Note: Intro -- ICAIT-2019 Organization -- ICAIT2019 International Advisory Board and Program Committee -- Preface -- Contents -- About the Editors -- Part IInvited Papers -- 1 Vegetable Distribution System Using Machine Learning Approach -- 1.1 Introduction -- 1.2 Current Technologies -- 1.2.1 Fujitsu Akisai -- 1.2.2 Toshiba FoodCaster Ex -- 1.2.3 NEC "IT-Aided Mikan Production" -- 1.3 Proposed Approach -- 1.4 Conclusion -- References -- 2 A Purpose of a Smart Vegetable Garden Model Based on Paraconsistent Annotated Evidential Logic Eτ -- 2.1 Introduction -- 2.2 Smart Garden -- 2.3 Paraconsistent Logic -- 2.4 Paraconsistent Annotated Evidential Logic Eτ -- 2.5 Algorithm Para-analyzer -- 2.6 Proposing the Model -- 2.7 Conclusion -- References -- 3 Paraconsistent Artificial Neural Network Applied to Agribusiness -- 3.1 Introduction -- 3.2 Soybean -- 3.3 Methodology -- 3.4 Paraconsistent Artificial Neural Network -- 3.5 Applications in Agribusiness -- 3.6 Results and Discussion -- References -- Part IIRegular Papers -- 4 Research and Design on an Automatic Control System Using in Antarctic Greenhouse -- 4.1 Introduction -- 4.2 Designing Architecture of Greenhouse Automatic Control System -- 4.3 Control Scheme -- 4.3.1 Greenhouse Environmental Data Collection -- 4.3.2 Ambient Temperature Control Based on Fuzzy Logic -- 4.3.3 Light Control -- 4.3.4 Water and Fertilizer Control -- 4.4 System Implementation and Application -- 4.5 Conclusion -- References -- 6 Correlation Research on the Structure of the Apple Tree Vigor and Its Fruit Quality -- 6.1 Introduction -- 6.2 Materials and Experiments -- 6.3 Results and Analysis -- 6.3.1 Correlation Between Indicators of Crown Diameter, Crown Height, Trunk Girth, and Hardness of the Fruit -- 6.3.2 Correlation Research Between the Trunk Girth and the Soluble Sugar. , 6.3.3 Correlation Research Between the Structure of Tree Vigor and Soluble Solids -- 6.4 Conclusions -- References -- 7 Real-Time Data Transmission Design of Unmanned Aerial Vehicle Gamma Spectrometer -- 7.1 Introduction -- 7.2 Data Transmission Overall Structure Design -- 7.2.1 Time Base -- 7.2.2 Digital Multi-channel Data Transmission -- 7.2.3 IPC Program Data Processing -- 7.2.4 Data Transmission Between Drones and Ground Control Platforms -- 7.2.5 Ground Control Platform Data Transmission -- 7.3 System Test -- 7.4 Conclusion -- References -- 8 0.8 GHz Low-Noise Amplifier Design -- 8.1 Introduction -- 8.2 Low-Noise Amplifier Design Flow -- 8.3 Research and Design of Matching Networks -- 8.3.1 Selection of Impedance Points -- 8.3.2 Matching Network Design -- 8.3.3 LNA Production Debugging and Analysis -- 8.3.4 Circuit Debugging and Analysis -- 8.4 Conclusions -- References -- 9 Optimization Analysis of Laying Length of Thin-Wall Micro-Spray Belt Under Different Slope Conditions -- 9.1 Introduction -- 9.2 Analysis on Allowable Laying Length of Micro-Spray Belt -- 9.2.1 Allowable Head Deviation in Lateral Pipe -- 9.2.2 The Formula of the Head Loss Along the Micro-Spray Belt -- 9.2.3 Pressure of Micro-Spray Belt at Any Point Under Different Slopes -- 9.3 Relative Pressure at Any Point Under Different Slopes -- 9.4 The Maximum Laying Length Under Different Slopes -- 9.4.1 Determination of the Laying Length of Micro-Spray Belt During Flat Slope -- 9.4.2 Determination of Laying Length of Micro-Spray Belt in Adverse Slope -- 9.4.3 Determination of Laying Length of Micro-Spray Belt in Down Slope -- 9.5 Laying Length Analysis -- 9.5.1 Calculation of Head Deviation and Deviation Rate -- 9.5.2 Calculation of Laying Length for Different Slope -- 9.6 Conclusions -- References -- 10 L-Band Ultra-Wideband Low-Noise Amplifier Design -- 10.1 Introduction. , 10.2 Parallel Negative Feedback Amplifier Circuit Analysis -- 10.3 L-Band Ultra-Wideband Low-Noise Plifier Design -- 10.3.1 The Role of VSWR Circles in Matching Networks -- 10.3.2 Single-Supply Bias Circuit Design -- 10.3.3 Negative Feedback Structure Optimization Simulation -- 10.3.4 Design Matching Network Based on Equal VSWR Circle -- 10.4 Circuit Testing and Analysis -- 10.5 Conclusions -- References -- 11 Research on Pipe Surface Defect Recognition Based on Convolutional Neural Network -- 11.1 Introduction -- 11.2 The Classification of Pipe Surface Defect -- 11.3 Design of Pipeline Surface Defect Identification Model -- 11.3.1 The Structure of GoogLeNet Model -- 11.3.2 Improved GoogLeNet Network Structure -- 11.4 Tests and Results -- 11.5 Conclusion -- References -- 12 Research on the Method of Tea Disease Recognition Based on Deep Learning -- 12.1 Introduction -- 12.2 Making Tea Disease Data Set -- 12.2.1 Sample Collection of Tea Diseases -- 12.2.2 Expansion of Tea Disease Samples -- 12.2.3 Production of Tea Disease Data Set -- 12.3 Performance Optimization of Tea Disease Classification and Recognition Model Based on Transfer Learning -- 12.3.1 Merge BN Layer to Convolution Layer -- 12.3.2 L2 Regularization -- 12.4 Pre-training and Transfer Training -- 12.5 Experimental Tests and Results -- References -- 13 A Research on Tea Traceability Consensus Mechanism Based on Blockchain Technology -- 13.1 Introduction -- 13.2 Problems in Traceability of Tea Application -- 13.2.1 Production and Circulation Model of Tea Industry Chain -- 13.2.2 Application of Blockchain Technology in Tea Traceability -- 13.3 Optimization of the Consensus Mechanism in a Tea Traceability System -- 13.3.1 Analysis of Consensus Flow of dBFT Algorithm -- 13.3.2 Improvement of C-dBFT Consensus Mechanism Based on Credit Rewards and Punishments. , 13.3.3 Credit Reward and Punishment Mechanism -- 13.3.4 Hierarchical Analysis for Selecting Consensus Nodes -- 13.4 Experiments and Analysis -- 13.4.1 Modeling Experiment -- 13.4.2 Verification of Results and Conclusion -- References -- 14 The Research on the Judgment Method for Porcine Abnormal Diet Based on Improved PSO-SVDD -- 14.1 Introduction -- 14.2 The Judgment of Porcine Abnormal Diet Based on SVDD -- 14.3 The Parameter Optimization of SVDD Based on PSO -- 14.4 Experimental Results and Analysis -- 14.4.1 The Comparison Results of Decision Function Before and After Improvement -- 14.4.2 The Judgment Results for Porcine Abnormal Diet Data Based on Improved PSO-SVDD -- 14.5 Conclusions -- References -- 15 The Design of Two-Channel Outputs Switching Mode Power Supply Based on TOP100Y -- 15.1 Introduction -- 15.2 Scheme Selection -- 15.2.1 Basic Regulator Regulating Circuit -- 15.2.2 Circuit TOP Power Supply -- 15.3 System Structure and Working Mode -- 15.4 Transformer Design -- 15.5 Experimental Results and Analysis -- References -- 16 Design of Data Acquisition System for ASA Test -- 16.1 Basic Ideas -- 16.2 Design Scheme -- 16.2.1 The Hardware Design -- 16.2.2 Software Design -- 16.3 Verification and Analysis of VI Curve Acquisition -- 16.3.1 ASA Testing of Typical Components -- 16.3.2 ASA Test of Analog Circuit -- 16.4 Conclusion -- References -- 17 Raman Perception Monitoring Application of IoT Technology in Agricultural Planting -- 17.1 Introduction -- 17.1.1 Characteristics of Raman Spectrometer -- 17.1.2 Application and Advantages of Raman Spectrometer in Agricultural IoT -- 17.2 Implementation Case -- 17.2.1 RamanPerception Monitoring IoT System Design -- 17.2.2 Establish an Integrated Agricultural Management System and APP -- 17.3 Development and Prospects -- References. , 18 Visible and Infrared Image Fusion Based on Masked Online Convolutional Dictionary Learning with Frequency Domain Computation -- 18.1 Introduction -- 18.2 Proposed Fusion Framework -- 18.2.1 Masked Online Convolutional Dictionary Learning Using Frequency Domain Computation -- 18.2.2 Fusion Method -- 18.3 Experiment and Discussion -- 18.4 Conclusion -- References -- 20 Intelligent Greenhouse Information Collection and Control System Based on Internet of Things -- 20.1 Introduction -- 20.2 System Design -- 20.2.1 System Objective -- 20.2.2 General System Architecture -- 20.3 System Implementation -- 20.3.1 System Hardware Implementation -- 20.3.2 Software Design of the System Lower Computer -- 20.3.3 Key Code Implementation -- 20.4 System Highlights-Remote Control -- 20.5 Conclusion -- References -- 21 Design and Key Technology Research of Civil-Military Integration Regulations and Standards Management System -- 21.1 Introduction -- 21.2 Overall Design -- 21.2.1 Functional Requirement -- 21.2.2 System Framework -- 21.2.3 Presentation Layer Design -- 21.2.4 Functional Design -- 21.2.5 Data Layer Design -- 21.3 Key Technology Research -- 21.3.1 Support Process Consolidation and Splitting -- 21.3.2 Support Document Version Control -- 21.3.3 Support Process Page Customization -- 21.4 Conclusion -- References -- 22 A Reliable Wireless Monitor and Control System with Low Power for Greenhouse Microclimate -- 22.1 Introduction -- 22.2 Realization Principles -- 22.3 Wireless Monitoring and Control System for Greenhouse Microclimate -- 22.4 Experiments -- 22.4.1 Experimental Scheme -- 22.4.2 Results and Analysis -- 22.5 Conclusions -- References -- 23 Prediction of Excessive Cadmium in Rice Based on Weighted Bayesian Fusion Model -- 23.1 Introduction -- 23.2 Related Work -- 23.3 Proposed Method -- 23.3.1 Bayes -- 23.3.2 Naive Bayes. , 23.3.3 Weighted Naive Bayesian Fusion Model.