Intelligence of Things : The Second International Conference on Intelligence of Things (ICIT 2023), Ho Chi Minh City, Vietnam, October 25-27, 2023, Proceedings, Volume 2

• Autore: Dao Nhu-Ngoc
• Pubblicazione: Cham : , : Springer, , 2023; ©2023
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (368 pages)
• Altri autori: ThinhTran Ngoc NguyenNgoc Thanh
• Nota di contenuto: Intro -- Preface -- Organization -- Contents -- AIoT Services and Applications -- Investigating Ensemble Learning Methods for Predicting Water Quality Index -- 1 Introduction -- 2 Methodology -- 2.1 Decision Tree -- 2.2 Bagging (Bootstrapped Aggregating) -- 2.3 Random Forest -- 2.4 Extra Trees -- 2.5 Adaptive Boosting -- 2.6 XGBoost (eXtreme Gradient Boosting) -- 3 Experiments and Results -- 3.1 Data Description -- 3.2 Metrics to Evaluate the Performance of ML Models -- 3.3 The Performance of Ensemble Methods on Predicting the WQI -- 4 Conclusions -- References -- Age-Invariant Face Recognition Based on Self-Supervised Learning -- 1 Introduction -- 2 Related Works -- 2.1 Age-Invariant Face Recognition -- 2.2 Self-Supervised Learning in Face Recognition -- 3 Methods -- 3.1 Data Augmentation -- 3.2 Age-Invariant Face Recognition Models -- 3.3 Self-Supervised Learning -- 4 Experimental Results -- 4.1 Experiment Setup -- 4.2 Experimental Results -- 5 Conclusion -- References -- Detection of Kidney Stone Based on Super Resolution Techniques and YOLOv7 Under Limited Training Samples -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Dataset -- 3.2 Convolutional Block Attention Module -- 3.3 Single Image Super Resolution Techniques -- 3.4 The Proposed Re-Designed YOLOv7 Architecture -- 4 Experimental Results -- 4.1 Environment and Hyperparameters Setup -- 4.2 Evaluation Results -- 5 Conclusion -- References -- Hardware-Based Lane Detection System Architecture for Autonomous Vehicles -- 1 Introduction -- 2 Related Work -- 3 Proposed Hough Transform Hardware Design Architecture -- 4 Proposed Design Verification -- 5 Conclusions -- References -- Video Classification Based on the Behaviors of Children in Pre-school Through Surveillance Cameras -- 1 Introduction -- 2 Related Works -- 3 The BCiPS Dataset -- 3.1 Dataset Creation. ; 3.2 Dataset Analysis -- 4 Baseline Models -- 4.1 CNN+LSTM (ConvLSTM2D) -- 4.2 CNN+SVM -- 4.3 CNN+Random Forest -- 4.4 TimeSformer -- 4.5 MoViNets -- 4.6 (2+1)D Resnet-18 -- 4.7 EfficientNetB0 -- 5 Results -- 5.1 Results of Baseline Models -- 5.2 Error Analysis -- 6 Conclusion-Future Works -- References -- Land Subsidence Susceptibility Mapping Using Machine Learning in the Google Earth Engine Platform -- 1 Introduction -- 2 Study Area -- 3 Materials and Methods -- 3.1 Methods -- 3.2 Materials -- 4 Results and Discussions -- 5 Conclusions -- References -- Building an AI-Powered IoT App for Fall Detection Using Yolov8 Approach -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Network Architecture -- 3.2 Fall Detection Work Flow -- 3.3 Performance Metrics -- 4 Implementation and Result -- 4.1 Data -- 4.2 Comparison Result of Different YOLOv5 Models over 100 Epochs -- 4.3 Fall Detection Web Application Using Streamlit -- 5 Discussion and Conclusion -- References -- Seam Puckering Level Classification Using AIoT Technology -- 1 Introduction -- 2 Background and Related Works -- 3 Methodology -- 3.1 Framework Architecture -- 3.2 Custom Dataset -- 3.3 Models for Seam Puckering Level Classification -- 3.4 System Implementation -- 4 Result and Evaluation -- 4.1 Result -- 4.2 Evaluation -- 5 Discussion, Conclusion, and Future Works -- References -- Classification of Pneumonia on Chest X-ray Images Using Transfer Learning -- 1 Introduction -- 2 Related Works -- 3 Dataset and Methods -- 3.1 Dataset -- 3.2 Proposed Method -- 4 Experimental Results -- 5 Conclusions -- References -- Bayesian Approach for Static Object Detection and Localization in Unmanned Ground Vehicles -- 1 Introduction -- 2 Methodologies -- 2.1 Detecting Algorithms -- 2.2 Noise Reducing and Navigating Procedures -- 2.3 Sensor's Fusion and Target Localization. ; 3 Experiment and Prelim Results -- 3.1 Simulation Environment -- 3.2 Onsite Testing -- 4 Conclusion and Future Work -- References -- Diabetic Retinopathy Diagnosis Leveraging Densely Connected Convolutional Networks and Explanation Technique -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Preprocessing -- 3.2 Data Augmentation -- 3.3 Architectures for Classification -- 3.4 Grad-CAM for Output Visualization From the Trained Model -- 4 Experimental Results -- 4.1 Datasets -- 4.2 Evaluation Metrics -- 4.3 Scenarios -- 4.4 Result Summary and Comparison with Some Previous Studies -- 5 Conclusion -- References -- Deep Learning Approach for Inundation Area Detection Using Sentinel Data -- 1 Introduction -- 2 Methodology and Dataset -- 2.1 Methodology -- 2.2 Dataset -- 3 Prelim Results -- 4 Conclusion -- References -- Classification of Raisin Grains Based on Ensemble Learning Techniques in Machine Learning -- 1 Introduction -- 2 Problem and Data -- 3 Research Methodology -- 3.1 Existing Methods -- 3.2 Proposed Method -- 3.3 Data Preprocessing -- 3.4 Experimental Settings -- 4 Results -- 5 Conclusion -- References -- An Effective Deep Learning Model for Detecting Plant Diseases Using a Natural Dataset for the Agricultural IoT System -- 1 Introduction -- 2 Related Work -- 3 Background -- 3.1 Data Augmentation Methods -- 3.2 Datasets -- 3.3 CNN Architecture -- 4 The Proposed Model -- 5 Conclusions -- References -- Real-Time Air Quality Monitoring System Using Fog Computing Technology -- 1 Introduction -- 2 Background and Related Works -- 3 Methodology -- 3.1 System Design -- 3.2 Pollution Parameters Selection -- 3.3 Data Acquisition Module -- 3.4 Communication Module -- 3.5 Fog Computing Module -- 4 Implementation and Evaluation -- 4.1 Implementation -- 4.2 Evaluation -- 5 Discussion, Conclusion, and Future Works -- References. ; An Intelligent Computing Method for Scheduling Projects with Normally Distributed Activity Times -- 1 Introduction -- 2 Project Scheduling with Crisp Activity Duration Times Using Approach Based on Linear Programming -- 2.1 Program Evaluation and Review Technique: Some Fundamental Definitions and Concepts -- 2.2 Scheduling Projects Using Linear Programming -- 3 Schedule Project with Normally Distributed Activity Times Using an Approach Based on Fuzzy Linear Programming -- 3.1 Solving a Class of Stochastic Programming Problems Using Fuzzy Linear Programming -- 3.2 Computing the Project Completion Time when Project Activity Duration Times are Random Variables following Normal Distributions -- 3.3 Finding Critical Activities when Project Activity Duration Times are Random Variables following Normal Distributions -- 4 Concluding Observations -- References -- Security and Privacy -- An Improved Hardware Architecture of Ethereum Blockchain Hashing System -- 1 Introduction -- 2 Proposed Ethash Hardware Architecture -- 2.1 The Architecture of Ethash -- 2.2 The Architecture of Keccak256_2stage -- 2.3 The Architecture of Main_Loop -- 3 Implementation Results -- 3.1 Keccak Implementation Result -- 3.2 Ethash Implementation Result -- 4 Conclusion -- References -- CSS-EM: A Comprehensive, Secured and Sharable Education Management System for Schools -- 1 Introduction -- 2 Blockchain -- 2.1 Overview -- 2.2 Substrate -- 3 Proposed Scorechain System -- 3.1 Scorechain System Overview -- 3.2 A Comprehensive University Management System -- 3.3 High Secure Data Management Through a Hierarchical Role Assignment Mechanism -- 3.4 Multiple Universities' High Secure Privacy and Data-Sharing Platform -- 4 System Implementation -- 5 Discussion -- 6 Conclusion -- References -- A High-Speed Barret-Based Modular Multiplication with Bit-Correction for the CRYSTAL-KYBER Cryptosystem. ; 1 Introduction -- 2 The Preliminary Background -- 2.1 Barret Reduction Method -- 2.2 K-RED/K2-RED Reduction Method -- 3 The Proposed Design -- 4 Implementation Result -- 5 Conclusion -- References -- Securing Digital Futures: Exploring Decentralised Systems and Blockchain for Enhanced Identity Protection -- 1 Introduction -- 2 Centralized and Decentralized Identity Models -- 2.1 Definition -- 2.2 Process -- 2.3 Practical Applications -- 2.4 Advantages -- 2.5 Disadvantages -- 2.6 Decentralized Identity Model -- 3 Preliminaries of Blockchain-Based Digital Identity Management System -- 3.1 Blockchain Technology -- 3.2 AI and OCR Technologies -- 3.3 Zero-Knowledge Proof and Smart Contracts -- 4 Proposed System Model and Processes for Managing Privacy Attributes -- 4.1 Scheme Overview -- 4.2 User Registration -- 4.3 Identity Verification -- 4.4 Authentication in Digital Identity Decentralized System on Blockchain -- 4.5 Access Control -- 5 Conclusion and Future Work -- 5.1 Conclusion -- 5.2 Future Work -- References -- Enhancing Blockchain Interoperability Through Sidechain Integration and Valid-Time-Key Data Access Control -- 1 Introduction -- 2 Related Works -- 3 Proposed System -- 3.1 Blockchain -- 3.2 Sidechain -- 3.3 Valid Time Key - VTK -- 3.4 Cross-Chain Data Transfer -- 4 Experiments and Results -- 4.1 Performance Evaluation -- 4.2 Security Analysis -- 5 Conclusions and Future Work -- References -- An IoT Attack Detection Framework Leveraging Graph Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Graph Neural Networks (GNNs) -- 4 Data Preparation -- 4.1 Datasets -- 4.2 Data Acquisition and Integration -- 4.3 Data Preprocessing -- 4.4 Feature Selection -- 5 GraphSage-Based Attack Classification Framework -- 6 Performance Evaluation and Discussion -- 7 Conclusion -- References -- Network Attack Detection on IoT Devices Using 2D-CNN Models. ; 1 Introduction.
• Titolo autorizzato: Intelligence of Things
• ISBN: 3-031-46749-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910754096603321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes on Data Engineering and Communications Technologies Series