensing platform is limited by the flight height and focal length of camera, the acquired image size is smaller, single image can’t cover the entire target area. Therefore, image mosaic has become a key technology to solve the problem. Image matching and image fusion are the key techniques of image mosaic. Due to the good robustness of image scaling, translation and rotation, this paper uses the SIFT algorithm to realize image matching of UAV. Since the feature extraction may produce false matches, RANSAC algorithm is applied to the feature point purification points. According to the seam-line in jointing overlap region, weighted fusion algorithm is applied to realize the image seamless splicing.

Hyperspectral Response of Rice Canopy and Prediction of Its Chlorophyll Content in Cold Regions

Jianqing Yuan,Zhongbin Su,Qingming Kong,Li Kang,Qi Zhang,Yu Zhang 보안공학연구지원센터 2015 International Journal of u- and e- Service, Scienc Vol.8 No.10

Based on field trials of different nitrogen levels, rice canopy chlorophyll content and canopy spectrum of its booting stage were respectively measured using the nitrogen balance index meter and the hyperspectral imager, in the Northeast of china. Analyzing the rice canopy spectral response characteristics under nitrogen gradient after canopy reflectance spectra were first extracted and filtered for noise, then the original reflectance spectra were transformed into the first derivative reflectance for further analysis. Stepwise analysis was carried out to select sensitive bands for canopy chlorophyll content by making correlation analysis and to build spectral indexes, and then chlorophyll content prediction models were generated and tested. After comparing, the two models with better estimation precision were the model with reflectivity at 572nm as a variable and the model with the index DSI(572,682) constructed the reflectivity at 572 and 682nm as a variable, the coefficients of determination R2 were 0.733 and 0.694, the root mean square errors RMSE were 2.9656 and 3.0346, and the relative errors RE% were 7.07% and 7.43%.

Design and Implementation of Livestock House Environmental Perception System Based on Wireless Sensor Networks

Weizheng Shen,Guanting Liu,Zhongbin Su,Rongyu Su,Yu Zhang 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.5

In order to monitor the six factors which is the most crucial influence on livestock production in livestock house, this paper designs a set of livestock house(LH) environmental perception system based on wireless sensor networks. This system is composed by a number of data acquisition nodes(DAN) connected by using Wireless Sensor Networks. Inside of DAN is equipped with six type of sensor which in charge of collecting Real-time environmental data in LH, including carbon dioxide sensor, ammonia gas sensor, illumination sensor, relative humidity sensor and so on. The communication mode between upper-computer and central node is GPRS, to research on remotely control environmental parameters in LH in the future. The upper-computer could treat data which is uploaded by several central nodes through some way, for example, data analysis based on established protocol, threshold judgment, etc. Then, the real-time data is stored by database. The stability and veracity of the system was verified by field tests which set technical grade monitors as control groups. Comparing with industrial-grade high precision monitoring instruments, the error of collecting data and wireless communication network is within normal error range, By SPSS, the result shows that there is no significant difference of P-Value(P>0.05) in different groups at same time.

SWIPT in MISO Full-Duplex Systems

Alexander Akpofure Okandeji,Muhammad R. A. Khandaker,Kai-Kit Wong,Gan Zheng,Yangyang Zhang,Zhongbin Zheng,Ruopeng Liu 한국통신학회 2017 Journal of communications and networks Vol.19 No.5

This paper investigates a multiuser multiple-input singleoutput(MISO) full-duplex (FD) system for simultaneous wirelessinformation and power transfer (SWIPT), in which a multiantennabase station (BS) simultaneously sends wirelessly informationand power to a set of single-antenna mobile stations (MSs) usingpower splitters (PSs) in the downlink and receives informationin the uplink in FD mode. In particular, we address the joint designof the receive PS ratio and the transmit power at the MSs, andthe beamforming matrix at the BS under signal-to-interferenceplus-noise ratio (SINR) and the harvested power constraints. Usingsemidefinite relaxation (SDR), we obtain the solution to theproblem with imperfect channel state information (CSI) of the selfinterferingchannels. Furthermore, we propose another suboptimalzero-forcing (ZF) based solution by separating the optimizationof the transmit beamforming vector and the PS ratio. Simulationresults are provided to evaluate the performance of the proposedbeamforming designs.