Smart Trajectories

Metamodeling, Reactive Architecture for Analytics, and Smart Applications

Azedine Boulmakoul, Lamia Karim, Bharat Bhushan

• Publisher: CRC Press
• Year: 2022
• eBook ISBN: 9781000817461
• Edition: 1
• Topic: Computer Science
• Subtopic: Computer Science General
• Index: Computer Science

This book highlights the developments, discoveries, and practical and advanced experiences related to responsive distributed computing and how it can support the deployment of trajectory-based applications in smart systems. Smart Trajectories: Metamodeling, Reactive Architecture for Analytics and Smart Applications deals with the representation and manipulation of smart trajectories in various applications and scenarios. Presented in three parts, the book first discusses the foundation and principles for spatial information systems, complex event processing, and building a reactive architecture. Next, the book discusses modeling and architecture in relation to smart trajectory metamodeling, mining and big trajectory data, and clustering trajectories. The final section discusses advanced applications and trends in the field, including congestion trajectory analytics and real-time Big Data analytics in cloud ecosystems. Metamodeling, distributed architectures, reactive programming, Big Data analytics, NoSQL databases, connected objects, and edge-fog-cloud computing form the basis of the concepts and applications discussed. The book also presents a number of case studies to demonstrate smart trajectories related to spatiotemporal events such as traffic congestion and pedestrian accidents.

This book is intended for graduate students in computer engineering, spatial databases, complex event processing, distributed systems, and geographical information systems (GIS). The book will also be useful for practicing traffic engineers, city managers, and environmental engineers interested in monitoring and security analysis.

Table of contents

• Cover Page
• Half-Title Page
• Title Page
• Copyright Page
• Contents
• Preface
• Editor Biographies
• Contributors
• Acknowledgments
• Chapter 1 Intelligent Distributed Computing Paradigm
• Chapter 2 Multi-Micro-Agent System Middleware Model Based on Event Sourcing and CQRS Patterns
• Chapter 3 Intelligent Distributed Computing Paradigm: Emergence, Challenges and Future Research Directions
• Chapter 4 Emerging Paradigm of Urban Computing: Challenges, Applications, and Future Research Directions
• Chapter 5 Complex Event Processing Architectures for Smart City Applications
• Chapter 6 Portunus: Enhancing Smart City Application Connectivity with a Complex Space-Time Events Distributed System
• Chapter 7 Smart Trajectories Meta-Modeling
• Chapter 8 A Type-Level Trajectory Framework
• Chapter 9 A Distributed Reactive Trajectory Framework for Nearby Event Discovery
• Chapter 10 A Multidimensional Trajectory Model in the Context of Mobile Crowd Sensing
• Chapter 11 Trajectory Mining Based on Process Mining in RORO Terminals: Performance-Driven Analysis to Support Trajectory Redesign
• Chapter 12 Aspects of Mobility Data in the Fog/Cloud Era: Directions from a Pilot Case Study of Hazmat Transportation Telemonitoring in an Urban Area
• Chapter 13 Utility Assessment of Line-of-Sight Traffic Jam and Queue Detection in Urban Environments for Intelligent Road Vehicles
• Chapter 14 Risky Trajectory Prediction for Safe Walkability under an Intuitionistic Fuzzy Environment
• Chapter 15 A Real-Time Reactive Service-Oriented Architecture for Safe Urban Walkability
• Chapter 16 Safest Trajectories for Pedestrians Using Distributed Architecture Based on Spatial Risk Analysis and Voronoï Spatial Accessibility
• Chapter 17 Toward a Predictive Simulation Framework of Accident Risks for Pedestrians Based on Distributed Artificial Intelligence and Intuitionist Fuzzy Modeling
• Chapter 18 Trajectory to a New Shape of Organizational Structure, Enterprise Architect, and Organizational Audit for Governance of Information Systems Processes
• Chapter 19 Dynamic Detection of Fuzzy Subcongested Urban Traffic Networks
• Chapter 20 Multiagent Modeling for Pedestrian Risk Assessment
• Index