Intelligent Networked Things : The 6th Conference on Intelligent Networked Things, CINT 2024, Xi'an, China, May 18, 2024, Proceedings, Part II

• Autore: Zhang Lin
• Pubblicazione: Singapore : , : Springer Singapore Pte. Limited, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (0 pages)
• Altri autori: YuWensheng WangQuan LailiYuanjun LiuYongkui
• Nota di contenuto: Intro -- Preface -- Organization -- Contents - Part II -- Contents - Part I -- Artificial Intelligence for Intelligent Networked Things -- Application of Improved ResNet18 Based Neural Network for Non-invasive Blood Glucose Testing -- 1 Introductory -- 2 Deep Learning Based on ResNet18-SVM -- 2.1 Wavelet Transform -- 2.2 ResNet18 Deep Learning Network with SVM Fusion Approach -- 3 Experiment and Result Analysis -- 3.1 Data Acquisition Process -- 3.2 Regression Testing Process -- 3.3 Results Analysis -- 3.4 Conclusion -- References -- iKnowiSee: AR Glasses with Language Learning Translation System and Identity Recognition System Built Based on Large Pre-trained Models of Language and Vision and Internet of Things Technology -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Overall Framework and Implementation of AR Glasses Designed and Developed Based on Internet of Things Technology -- 3.2 Language Learning and Translation System -- 3.3 Identification System -- 4 Experiments -- 4.1 AR Glasses Entity -- 4.2 Language Learning and Translation System -- 4.3 Identification System -- 4.4 APP Design and Build -- 5 Conclusion -- References -- HM-W2V: Word Embedding from Hippocampus Spiking Neural Network -- 1 Introduction -- 2 Related Research -- 3 Model Structure -- 3.1 LIF Neuron -- 3.2 HM Embedding Layer -- 3.3 PR Module -- 4 Experimental Evaluation -- 4.1 Word Similarity -- 4.2 Document Classification -- 4.3 Threshold of LIF Neuron -- 5 Conclusion -- References -- Multi-target Intelligent Detection Method of Support Structure Defects Based on Digital Image Processing Technology -- 1 Introduction -- 2 Support Defect Target Detection Algorithm -- 2.1 Target Detection of Defective Support Structure Based on YOLOv5 Neural Network -- 2.2 Training and Validation -- 3 Support Defect Feature Extraction Algorithm. ; 3.1 Improved Gaussian Algorithm Combined with Histogram Equalization -- 3.2 Improved Adaptive Canny Algorithm Combined with Otsu -- 3.3 Crack Algorithm Based on Morphology -- 3.4 Defect Area Algorithm Based on Connected Component Labelling -- 4 Experiments and Results -- 4.1 Construction of Image Acquisition Hardware Platform -- 4.2 Defect Image Detection Experiment -- 5 Conclusion -- References -- Design of Calculation Algorithm for Edge Straight Line Accuracy of Metal Plate Based on Point Cloud Data -- 1 Introduction -- 2 Measurement and Data Preprocessing -- 2.1 Line Structured Light Ranging Theory -- 2.2 Point Cloud Data Preprocessing Algorithm Design -- 3 Straight Line Accuracy Calculation -- 4 Experiments and Results -- 4.1 The Composition of the Measurement System -- 4.2 Straight Line Accuracy Calculation Experimental Verification -- 5 Conclusion -- References -- Fault Diagnosis of Rolling Bearings Based on SVM and Improved D-S Evidence Theory for Multi-sensor Fusion -- 1 Introduction -- 2 SVM Theory -- 3 Improved D-S Evidence Theory -- 3.1 The Fusion of Evidence is Modified Based on the Lance Distance Function and the Spectral Angle Cosine Function -- 3.2 Case Analysis -- 4 Fault Diagnosis Model Based on SVM and Improved D-S Evidence Theory -- 5 Case Study Analysis -- 5.1 Experimental Setup -- 5.2 Data Acquisition and Feature Extraction -- 5.3 Fault Diagnosis -- 6 Conclusion -- References -- mmWave Radar Point Cloud Based Pose Estimation with Residual Blocks for Rehabilitation Exercise -- 1 Introduction -- 2 Related Work -- 3 mmWave Radar Sensing System -- 3.1 Data Acquisition -- 3.2 Data Preprocessing -- 4 Proposed Method -- 4.1 Model Design -- 4.2 Loss Function -- 5 Experimental Evaluations -- 5.1 Experimental Setup and Dataset -- 5.2 Model Setting and Training Details -- 5.3 Experimental Results -- 5.4 Ablation Study. ; 6 Limitations of the Proposed Method -- 7 Conclusions -- References -- Enhancing Repetitive Action Counting Through Hierarchical Transformer-Based Radar-Vision Fusion -- 1 Introduction -- 2 Related Work -- 2.1 Repetitive Action Counting -- 2.2 Radar-Vision Fusion Based Learning -- 3 Radar-Video Based Multi-modal Fusion Approach -- 3.1 Method Overview -- 3.2 Feature Extraction Module -- 3.3 Hierarchical Multi-modal Fusion Transformer -- 3.4 Period Predictor -- 4 Experiment Studies -- 4.1 Data Collection -- 4.2 Dataset Description -- 4.3 Experiment Setting -- 4.4 Experiment Results -- 5 Conclusion -- References -- Realizing Human Pose Estimation Based on Deep Kalman Filtering -- 1 Introduction -- 2 Related Work -- 2.1 Human Pose Estimation Based on Radar -- 2.2 Deep Kalman Filtering -- 3 mmWave Radar Sensing System -- 3.1 Data Acquisition -- 3.2 Data Processing -- 3.3 Overview of Our Method -- 4 Deep Kalman Filtering Method -- 4.1 Deep Kalman Filtering -- 5 Experimental Studies -- 5.1 Radar Configuration and Dataset -- 5.2 Experimental Results -- 6 Conclusion -- References -- A Multi-scale Feature Fusion Method for Demand Forecasting in Supply Chain Management -- 1 Introduction -- 2 Methods -- 3 Experiments -- 3.1 Data Preprocessing -- 3.2 Training Settings -- 3.3 Results -- 3.4 Ablation Study -- 4 Conclusion -- References -- Process Fault Diagnosis Based on Moving Window KECA and Random Forest -- 1 Introduction -- 2 Basic KECA and RF -- 3 Moving Window KECA-RF Fault Diagnosis Method -- 4 Simulation Results and Analysis -- 5 Conclusion -- References -- Intelligent Monitoring Method for Gear Grinding Machine Spindle Based on Multi-source Information Fusion -- 1 Introduction -- 2 Related Works -- 3 Overall Framework -- 4 Methodology -- 4.1 Spindle Vibration Signal Feature Extraction of Wavelet Packet Based on Sample Entropy. ; 4.2 Evaluation of Gear Grinding Machine State Based on Entropy Weight Method Improved D-S Evidence Theory -- 5 Experiment and Result -- 6 Conclusion -- References -- Research on Improving ResNet18 for Classifying Complex Images Based on Attention Mechanism -- 1 Introduction -- 2 The Method of This Article -- 2.1 Overall Model Structure Design -- 2.2 The Channel Attention Mechanism -- 2.3 The Spatial Convolution Attention Mechanism -- 3 Experiment and Analysis -- 3.1 Experimental Environment and Parameter Design -- 3.2 Experimental Dataset -- 3.3 Experimental Results and Analysis -- 3.4 Ablation Experiment -- 3.5 Classification Confusion Matrix -- 4 Conclusion -- References -- A Framework for Automated Generation of Transmission Processes Based on Kinetic Knowledge Mapping -- 1 Introduction -- 2 Related Works -- 3 Overall Framework -- 4 Methodology -- 4.1 Dynamic and Static Multimodal Transmission Domain Knowledge Graph Construction -- 4.2 Process Scheme Generation Based on Graph Cyclic Networks and Ant Colony Algorithm -- 5 Experiment and Result -- 6 Conclusion -- References -- Optimization and Decision in Intelligent Networked Things -- Intelligent Optimization Methods for Unmanned Cluster Delivery Support Task Allocation -- 1 Introduction -- 2 VRPTW Model Based on Unmanned Swarming -- 2.1 Description of the VRPTW Model Based on Unmanned Cluster Task Allocation -- 2.2 Mathematical Model of the VRPTW Based on Unmanned Delivery Platforms -- 3 Task Allocation Method Based on Genetic Algorithms -- 3.1 Encoding Design -- 3.2 Fitness Function -- 3.3 Genetic Operation Operator -- 4 Simulation and Experimental Verification -- 4.1 Introduction of the Example -- 4.2 Experimental Results and Analysis -- 5 Conclusion -- References -- Knowledge-Specific Reinforcement Learning for Job-Shop Scheduling with Dynamic Processing States in Disassembly Factory. ; 1 Introduction -- 2 Problem Description -- 2.1 Job-Shop Scheduling Problem -- 2.2 Disassembly Job-Shop with Dynamic Factors -- 3 Knowledge-Specific Dynamic Scheduling Method -- 3.1 Environment and Constraints -- 3.2 RL Interaction Design -- 3.3 Algorithm -- 4 Experiment -- 4.1 Experiment Configuration -- 4.2 Dynamic Job-Shop Scheduling with Unequal Probability Distributions -- 4.3 Dynamic Job-Shop Scheduling with Different MTBF -- 5 Conclusion -- References -- Implementation of Real-Time Robot Monitoring and Scheduling Platform in Cloud Manufacturing Environment -- 1 Introduction -- 2 Scheduling Model -- 2.1 Robot, Enterprise and Logistics -- 2.2 Task and Subtask -- 2.3 Constraints and Objectives -- 3 Requirements Analysis and Implementation -- 3.1 Requirements Analysis -- 3.2 Implementation -- 4 Deployment and Test -- 4.1 Deployment -- 4.2 Test -- 5 Conclusion -- References -- Multi-mission UAV Trajectory Planning in Smart Agriculture with Polarization Learning Model-Driven by Harris Hawks Optimizer -- 1 Introduction -- 2 Literature Review -- 3 Design and Optimization of the Harris Hawks Optimizer -- 3.1 Polarization Model-Based Diversity Enhancement Mechanism -- 3.2 Nonlinear Energy Parameter Optimization Mechanism -- 3.3 Random Spiral Perturbation Based Mutation Mechanism -- 4 Examination of the PL-HHO Algorithm -- 4.1 Experimental Parameters and Test Functions -- 4.2 Results and Analysis of Tests -- 5 Multi-mission UAV Trajectory Planning in Smart Agriculture -- 5.1 Mission Scale Setting -- 5.2 Multi-mission UAV Trajectory Planning Under Routine Conditions -- 5.3 Multi-mission UAV Trajectory Planning in Complex Conditions -- 6 Conclusion -- References -- Optimal Deception Attacks on Remote State Estimation with Heterogeneous Vulnerabilities -- 1 Introduction -- 2 Problem Formulation -- 2.1 Process Model -- 2.2 Smart Sensor and Remote Estimator. ; 2.3 False Data Detector.
• Titolo autorizzato: Intelligent Networked Things
• ISBN: 981-9739-48-9
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910872188103321
• Lo trovi qui: Univ. Federico II
• Serie: Communications in Computer and Information Science Series