Enables readers to understand a broad area of state-of-the-art research in physical IoT-enabled security

IoT-enabled Unobtrusive Surveillance Systems for Smart Campus Safety describes new techniques in unobtrusive surveillance that enable people to act and communicate freely, while at the same time protecting them from malevolent behavior. It begins by characterizing the latest on surveillance systems deployed at smart campuses, miniatures of smart cities with more demanding frameworks that enable learning, social interaction, and creativity, and by performing a comparative assessment in the area of unobtrusive surveillance systems for smart campuses.

A proposed taxonomy for IoT-enabled smart campus unfolds in five research dimensions: (1) physical infrastructure; (2) enabling technologies; (3) software analytics; (4) system security; and (5) research methodology. By applying this taxonomy and by adopting a weighted scoring model on the surveyed systems, the book presents the state of the art and then makes a comparative assessment to classify the systems.

Finally, the book extracts valuable conclusions and inferences from this classification, providing insights and directions towards required services offered by unobtrusive surveillance systems for smart campuses.

IoT-enabled Unobtrusive Surveillance Systems for Smart Campus Safety includes specific discussion of:

• Smart campus’s prior work taxonomies and classifications, a proposed taxonomy, and an adopted weight scoring model
• Personal consumer benefits and potential social dilemmas encountered when adopting an unobtrusive surveillance system
• Systems that focus on smart buildings, public spaces, smart lighting and smart traffic lights, smart labs, and smart campus ambient intelligence
• A case study of a spatiotemporal authentication unobtrusive surveillance system for smart campus safety and emerging issues for further research directions

IoT-enabled Unobtrusive Surveillance Systems for Smart Campus Safety is an essential resource for computer science and engineering academics, professionals, and every individual who is working and doing research in the area of unobtrusive surveillance systems and physical security to face malevolent behavior in smart campuses.

Theodoros Anagnostopoulos, PhD, is a Lecturer (Teaching) in Computer Science in the Department of Business Administration at the University of West Attica, Greece. He is also an Associate Academic in Artificial Intelligence with the School of Computing Science in the University of Glasgow, United Kingdom, and Associated Lecturer in Internet of Things (IoT) at the International Research Laboratory in Modern Communications in the Department of Infocommunication Technologies at ITMO University, Russia.

Author Biography xi

Preface xiii

1 Introduction 1

1.1 Smart Cities Dimensions and Risks 2

1.2 Smart Campuses Components 2

1.3 Smart Campuses Unobtrusive Surveillance Systems 3

1.4 Smart Campus Safety Systems Survey 3

1.5 Smart Campuses Comparative Assessment 4

1.6 Smart Campus Systems Classification 4

1.7 Smart Campus Safety: A System Architecture 4

1.8 Human Factor as an Unobtrusive Surveillance System’s Adoption Parameter for Smart Campus Safety 5

1.9 Smart Campus Surveillance Systems Future Trends and Directions 5

2 Smart City 7

2.1 Smart Cities Dimensions 7

2.1.1 Smart Economy 8

2.1.2 Smart Governance 9

2.1.3 Smart Living 10

2.1.4 Smart Mobility 10

2.1.5 Smart People 11

2.1.6 Smart Environment 12

2.2 Risks Related to Smart Cities 12

2.2.1 Technical Risks 12

2.2.2 Nontechnical Risks 13

2.3 Mitigating Smart Cities Risks 14

2.4 Systems Beyond Smart Cities 15

3 Smart Campus 17

3.1 Smart Campus Components 17

3.1.1 Smart Grid 18

3.1.2 Smart Community Services 20

3.1.3 Smart Management 21

3.1.4 Smart Propagation Services 23

3.1.5 Smart Prosperity 24

3.2 Unobtrusive

Surveillance Campus System 24

4 Unobtrusive Surveillance Systems 27

4.1 Geospatial Internet of Things 27

4.2 Smart Campus Unobtrusive Surveillance 28

4.3 Proposed Taxonomy 28

4.4 Adopted Weighted Scoring Model 34

5 Smart Campus Safety Systems Survey 39

5.1 Systems Not Classified 39

5.2 Systems That Focus on Public Spaces and Smart Parking 46

5.3 Systems That Focus on Smart Buildings, Smart Labs, Public Spaces, and Smart Lighting 48

5.4 Systems That Focus on Public Spaces and Smart Traffic Lights 51

5.5 Systems That Focus on Smart Buildings and Smart Classes 54

5.6 Systems That Focus on Smart Buildings, Public Spaces, Smart Lighting, and Smart Traffic Lights 58

5.7 Systems That Focus on Smart Buildings and Smart Labs 63

5.8 Systems That Focus on Smart Buildings and Public Spaces 67

5.9 Systems That Focus on Smart Campus Ambient Intelligence and User Context 79

5.10 Systems That Focus on Smart Campus Low-Power Wide Area Networks Technology 87

6 Comparative Assessment 97

7 Classification and Proposed Solution 103

7.1 Weighting Process 103

7.2 Classification Process 106

8 Smart Campus Spatiotemporal Authentication Unobtrusive Surveillance System for Smart Campus Safety 111

8.1 Smart Campus Spatiotemporal Authentication Unobtrusive Surveillance System 112

8.2 Smart Campus Safety: A System Architecture 116

9 Human Factor as an Unobtrusive Surveillance System’s Adoption Parameter for Smart Campus Safety 127

9.1 Ethical Dilemma of Adopting an Unobtrusive Surveillance System 127

9.2 Degree of Free Will Engagement and Negotiation with an Unobtrusive System 128

10 Smart Campus Surveillance Systems Future Trends and Directions 131

References 133

Index 143