Smart Cities, Green Technologies, and Intelligent Transport Systems: 11th International Conference, SMARTGREENS 2022 and 8th International Conference, VEHITS 2022 Virtual Event, April 27–29, 2022 Revised Selected Papers

Preface
Organization
Contents
Smart Cities and Green ICT Systems
Simulation of Modes of Electric Networks with Electric Transmission Lines Using Earth as Current-Live Part
	1 Introduction
	2 Double TWE Line
	3 The TWE Line Build with Two Special Design Cables
	4 The TWE Structure Based on Four Cables of a Standard Structure
	5 Conclusions
	References
On Developing Sustainable Deep Learning Applications Using Pre-calculating Energy Usage
	1 Introduction
	2 Energy Estimation of Application Systems
		2.1 System Energy Estimation
		2.2 Energy Estimation of a Computing Unit
	3 Energy Modeling of Deep Learning
		3.1 Background on DNN
		3.2 Estimation of Number of MACs
		3.3 Estimation of Number of Data Access
	4 Case Studies of Smart Agriculture Systems
		4.1 Case Study 1: Sensors
		4.2 Case 2: Drones
		4.3 Experiments and Initial Setup
	5 Results for Case Study 1: Sensor Network
		5.1 Effects from Network Structures
		5.2 Effects from Bandwidths
		5.3 Effects from Sensors and Servers Ratios
	6 Case Study 2: Drone Network
		6.1 Effects of the Size of the Area
		6.2 Effects of Number of Servers and Number of Drones
		6.3 Typical vs. Modern Drones
	7 Evaluation, Limitation and Discussion
	8 Related Work
	9 Conclusions
	References
An Evaluation of Smart City Models Towards a New Service Design Model*-4pt
	1 Introduction
	2 Smart City Models
		2.1 Conceptual Smart City Models
		2.2 Discussions for Conceptual Models
		2.3 Structural Smart City Models
		2.4 Discussions for Structural Models
	3 Evaluation Criteria and Results
		3.1 Service Structure
		3.2 Interoperability
		3.3 Multi-contextuality
		3.4 Adaptability
	4 New Model for Smart City Service Design
		4.1 Types of Smart City Services: Background Services and Customer-Facing Services
		4.2 Service Structure and Interoperability
		4.3 Multi-contextuality and Adaptability
		4.4 Further Development of the Model
	5 Conclusions
	References
Fast Electrical Load Classification Using a Dimmer-Based Smart Plug
	1 Introduction
	2 Related Work
		2.1 Edge Computing
	3 Smart Plug Prototype
		3.1 Hardware and Measurement Method
	4 Complexity Reduction with Measurement Profiles
	5 Measured Devices
	6 Classification Results
		6.1 FCNN
		6.2 RNN
		6.3 CNN
	7 On-Device Electrical Load Classification
		7.1 TinyML – Machine Learning on Microcontrollers
		7.2 Smart Plug with TinyML Capabilities
	8 Conclusions and Future Work
		8.1 Future Work
	References
Vehicle Technology and Intelligent Transport Systems
Solving the Dial-a-Ride Problem for Railway Traffic by Means of Heuristics
	1 Introduction
	2 Problem Definition and Notation
	3 Complexity of DARPRT
	4 Algorithms
		4.1 Insertion Heuristic
		4.2 Charging Stop Insertion Algorithms
		4.3 Time-Disjoint Path Algorithms
		4.4 Feasibility Checking of a Schedule
		4.5 Running Time
	5 Computational Study
		5.1 Empirical Graph Instances
		5.2 Study Setup
		5.3 Results
	6 Prospect
		6.1 Summary
		6.2 Extensions and Variants of the DARPRT
		6.3 Online Variant
	A  Appendix
		A.1  General Performance Results
	References
Intelligent Roadside Infrastructure for Connected Mobility
	1 Introduction
	2 Related Work
		2.1 Test Fields with Roadside Infrastructure
		2.2 Sensor Fusion
		2.3 Sensor Synchronization
		2.4 Sensor Calibration
	3 Architecture of the Intelligent Roadside Infrastructure Unit
	4 Hardware Design
		4.1 Sensors and V2X Module Specifications
		4.2 Mechanical Design
		4.3 Electrical Design
	5 Sensor Perception Module
		5.1 Sensor Data Fusion
		5.2 Sensor Monitoring
	6 Communication Module
		6.1 V2X Module
		6.2 V2X Protocol Stacks
		6.3 SENSORIS Integration
	7 Case Study
	8 Conclusion
	References
Using Emotion Recognition and Temporary Mobile Social Network in On-Board Services for Car Passengers
	1 Introduction
	2 Functional Design of a TMSN Playlist Recommender
	3 Experimental Analysis
	4 Performance Analysis of Face Detection and Emotion Recognition Algorithms
		4.1 Hardware Systems
		4.2 Selected Face Detection Algorithms
		4.3 Selected Face Emotion Recognition Algorithms
		4.4 Analysis of Face Detection Algorithm
		4.5 Overall System Performance
	5 Conclusions
	References
Author Index