This book presents advances on the state of the art in smart cities systems and applications based on the proof of concept and prototyping for smart cities in an interdisciplinary context of engineering and information sciences. Smart cities have emerged as highly complex technological endeavors that combine knowledge and technology from many disciplines ranging from information sciences to engineering. Due to their complex nature, the modeling, development, and prototyping of applications in smart cities present a myriad of challenges, including technical, economic, and social ones, across application subdomains such as smart transportation, social welfare, tourism, and smart industry. It becomes difficult or sometimes impossible to provide a solution for such potential research issues and challenges from a traditional disciplinary-approach only; to tackle such research issues and to make the paradigm of smart cities a reality, interdisciplinary approaches are deemed necessary. Readers, developers, practitioners, and policy-makers in the field find in the book insights, experiences, findings, and perspectives on smart cities applications with an emphasis on real-life prototyping, beyond the confines of laboratory experiments.
Author(s): Ryoichi Shinkuma, Fatos Xhafa, Takayuki Nishio
Series: Engineering Cyber-Physical Systems and Critical Infrastructures, 5
Publisher: Springer
Year: 2023
Language: English
Pages: 259
City: Cham
Preface
Acknowledgments
Contents
Contributors
Critical Infrastructures Resilience in the Context of a Physical Protection System
1 Introduction
2 Perceiving the Resilience in a Critical Infrastructure System
3 Physical Protection of Critical Infrastructures Elements
4 Security Factors of the Physical Protection System
5 Assessing the Critical Infrastructures Elements Resilience Using Security Factors of the Physical Protection System
5.1 Assessment Parameters of the Physical Protection System Security Factors
5.2 The Procedure for Assessing the Critical Infrastructures Elements Resilience Against Intentional Threats of a Physical Nature
6 Conclusion
References
Smart City Security Based on a Meta-Security Framework for Digital Twins
1 Introduction
2 Review of Smart City Security and Digital Twins
2.1 Smart City Security
2.2 Security Study on Digital Twins
2.3 Models of Digital Twins
3 Problem Statement
4 Introduction of Meta-Security for Digital Twins
4.1 Model of Meta-Security
4.2 Use Cases of Meta-Security Framework in Smart City
5 Future Direction of Smart City Security
6 Conclusion
References
On-Premise Artificial Intelligence as a Service for Small and Medium Size Setups
1 Introduction
2 Infrastructure Automation
2.1 Infrastructure Automation Lifecycle
2.2 Technology Stack for On-Premise Infrastructure Automation
2.3 Semi-automated Solutions for On-Premise Infrastructure Deployments
3 Machine Learning Automation
3.1 Technology Stack for Cloud-Native ML Automation
3.2 On-premise AIaaS Deployment Guidelines
4 Conclusions
References
Incentives in Surplus Food Distribution for Smart Cities and Beyond: An Activity Aware Solution
1 Introduction
2 Related Work
3 Algorithms and Methodology
3.1 Notations and Problem Formulation
3.2 Proposed Mechanism
4 Algorithm Analysis
5 Results
5.1 Analysis
6 Conclusion
References
Evaluation of Smart Charging Integrated with Smart Energy Management and Advance Booking in an eMobility Urban Living Lab
1 Introduction
2 Related Work
3 Methodology
4 Reference Architecture (RA)
5 Planning and Implementation of the eMobility Demonstrators
5.1 Planning of the Oslo Demonstrators
5.2 Implementation of Demo 1
5.3 Implementation of Demo 2
6 Evaluation and Lessons Learned
6.1 Impact on Stakeholder Awareness and Acceptance
6.2 Process Evaluation Findings
7 Discussion
7.1 Recommendations
7.2 Deployment of Smart Charging in Large Urban Areas
7.3 Validity of the Results
8 Conclusion
References
Vehicle Allocation Algorithm Improving User Satisfaction in Ride-Sharing
1 Introduction
2 Related Work
3 Vehicle Allocation Based on User Satisfaction
3.1 Use Case
3.2 Overview of Vehicle Allocation
3.3 Successive Best Insertion (SBI) Algorithm
3.4 Cost Functions
4 Evaluation
4.1 Experiment Environment
4.2 User Satisfaction Metric
4.3 User Satisfaction Against the User Satisfaction Preference Weights
4.4 Economy User Satisfaction Against Different Fare Parameters
4.5 User Satisfaction Against Different Weight Distribution
5 Conclusion
References
A City Airspace Testbed for Drone Networks in Future Smart Cities
1 Introduction
2 Related Work
3 City Airspace Testbed for Future Smart Cities
3.1 Key Concepts
3.2 Self-standing Smart Pole as a Hovering Drone
4 Field Experiments
4.1 Experiment 1: Emulating Multiple Hovering Drones using Self-standing Smart Poles
4.2 Experiment 2: Inter-drone Communication and Its Quality
4.3 Experiment 3: Taking Video from Hovering Drones
5 Conclusions
References
A Feasibility Study of Tethered Autonomous Moving Cells for Smart City
1 Introduction
2 Related Work
3 Proposed Tethered Cell
3.1 Concept
3.2 Fiber Reel
3.3 Slackness Control Algorithm
4 Numerical Results
4.1 Simulation Condition
4.2 Simulation Results
5 Experimental Results
5.1 Use Case 1: Ground Robot
5.2 Use Case 2: Floating Node
6 Conclusion
References
Relationship Among Different Types of Input and Model Accuracies in LSTM Driver Models
1 Introduction
2 Literature Review
3 Experimental Methods
3.1 Participants in the Experiment
3.2 Driving Simulator
3.3 Experimental Scenario
3.4 LSTM
3.5 Model Evaluation Methods and Model Accuracy
4 Results
4.1 Evaluation of Model Accuracy Using Coefficient of Determination
4.2 Model Accuracy for LSTM Input Patterns
4.3 Effects of Logarithmic Distance Between EGV and PRV
4.4 Effects of THW, TTC, Relative Velocity, and Headway Distance
5 Discussion
5.1 Model Accuracy When THW and TTC Are Used as Inputs
5.2 Effect of Input Features on Model Accuracy
5.3 Effect of Logarithmic Distance Between EGV and PRV on Model Accuracy
6 Limitations
7 Conclusion
References
Watch-from-Inside: 3D Sensor System Deployed Inside Building for Road Safety
1 Introduction
2 Related Works
3 Proposed System
3.1 System Model
3.2 Methodology
4 Evaluation
4.1 Experiment for Data Collection
4.2 Construction of Conversion Model
4.3 Construction of ML Model
4.4 Evaluation Result
4.5 Detection Accuracy Versus Distance
5 Evaluation for Experiment at Real Intersection
5.1 Setup for Outdoor Experiments
5.2 Evaluation Result
6 Conclusion
References
Federated Learning with Client Selection in Resource-Uncertain Wireless Networks: Simulation and Proof of Concept Experiments
1 Introduction
1.1 Related Works and Problem Statement
1.2 Our Work
2 Prior Work: Federated Learning with Client Selection
3 Federated Learning with Multi-armed Bandit-Based Client Selection
3.1 System Model
3.2 Multi-armed Bandit-Based Client Selection
4 Simulation and Experimental Evaluation
4.1 ML Setups
4.2 Simulation Settings
4.3 Simulation Results
4.4 Experimental Settings
4.5 Experimental Results
5 Conclusion
References
Index
