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Design of multi-sensors Cooperation Control System for Intelligent Building

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Energy and Power Engineering 2017年第4期9卷 495-502页

作者： Qi-Jiao He Lin Ye School of Power and Energy Northwestern Polytechnical University Xi’an 710072 China

This paper presents a design of intelligent building control system based on multi-sensors. In order to achieve comfort, low carbon and energy conservation for buildings. The design uses STC89C52 chip, combined with monitoring data of Pyroelectric infrared microwave dual sensor, temperature sensors and light sensors to control the optical system, the temperature control system and the security system. It helps to achieve low carbon and energy conservation. In addition, the energy-saving effect of a medium-sized multimedia classroom was analyzed. We analyze the feasibility of the system. It is proved that the system is low cost, high yield and easy to operate, with strong engineering application value.

关键词： Intelligent Building multi-sensors Control System STC89C52

A novel three-dimensional indoor localization algorithm based on multi-sensors

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A novel three-dimensional indoor localization algorithm base...

Integrated sensor system for monitoring rice growth conditions based on unmanned ground vehicle system

第四届中国卫星导航学术年会

作者： Zhifeng Li Zhongliang Deng Wenlong liu Lianming Xu Institute of EE Beijing University of Post and Telecommunication

With the wildly application of the mobile internet, the market of location-based services is growing rapidly. At present, the main current method of indoor location is based on the finger point position technology of wireless local area network （WLAN）, and combined with a fusion algorithm of pedestrian dead reckoning （PDR）. Furthermore, due to the spread characteristics of Wi-Fi signal, there are some weak signal zones and even blind zones. This paper proposes a novel indoor localization algorithm. The algorithm combines the multi-finger point technology, geomagnetic navigation and inertial navigation, and uses the advantages of each technology to complement each other, to achieve the series, seamless, and three dimensions indoor location. Through the algorithm simulation and contrast analysis of experiment, the algorithm given in this paper has showed that the average positioning accuracy has improved nearly 37%, the average positioning error can reach 2.72m and the new algorithm has a 100% coverage area rates in comparison with KNN\W-KNN\PDR and their fusion algorithm, which has proved the feasibility and effectiveness of this new fusion algorithm.

关键词： multi-sensors fusion algorithm high-precision

来源： cnki会议评论

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International Journal of Agricultural and Biological Engineering 2014年第2期7卷 75-81页

作者： Wang Pei Yubin Lan Luo Xiwen Zhou Zhiyan Zhigang Wang Yonghui Wang South China Agricultural University Key La boratory of Key Technology on Agricultural Machine and EquipmentMinistry of EducationGuangzhou 510642China USDA-ARS AATRU3103 F&B RoadCollege StationTX 77845USA Prairie View A&M University Prairie ViewTX77446USA

Ground-based platform systems provide a good tool for monitoring and managing crop conditions in precision agriculture applications and have been widely used for monitoring crop *** develop an unmanned ground vehicle system(UGVS)based multi-sensors and test the feasibility of this system for monitoring rice conditions,an UGVS was developed to collect real-time rice condition information including NDVI values,reflectance measurements and crop canopy temperature in this *** components of the integrated system are GreenSeeker R100 system,hyper-spectroradiometer and infrared temperature *** leaf area index(LAI)was measured by the CGMD302 *** Independent Samples T-Test method and the one way ANOVA method were used to determine the best spectral indices and analyze the relationship between the vegetation indices and rice *** was found that the two best spectral indices for estimating LAI were NDVI(860 nm and 750 nm)with the correlation coefficient(R^(2))at 0.745 and RVI(853 nm and 751 nm)with the R^(2)at *** results show the UGVS can support multi-source information acquisition and is useful for crop management and precision agriculture applications.

关键词： unmanned ground vehicle system(UGVS) multi-sensors rice growth condition spectral vegetation indices leaf area index(LAI)

Registration algorithm for sensor alignment based on stochastic fuzzy neural network

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Journal of Systems Engineering and Electronics 2005年第1期16卷 134-139页

作者： LiJiao JingZhongliang HeJiaona WangAn DepartmentofAutomaticControl NorthwesternPolytechnicalUniversityXi'an710072P.R.China InstitureofAerospaceInformationandControl SchoolofElectroniceandInformationTechnologyShanghaiJiaotongUniversityShanghai200030P.R.China DepartmentofAutomaticControl NorthwesternPolytechnicalUniversityXi'an710072P.R.China

multiple sensor registration is an important link in multi-sensors data fusion. The existed algorithm is all based on the assumption that system errors come from a fixed deviation set. But there are many other factors, which can result system errors. So traditional registration algorithms have limitation. This paper presents a registration algorithm for sensor alignment based on stochastic fuzzy neural network (SNFF), and utilized fuzzy clustering algorithm obtaining the number of fuzzy rules. Finally, the simulative result illuminate that this way could gain a satisfing result.

关键词： multi-sensors registration fuzzy clustering stochastic fuzzy neural network.

Comparative spatio-spectral heterogeneity analysis using multispectral and hyperspectral airborne images

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Geo-Spatial Information Science 2013年第2期16卷 83-90页

作者： QIU Bingwen ZENG Canying CHEN Chongcheng Key Laboratory of Spatial Data Mining&Information Sharing of Ministry of Education Spatial Information Research Centre of Fujian ProvinceFuzhou University 523 Gongye RoadFuzhou 350002China

Knowledge of spatio-spectral heterogeneity within multisensor remote sensing images across visible,near-infrared and short wave infrared spectra is *** now,little comparative research on spatio-spectral heterogeneity has been conducted on real multisensor images,especially on both multispectral and hyperspectral airborne *** this study,four airborne images,Airborne Thematic Mapper,Compact Airborne Spectrographic Imager,Specim AISA Eagle and AISI Hawk hyperspectral airborne images of woodland and heath landscapes at Harwood,UK,were applied to quantify and evaluate the differences in spatial heterogeneity through semivariogram *** revealed that spatial heterogeneity of multisensor airborne images has a close relationship with spatial and spectral resolution and *** the visible,near-infrared spectra and short wave infrared spectra,greater spatial heterogeneity is generally observed from the relatively longer wavelength in short wave infrared *** are dramatic changes across the red and red edge spectra,and the peak value is generally examined in the red middle or red edge wavelength across the visible and near-infrared spectra for vegetation or non-vegetation landscape *** all,for real multisensor airborne images,the change in spatial heterogeneity with spatial resolution will accord with the change of support theory depending on whether dramatic change exists across the corresponding ***,if with close spatial resolution,the spatial heterogeneity of multispectral images might be far from the overall integration of these bands from the hyperspectral images involved.A comparative assessment of spatio-spectral heterogeneity using real hyperspectral and multispectral airborne images provides practical guidance for designing the placement and width of a spectral band for different applications and also makes a contribution to the understanding of how to reconcile spatial patterns generated by m

关键词： variogram modelling spatio-spectral heterogeneity ATM CASI Eagle Hawkairborne imagery multi-sensors

Target Priority Determination Methods by Interval-Valued Intuitionistic Fuzzy Sets with Unknown Attribute Weights

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Journal of Shanghai Jiaotong university(Science) 2017年第5期22卷 624-632页

作者：徐公国段修生吕豪 Department of Electronic and Optical Engineering Ordnance Engineering College Department of Automation University of Science and Technology of China

The paper aims at the problem of multi-targets threat degree being hard to be evaluated accurately in complex air defense battlefield environments. Combined with multi-sensors information fusion and interval-valued intuitionistic fuzzy sets(IVIFS) theories, the target priority determination is studied. The score and accuracy functions of IVIFS are improved with thinking about the hesitating information in order to increase the ***, the influence factors of target priority and the nonlinear relationship between the influence factors and target priority are analyzed. Next, the algorithms for calculating the factor weights and sensor weights are given. Based on the theory of IVIFS and technique for order preference by similarity to an ideal solution(TOPSIS), two methods of target priority determination based on the IVIFS and TOPSIS are proposed. At last, an application example verifies the effectiveness and flexibility of the proposed algorithms.

关键词： target priority interval-valued intuitionistic fuzzy set(IVIFS) multi-sensors information fusion score and accuracy functions

Monitoring Land-Use Change in Nakuru (Kenya) Using multi-Sensor Satellite Data

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Advances in Remote Sensing 2012年第3期1卷 74-84页

作者： Kenneth Mubea Gunter Menz Center for Remote Sensing of Land surfaces (ZFL) University of Bonn Bonn Germany Remote Sensing Research Group (RSRG) University of Bonn Bonn Germany

Recently land-use change has been the main concern for worldwide environment change and is being used by city and regional planners to design sustainable cities. Nakuru in the central Rift Valley of Kenya has undergone rapid urban growth in last decade. This paper focused on urban growth using multi-sensor satellite imageries and explored the potential benefits of combining data from optical sensors (Landsat, Worldview-2) with Radar sensor data from Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data for urban land-use mapping. Landsat has sufficient spectral bands allowing for better delineation of urban green and impervious surface, Worldview-2 has a higher spatial resolution and facilitates urban growth mapping while PALSAR has higher temporal resolution compared to other operational sensors and has the capability of penetrating clouds irrespective of weather conditions and time of day, a condition prevalent in Nakuru, because it lies in a tropical area. Several classical and modern classifiers namely maximum likelihood (ML) and support vector machine (SVM) were applied for image classification and their performance assessed. The land-use data of the years 1986, 2000 and 2010 were compiled and analyzed using post classification comparison (PCC). The value of combining multi-temporal Landsat imagery and PALSAR was explored and achieved in this research. Our research illustrated that SVM algorithm yielded better results compared to ML. The integration of Landsat and ALOS PALSAR gave good results compared to when ALOS PAL- SAR was classified alone. 19.70 km2 of land changed to urban land-use from non-urban land-use between the years 2000 to 2010 indicating rapid urban growth has taken place. Land-use information is useful for the comprehensive land-use planning and an integrated management of resources to ensure sustainability of land and to achieve social Eq- uity, economic efficiency and environmental sustainabi

关键词： Land-Use Monitoring Nakuru Urban Growth multi-sensors Satellite Data Maximum Likelihood Support Vector Machine Post Classification Comparison Sustainability

Estimation of Land Use Changes in Tan Rai Bauxite Mine by multi-Variants Change Vector Analysis (MCVA) on multi-Temporal Remote Sensing Data

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Journal of Geoscience and Environment Protection 2020年第3期8卷 70-84页

作者： Nguyen Thanh Hoan Hoa Thuy Quynh Le Minh Hang Nguyen Manh Ha Hoang Thi Huyen Ngoc Dang Xuan Phong Institute of Geography Vietnam Academy of Science and Technology Hanoi Vietnam Graduate University of Science and Technology Vietnam Academy of Science and Technology Hanoi Vietnam Le Quy Don Technical University Hanoi Vietnam

The Tan Rai Bauxite Project, which exploits a large bauxite mine in Lam Dong province, Vietnam has been in operation since 2012. In addition to the economic efficiency of the project, bauxite mining and processing uses a large area arable land and affect the regional environment. Remote sensing technology is increasingly widely used in many purposes in monitoring the changes of environment and resources, including land use change with high accuracy, giving managers more information to monitor the exploitation and use process of land resource. This study used a Change Vector Analysis (CVA) method of analysis on various remote sensing data sources to monitor the process of land exploitation and restoration of the Tan Rai Bauxite project. High-resolution remote sensing images were used as diverse as SPOT-5, VNREDSat-1, Google Earth from 2013 to 2019 to demonstrate the ability of the MCVA method to combine many other types of remote sensing images together. The results of fluctuation analysis were validated by 200 random points in the study area, and the accuracy of result is more than 90%. The results of land use change statistics were also compared with the annual data of Tan Rai Bauxite Factory. From this study, it can be concluded that the MCVA analysis method can quickly detect land use change areas and can combine many different image sources with a high accuracy. In addition, it also provides statistics of mining areas and restored areas, thereby assisting managers in monitoring the operation of the mine.

关键词： Bauxite Tan Rai MCVA Land Use Change Monitoring multi-sensors