Intro
Preface
Organization
Contents
Part II
Contents
Part I
Human Behaviour Analysis for Smart City Environment Safety
HBAxSCES
A Framework for Forming Middle Distance Routes Based on Spatial Guidelines, Perceived Accessibility and Visual Cues in Smart City
1 Introduction
2 Orientation and Perception Along the Route When Using the Navigation Interface
2.1 Mental Maps and Traveler Environment in Route Network Sustainability
2.2 Aggregation of Information for Navigation Tasks
2.3 Planning, Detailing, and Optimizing a Middle-Distance Route

2.4 Smart Routes Application Interface
3 GIS Applications in the Study of Navigation Behavior
3.1 Materials and Methods
3.2 Results
4 Conclusion
References
A Survey on Few-Shot Techniques in the Context of Computer Vision Applications Based on Deep Learning
1 Introduction
2 Description of Few-Shot Learning
2.1 Applications of FSL
2.2 FSL Techniques
2.3 FSL Benchmarks for Computer Vision
3 FSL for Human Behaviour Analysis Applications
4 Few-Shot for Smart City Environment Safety Applications
5 Conclusion
References

Decision-Support System for Safety and Security Assessment and Management in Smart Cities
1 Introduction
2 Material and Method
2.1 Conceptual Model
2.2 System Architecture
3 Case Study
4 Conclusions and Discussion
References
Embedded Intelligence for Safety and Security Machine Vision Applications
1 Introduction
2 Edge Computing Machine Vision Systems in S4AllCities Project
3 Integration with the Distributed Edge Computing Platform (DECIoT)
4 Hardware Platform for Machine Vision Based on the I. MX8M PLUS
5 VAEC System
6 Conclusions
References

Supporting Energy Digital Twins with Cloud Data Spaces: An Architectural Proposal
1 Introduction
2 Background and State of Art
2.1 Energy of Things
2.2 Open Initiatives in Energy Computing Field
3 Design of the Italian Energy Data Space
3.1 Logical Architecture
3.2 The Proposed Development Process
4 Conclusion
References
High-Level Feature Extraction for Crowd Behaviour Analysis: A Computer Vision Approach
1 Introduction
2 Related Work
3 Proposed Method
3.1 Pre-processing
3.2 Supervised Deep Learning Module

3.3 Unsupervised Learning for Trajectory Clustering
4 Experimental Results
5 Conclusions
References
Binary is the New Black (and White): Recent Advances on Binary Image Processing
A Simple yet Effective Image Repairing Algorithm
1 Introduction
2 Background Notions
3 Related Work
4 Our Approach to Image Repairing
4.1 Algorithm A
4.2 Algorithm B
5 Proof of Correctness
5.1 Well-Composedness
5.2 Homotopy Equivalence
6 Experimental Results and Discussion
6.1 Results of Algorithms A and B
6.2 Processing The Repaired Images
7 Conclusion
References