Biometric data in smart cities: methods and models of collective behavior
In modern conditions of the development of intelligent systems to solve the problems of smart cities, more and more attention is paid to the construction of distributed intelligent systems, which, based on a network of sensors and specialized calculators, help residents and visitors of the city in r...
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Format: | Buch |
Sprache: | English |
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Boca Raton ; London ; New York
CRC Press, Taylor & Francis Group
2022
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Schriftenreihe: | Sensors communication for urban intelligence
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Online-Zugang: | Inhaltsverzeichnis |
Zusammenfassung: | In modern conditions of the development of intelligent systems to solve the problems of smart cities, more and more attention is paid to the construction of distributed intelligent systems, which, based on a network of sensors and specialized calculators, help residents and visitors of the city in real time to solve a whole range of complex problems that arise in an urban environment. In a smart city, much attention is paid to the processing of biometric information that comes from biometric sensors distributed throughout the city. Such biometric systems are multimodal and allow you to control the general condition of a person, and also help a person to move around the city and predict events within the city.This book describes methods for processing biometric information in a smart city environment. The theoretical foundations of building a biometric multisensor network, which allows you to create a unified urban biometric community, are considered. The theoretical foundations of the parallel shift technology and the Radon transformation on cellular automata with a hexagonal covering are presented. On the basis of these technologies, methods of biometric identification by gait parameters and the geometric shape of the auricle are described, which are effectively used in a smart city. A method for tracking dynamic changes in the state of a smart city in real time is considered. Models of behavior of colonies of living organisms, their formation, movement and interaction are described on the basis of the technology of cellular automata with active cells. Models of behavior of active cells in meeting with unwanted cells and models of combining and destruction of active cell colonies are also described.This book is intended for undergraduate, graduate students and specialists working and conducting research in the field of biometric information processing, as well as in the development and construction of distributed intelligent systems |
Beschreibung: | xiii, 213 Seiten Illustrationen, Diagramme |
ISBN: | 9780367650247 9780367650254 |
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Contents Preface.ix About the Authors. xiii 1. Distributed Intelligent Systems and Natural Collective Intelligent Systems. 1 1.1 Introduction: Background and Driving Forces.1 1.2 DIS Short Classification.2 1.3 Natural Collective Intelligent Systems.4 1.4 Ant Colony.4 1.5 Bee Colony.6 1.6 Collective Movements in Nature. 6 2. Multisensor Systems. 9 2.1 Interaction of the System with the External Environment. 9 2.2 Sensor Classification.10 2.3 Multisensory Systems.17 2.4 Conclusion. 23 3. Smart Cities Based on Multisensor Systems. 25 3.1
Introduction. 25 3.2 The Main Characteristics of the Smart City. 26 3.3 Biometric Sensors in a Smart City. 29 4. Biometric Characteristics.31 4.1 Static Biometric Characteristics. 31 4.2 Dynamic Biometric Characteristics.33 4.3 Multimodality of Biometric Identification. 35 5. Biometric Data Processing in Smart Cities Based on Multisensor Systems. 39 5.1 Uniform City Biometric Community.39 5.2 Biometric Features in the Smart City.45 5.3 Human Face Image Analysis. 45 5.4 Analysis of the Geometry of the Auricle.». 47 5.5 Human Gait Analysis.48 6. General Information About ParallelShift Technology.51 6.1 Theoretical Foundations of Parallel Shift Technology. 51 6.2 Data Generation and Storage. 52 Ό
Contents VI 6.3 6.4 6.5 Vector Formation of Functions of the Area of Intersection.57 Formation of FAIs Sets for Non-Binary Images.60 Noise Control with the Use of PST.65 7. Image Recovery by Methods of Parallel Shift Technology. 71 7.1 The Method of Circumscribed Rectangles. 71 7.2 Determining the Parameters of Circumscribed Rectangles. 76 7.3 Formation of Reference Surfaces for Parts of the Existing Standard.82 8. Scene Analysis for Two Objects. 89 8.1 Determining the Basic Parameters of the Scene. 89 8.2 Determining the Real Values of the Basic Parameters of the Scene Objects.93 8.3 Determining the Shape of the Objects of Scene.101 8.4 The Order for Determining the Basic Parameters of the Scene.Ill 9. Radon Transformation Technology on Cellular Automata with Hexagonal Coating.115 9.1 Introduction.115 9.2 Images Description Technology Based on Cellular Automata with Hexagonal Coated Radon Transform.
116 10. Biometric Identification Methods Based on the Geometry of the Auricle Based on Parallel Shift Technology and Radon Transformation. 125 10.1 Technologies For Biometric Identification. 125 10.2 Biometric Identification Methods Based on the Analysis of the Auricle.126 10.3 Determination of the Area of Recognition in Biometric Identification by the Shape of the Ear Based on the Parallel Shift Technology. 137 10.4 Determining the Cut-Off Points of the Ear Image. 137 10.5 The Method of Dividing the Image into Individual Objects. 142 10.6 The Actual Application of the Method of Determining the Location of the Image of the Ear. 144 10.7 The Procedure For Comparing the Elements of the Ear Image with the Reference Data.145
Contents vii 11. Methods of Biometric Identification Based on Gait in the Smart City.149 11.1 The Main Reasons for Using Human Gait for Biometric Identification in a Smart City. 149 11.2 Description of Gait Identification Method.152 11.3 Search for the Motion Vector of the Object in the Visual Field and the Gait Period. 157 11.4 Defining the Area of Analysis in the Images of the Silhouette of the Object.163 11.5 Comparison of the Obtained Data with the Reference Information. 166 12. Biometric Data Processing of Human and Animal Colonies in a Smart City.169 12.1 Distributed Smart Sensor Network of Smart City. 169 12.2 A Method for Analyzing the Overall Urban Picture of the Behavior of People and Animals in a Smart City. 172 12.3 Selection and Description of Objects in the Visual Scene. 174 12.4 Time Impulse Description of the Visual Picture of a Smart City. 176 13. Behavioral Models of Human and Animal Colonies Based on the Technology of Cellular Automata with Active
Cells. 181 13.1 Theoretical Positions of Cellular Automata Technology with Active Cells.181 13.2 Interaction of Active Cells. 183 13.3 Colony Formation.190 13.4 Cell Colony Movement.193 13.5 Interaction of Active Cell Colonies.197 References. 203 Index 209 |
adam_txt |
Contents Preface.ix About the Authors. xiii 1. Distributed Intelligent Systems and Natural Collective Intelligent Systems. 1 1.1 Introduction: Background and Driving Forces.1 1.2 DIS Short Classification.2 1.3 Natural Collective Intelligent Systems.4 1.4 Ant Colony.4 1.5 Bee Colony.6 1.6 Collective Movements in Nature. 6 2. Multisensor Systems. 9 2.1 Interaction of the System with the External Environment. 9 2.2 Sensor Classification.10 2.3 Multisensory Systems.17 2.4 Conclusion. 23 3. Smart Cities Based on Multisensor Systems. 25 3.1
Introduction. 25 3.2 The Main Characteristics of the Smart City. 26 3.3 Biometric Sensors in a Smart City. 29 4. Biometric Characteristics.31 4.1 Static Biometric Characteristics. 31 4.2 Dynamic Biometric Characteristics.33 4.3 Multimodality of Biometric Identification. 35 5. Biometric Data Processing in Smart Cities Based on Multisensor Systems. 39 5.1 Uniform City Biometric Community.39 5.2 Biometric Features in the Smart City.45 5.3 Human Face Image Analysis. 45 5.4 Analysis of the Geometry of the Auricle.». 47 5.5 Human Gait Analysis.48 6. General Information About ParallelShift Technology.51 6.1 Theoretical Foundations of Parallel Shift Technology. 51 6.2 Data Generation and Storage. 52 Ό
Contents VI 6.3 6.4 6.5 Vector Formation of Functions of the Area of Intersection.57 Formation of FAIs Sets for Non-Binary Images.60 Noise Control with the Use of PST.65 7. Image Recovery by Methods of Parallel Shift Technology. 71 7.1 The Method of Circumscribed Rectangles. 71 7.2 Determining the Parameters of Circumscribed Rectangles. 76 7.3 Formation of Reference Surfaces for Parts of the Existing Standard.82 8. Scene Analysis for Two Objects. 89 8.1 Determining the Basic Parameters of the Scene. 89 8.2 Determining the Real Values of the Basic Parameters of the Scene Objects.93 8.3 Determining the Shape of the Objects of Scene.101 8.4 The Order for Determining the Basic Parameters of the Scene.Ill 9. Radon Transformation Technology on Cellular Automata with Hexagonal Coating.115 9.1 Introduction.115 9.2 Images Description Technology Based on Cellular Automata with Hexagonal Coated Radon Transform.
116 10. Biometric Identification Methods Based on the Geometry of the Auricle Based on Parallel Shift Technology and Radon Transformation. 125 10.1 Technologies For Biometric Identification. 125 10.2 Biometric Identification Methods Based on the Analysis of the Auricle.126 10.3 Determination of the Area of Recognition in Biometric Identification by the Shape of the Ear Based on the Parallel Shift Technology. 137 10.4 Determining the Cut-Off Points of the Ear Image. 137 10.5 The Method of Dividing the Image into Individual Objects. 142 10.6 The Actual Application of the Method of Determining the Location of the Image of the Ear. 144 10.7 The Procedure For Comparing the Elements of the Ear Image with the Reference Data.145
Contents vii 11. Methods of Biometric Identification Based on Gait in the Smart City.149 11.1 The Main Reasons for Using Human Gait for Biometric Identification in a Smart City. 149 11.2 Description of Gait Identification Method.152 11.3 Search for the Motion Vector of the Object in the Visual Field and the Gait Period. 157 11.4 Defining the Area of Analysis in the Images of the Silhouette of the Object.163 11.5 Comparison of the Obtained Data with the Reference Information. 166 12. Biometric Data Processing of Human and Animal Colonies in a Smart City.169 12.1 Distributed Smart Sensor Network of Smart City. 169 12.2 A Method for Analyzing the Overall Urban Picture of the Behavior of People and Animals in a Smart City. 172 12.3 Selection and Description of Objects in the Visual Scene. 174 12.4 Time Impulse Description of the Visual Picture of a Smart City. 176 13. Behavioral Models of Human and Animal Colonies Based on the Technology of Cellular Automata with Active
Cells. 181 13.1 Theoretical Positions of Cellular Automata Technology with Active Cells.181 13.2 Interaction of Active Cells. 183 13.3 Colony Formation.190 13.4 Cell Colony Movement.193 13.5 Interaction of Active Cell Colonies.197 References. 203 Index 209 |
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author | Bilan, Stepan 1962- Bilan, Mykola Motornyuk, Ruslan Yuzhakov, Serhii |
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spelling | Bilan, Stepan 1962- (DE-588)1190117754 aut Biometric data in smart cities methods and models of collective behavior Stepan Bilan, Mykola Bilan, Ruslan Motornyuk, and Serhii Yuzhakov Boca Raton ; London ; New York CRC Press, Taylor & Francis Group 2022 xiii, 213 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Sensors communication for urban intelligence In modern conditions of the development of intelligent systems to solve the problems of smart cities, more and more attention is paid to the construction of distributed intelligent systems, which, based on a network of sensors and specialized calculators, help residents and visitors of the city in real time to solve a whole range of complex problems that arise in an urban environment. In a smart city, much attention is paid to the processing of biometric information that comes from biometric sensors distributed throughout the city. Such biometric systems are multimodal and allow you to control the general condition of a person, and also help a person to move around the city and predict events within the city.This book describes methods for processing biometric information in a smart city environment. The theoretical foundations of building a biometric multisensor network, which allows you to create a unified urban biometric community, are considered. The theoretical foundations of the parallel shift technology and the Radon transformation on cellular automata with a hexagonal covering are presented. On the basis of these technologies, methods of biometric identification by gait parameters and the geometric shape of the auricle are described, which are effectively used in a smart city. A method for tracking dynamic changes in the state of a smart city in real time is considered. Models of behavior of colonies of living organisms, their formation, movement and interaction are described on the basis of the technology of cellular automata with active cells. Models of behavior of active cells in meeting with unwanted cells and models of combining and destruction of active cell colonies are also described.This book is intended for undergraduate, graduate students and specialists working and conducting research in the field of biometric information processing, as well as in the development and construction of distributed intelligent systems Smart City (DE-588)1061057097 gnd rswk-swf Lernendes System (DE-588)4120666-6 gnd rswk-swf Biometrie (DE-588)4124925-2 gnd rswk-swf Biometrie (DE-588)4124925-2 s Smart City (DE-588)1061057097 s Lernendes System (DE-588)4120666-6 s DE-604 Bilan, Mykola aut Motornyuk, Ruslan aut Yuzhakov, Serhii aut Erscheint auch als Online-Ausgabe 978-1-003-12746-8 Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032754286&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Bilan, Stepan 1962- Bilan, Mykola Motornyuk, Ruslan Yuzhakov, Serhii Biometric data in smart cities methods and models of collective behavior Smart City (DE-588)1061057097 gnd Lernendes System (DE-588)4120666-6 gnd Biometrie (DE-588)4124925-2 gnd |
subject_GND | (DE-588)1061057097 (DE-588)4120666-6 (DE-588)4124925-2 |
title | Biometric data in smart cities methods and models of collective behavior |
title_auth | Biometric data in smart cities methods and models of collective behavior |
title_exact_search | Biometric data in smart cities methods and models of collective behavior |
title_exact_search_txtP | Biometric data in smart cities methods and models of collective behavior |
title_full | Biometric data in smart cities methods and models of collective behavior Stepan Bilan, Mykola Bilan, Ruslan Motornyuk, and Serhii Yuzhakov |
title_fullStr | Biometric data in smart cities methods and models of collective behavior Stepan Bilan, Mykola Bilan, Ruslan Motornyuk, and Serhii Yuzhakov |
title_full_unstemmed | Biometric data in smart cities methods and models of collective behavior Stepan Bilan, Mykola Bilan, Ruslan Motornyuk, and Serhii Yuzhakov |
title_short | Biometric data in smart cities |
title_sort | biometric data in smart cities methods and models of collective behavior |
title_sub | methods and models of collective behavior |
topic | Smart City (DE-588)1061057097 gnd Lernendes System (DE-588)4120666-6 gnd Biometrie (DE-588)4124925-2 gnd |
topic_facet | Smart City Lernendes System Biometrie |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032754286&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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