Enablers for Smart Cities

Smart cities are a new vision for urban development. They integrate information and communication technology infrastructures - in the domains of artificial intelligence, distributed and cloud computing, and sensor networks - into a city, to facilitate quality of life for its citizens and sustainable growth. This book explores various concepts for the development of these new technologies (including agent-oriented programming, broadband infrastructures, wireless sensor networks, Internet-based networked applications, open data and open platforms), and how they can provide smart services and enablers in a range of public domains. The most significant research, both established and emerging, is brought together to enable academics and practitioners to investigate the possibilities of smart cities, and to generate the knowledge and solutions required to develop and maintain them.

Auteur

Amal El Fallah Seghrouchni is Full Professor at the University of Pierre and Marie Curie, Paris, France where she heads the MAS team at LIP6 (Laboratory of Informatics of Paris 6).

Fuyuki Ishikawa is Associate Professor at the National Institute of Informatics (NII), Tokyo, Japan.

Laurent Hérault holds a PhD degree in computer science from INPG. Since 2011 he is VP, Director of the Europe division at CEA-LETI and is a CEA fellow since 2014.

Hideyuki Tokuda is Professor at the Faculty of Environment and Information Studies and Director of the Ubiquitous Computing and Communication Laboratory at Keio University, Japan.

Contenu

Preface xi
Amal EL FALLAH SEGHROUCHNI, Fuyuki ISHIKAWA and Kenji TEI

Introduction xvii
Amal EL FALLAH SEGHROUCHNI, Fuyuki ISHIKAWA and Kenji TEI

Chapter 1. Shared Wireless Sensor Networks as Enablers for a Context Management System in Smart Cities 1
Kenji TEI

1.1. Introduction 1

1.2. Background 3

1.3. XAC middleware 5

1.3.1. Architecture of XAC middleware 6

1.4. Task-description language 7

1.4.1. Existing solutions 8

1.4.2. XAC middleware solutions 10

1.5. Runtime task management 12

1.5.1. Existing solutions 12

1.5.2. XAC middleware solutions 14

1.6. Self-adaptation 16

1.6.1. Existing solutions 17

1.6.2. XAC middleware solutions 17

1.7. Discussion 18

1.8. Conclusion 19

1.9 Bibliography 19

Chapter 2. Sensorizer: An Architecture for Regenerating Cyber-physical Data Streams from the Web 23
Jin NAKAZAWA

2.1. Introduction 23

2.2. Sensorizer architecture 25

2.2.1. Sensing process of EWC 25

2.2.2. Sensorizer architecture 25

2.3. Implementation 27

2.3.1. Sensorizer browser extension 27

2.3.2. Probe 28

2.3.3. Sensorizer/SoX API 29

2.4. Case of sensorized smart cities 29

2.5. Conclusion 32

2.6. Bibliography 32

Chapter 3. Smart Agent Foundations: From Planning to Spatio-temporal Guidance 33
Ahmed-Chawki CHAOUCHE, Amal EL FALLAH SEGHROUCHNI, Jean-Michel ILIÉ and Djamel Eddine SAÏDOUNI

3.1. Introduction 33

3.2. Smart-campus: use case and scenario 35

3.2.1. Smart-campus architecture 36

3.2.2. Scenario 37

3.3. Description of the software architecture for a smart ambient agent 37

3.4. Higher order agent model 38

3.4.1. Application to the scenario 39

3.5. Description of the concurrent planner based on AgLOTOS language 40

3.5.1. Agent plan structure 40

3.5.2. Syntax of AgLOTOS plans 42

3.5.3. Building of the agent plan from the intentions 44

3.5.4. Planning state of the agent 45

3.6. Contextual planning guidance 45

3.6.1. Semantics of AgLOTOS plans 46

3.6.2. Contextual planning system 48

3.6.3. Application to the scenario 50

3.7. Spatio-temporal guidance from past experiences 52

3.7.1. Contextual planning architecture 52

3.7.2. Learning actions from past experiences 53

3.7.3. Spatio-temporal guidance 58

3.8. Conclusion 61

3.9. Bibliography 62

Chapter 4. A Multi-Agent Middleware for Deployment of Ambient Applications 65
Ferdinand PIETTE, Amal EL FALLAH SEGHROUCHNI, Patrick TAILLIBERT, Costin CAVAL and CÉDRIC DINONT

4.1. Introduction 65

4.2. Challenges for ambient intelligence and Internet of Things 67

4.2.1. Toward the heterogeneity of hardware and protocols 67

4.2.2. Data transport and processing 69

4.2.3. Management of data privacy 71

4.3. Deployment of applications for ambient systems 73

4.3.1. Reasoning about heterogeneity 73

4.3.2. Graph modeling 74

4.3.3. Mathematical formalization of the deployment process 76

4.3.4. Modified graph-matching algorithm 81

4.3.5. Conclusion 85

4.4. Multi-agent middleware for ambient systems 86

4.4.1. Scenario 87

4.4.2. Multi-agent modeling 88

4.4.3. Distributed reasoning 92

4.4.4. Design and implementation 96

4.5. Conclusion 102

4.6. Bibliography 103

Chapter 5. ClouT: Cloud of Things for Empowering Citizen's Clout in Smart Cities 107
Kenji TEI, Levent GÜREEN and TAKURO YONEZAWA

5.1. Objective of the ClouT project 107 5.2. Goal of the ClouT p...