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Table of Contents
Intro
Welcome Message from AINA-2023 Organizers
Organization
AINA-2023 Keynote Talks
Blockchain and IoT Integration: Challenges and Future Directions
Toward Sustainable, Intelligent, Secure, Fully Programmable, and Multisensory (SENSUOUS) Networks
Contents
Next Generation Mobile Sensors: Review Regarding the Significance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors
1 Introduction
2 Proper Management of Sensitive Private Data
2.1 Demographic Data
2.2 Sensors that Detect Movement
3 Study of Human Behaviour
3.1 Motion Sensors
4 Body Features and Health Parameters
4.1 Motion Sensors
4.2 Remarks Concerning the Touchscreen
4.3 Mobile Applications, Location and Network
5 Conclusions and Open Research Avenues
References
Simulation Modeling of Human Aortic Valve Blood Flow
1 Introduction
2 Modelling Methodology
2.1 Construction of a Closed Valve in Pathologies
2.2 Construction of a Opened Valve in Pathologies
2.3 Simulation of Blood Flow
3 Conclusion
References
An Integrated System for Vibration Suppression Using Fuzzy Control and 2D-LiDAR
1 Introduction
2 Proposed System
2.1 Proposed System Structure and 3D Measurement
2.2 Fuzzy Control for Vibration Suppression
3 Experimental Results
4 Conclusions
References
Prediction in Smart Environments and Administration: Systematic Literature Review
1 Introduction
2 Systematic Literature Review Planning
2.1 Research Questions
2.2 Search Strategy
2.3 Selection Criteria
2.4 Data Collection
3 Results and Discussion
3.1 Introduction
3.2 RQ1: Did Prediction Solutions Integrate an Administration Element?
3.3 RQ2: What Are the Prediction Methods Applied in the Smart Environment and Administration in a Data-Series Case?
3.4 Learned Lesson
4 Conclusion
References
Protect Trajectory Privacy in Food Delivery with Differential Privacy and Multi-agent Reinforcement Learning
1 Introduction
2 Related Work
3 Background
3.1 Multi-agent Reinforcement Learning
3.2 Trajectory Protection
3.3 Differential Privacy
4 Problem Statement
4.1 Model Overview
4.2 DRL Formulation
5 Methodology
5.1 QMIX Algorithm
5.2 Protect Trajectory Privacy in Food Delivery with Multi-agent Reinforcement Learning
6 Experiment Design
6.1 Protect Trajectory in Food Delivery (PTFD)
6.2 Data Set Description
7 Experiment Results
7.1 Trajectory Similarity and Data Utility
8 Conclusion
References
Enhanced Machine Learning-Based SDN Controller Framework for Securing IoT Networks
1 Introduction
2 Related Work
3 Methodology
3.1 Software and Hardware Environment
3.2 SDN Architecture
3.3 Proposed ML-SDN Framework
4 Simulation Results
4.1 Evaluation Fundamental
4.2 Results
Welcome Message from AINA-2023 Organizers
Organization
AINA-2023 Keynote Talks
Blockchain and IoT Integration: Challenges and Future Directions
Toward Sustainable, Intelligent, Secure, Fully Programmable, and Multisensory (SENSUOUS) Networks
Contents
Next Generation Mobile Sensors: Review Regarding the Significance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors
1 Introduction
2 Proper Management of Sensitive Private Data
2.1 Demographic Data
2.2 Sensors that Detect Movement
3 Study of Human Behaviour
3.1 Motion Sensors
4 Body Features and Health Parameters
4.1 Motion Sensors
4.2 Remarks Concerning the Touchscreen
4.3 Mobile Applications, Location and Network
5 Conclusions and Open Research Avenues
References
Simulation Modeling of Human Aortic Valve Blood Flow
1 Introduction
2 Modelling Methodology
2.1 Construction of a Closed Valve in Pathologies
2.2 Construction of a Opened Valve in Pathologies
2.3 Simulation of Blood Flow
3 Conclusion
References
An Integrated System for Vibration Suppression Using Fuzzy Control and 2D-LiDAR
1 Introduction
2 Proposed System
2.1 Proposed System Structure and 3D Measurement
2.2 Fuzzy Control for Vibration Suppression
3 Experimental Results
4 Conclusions
References
Prediction in Smart Environments and Administration: Systematic Literature Review
1 Introduction
2 Systematic Literature Review Planning
2.1 Research Questions
2.2 Search Strategy
2.3 Selection Criteria
2.4 Data Collection
3 Results and Discussion
3.1 Introduction
3.2 RQ1: Did Prediction Solutions Integrate an Administration Element?
3.3 RQ2: What Are the Prediction Methods Applied in the Smart Environment and Administration in a Data-Series Case?
3.4 Learned Lesson
4 Conclusion
References
Protect Trajectory Privacy in Food Delivery with Differential Privacy and Multi-agent Reinforcement Learning
1 Introduction
2 Related Work
3 Background
3.1 Multi-agent Reinforcement Learning
3.2 Trajectory Protection
3.3 Differential Privacy
4 Problem Statement
4.1 Model Overview
4.2 DRL Formulation
5 Methodology
5.1 QMIX Algorithm
5.2 Protect Trajectory Privacy in Food Delivery with Multi-agent Reinforcement Learning
6 Experiment Design
6.1 Protect Trajectory in Food Delivery (PTFD)
6.2 Data Set Description
7 Experiment Results
7.1 Trajectory Similarity and Data Utility
8 Conclusion
References
Enhanced Machine Learning-Based SDN Controller Framework for Securing IoT Networks
1 Introduction
2 Related Work
3 Methodology
3.1 Software and Hardware Environment
3.2 SDN Architecture
3.3 Proposed ML-SDN Framework
4 Simulation Results
4.1 Evaluation Fundamental
4.2 Results