Kooperativer Bibliotheksverbund

UID:

Format: 1 online resource (446 pages)

Edition: 1st ed.

ISBN: 9783031540493

Series Statement: Studies in Computational Intelligence Series ; v.1147

Note: Intro -- Acknowledgements -- Contents -- Contributors -- Abbreviations -- Introduction -- Going to the Edge: Bringing Artificial Intelligence and Internet of Things Together -- 1 Introduction -- 2 Objectives -- 3 Trustworthiness -- 4 Building on a Sound Basis -- 5 Driven Through Industrial Applications -- 6 Building Technology for Intelligent, Secure, Trustworthy Things -- 7 Reference Architecture for Trustworthy AIoT -- 8 Summary -- References -- The Development of Ethical and Trustworthy AI Systems Requires Appropriate Human-Systems Integration -- 1 Is Trustworthiness of AI a Problem? -- 2 Current Initiatives to Address Trustworthiness of AI -- 2.1 Guidelines and Regulations -- 2.2 Implementation Support -- 2.3 Observed Gaps in Current Initiatives -- 3 From Technology-Centered to Human-Centered Development of Smart Technologies -- 3.1 Orchestrating the Development of Ethical and Trustworthy AI -- 4 Conclusions -- References -- The InSecTT Reference Architecture -- 1 Introduction -- 2 AI in IoT Architectures -- 3 Overview of the InSecTT Architecture -- 3.1 Evolution of the Bubble -- 3.2 Modern Reference Architectures -- 4 Entity Model -- 5 Layered Model -- 5.1 Level 0 -- 5.2 Level 1 -- 5.3 Level 2 -- 5.4 Hardware Interfaces -- 6 Domain Model -- 7 Functionality Model -- 7.1 SW Interfaces -- 8 Information Model -- 9 AI Perspective of the Architecture -- 10 Example Use Cases Alignment -- 10.1 Overview -- 10.2 Entity Model -- 10.3 Functionality model -- 10.4 Interfaces -- 10.5 General Project Overview for Architecture Alignment -- References -- Structuring the Technology Landscape for Successful Innovation in AIoT -- 1 Motivation -- 2 How to Structure Research and Development to Enact an Ambitious Project Vision -- 3 Requirements and Constraints -- 4 Requirement Engineering Process -- 5 Navigating the Landscape: Planning R& -- D Work. , 6 External Alignment -- 7 Documenting Scope, Work and Results -- 8 Progress Assessment and Validation -- 9 Demonstrators -- 10 Preparing for Market: Exploitation -- 11 InSecTT Exploitation Board (EB) -- 12 Use Case Marketplace -- 13 Open Innovation -- 14 Publications to Prepare Markets -- 15 Website and Social Networks -- 16 Industrial Conferences, Trade Fairs and Podcasts -- Technology Development -- InSecTT Technologies for the Enhancement of Industrial Security and Safety -- 1 Introduction -- 2 Background -- 2.1 Industrial Automation and Control Systems -- 3 Selected InSecTT Technologies Targeting Security and Safety -- 3.1 Access Control and Authentication Infrastructure -- 3.2 Intrusion Detection Systems -- 3.3 Tools, Simulators and Datasets -- 3.4 Safety and Security Analysis for AGV Platooning -- 4 Novelty and Applicability of Proposed Technologies -- 5 Conclusions and Future Perspectives -- References -- Algorithmic and Implementation-Based Threats for the Security of Embedded Machine Learning Models -- 1 Introduction -- 2 Threat Models -- 2.1 Formalism -- 2.2 Adversarial Objectives -- 2.3 The System Under Attack -- 2.4 Knowledge and Capacity of an Adversary -- 2.5 Attack Surface -- 3 A Panorama of Algorithmic Attacks -- 3.1 Confidentiality and Privacy Threats -- 3.2 Integrity-Based Attacks -- 3.3 Availability -- 4 A Focus on Physical Attacks -- 4.1 Model Extraction Based on Side-Channel Analysis -- 4.2 Weight-Based Adversarial Attacks -- 5 Protecting ML System -- 5.1 Embedded Authentication Mechanism -- 5.2 Main Defenses Against Algorithmic Attacks -- 5.3 Countermeasures Against Physical Attacks -- 6 Conclusion -- References -- Explainable Anomaly Detection of 12-Lead ECG Signals Using Denoising Autoencoder -- 1 Introduction -- 2 Anomaly Detection and Explainability in Deep Learning. , 3 Denosisng Autoencoder as an Explainable Anomaly Detection Model for ECGs -- 3.1 ECG Data Sets -- 3.2 Model Architecture and Training -- 3.3 Results of Denoising and the Exploration of the Latent Space -- 4 Cloud-Based Service and Visualization of Explainable Anomaly Detection on ECGs -- 5 Conclusion -- References -- Indoor Navigation with a Smartphone -- 1 Introduction -- 2 Encoding Information in QR -- 3 Navigation -- 4 Local to Global Coordinates -- 5 Triage -- 6 Future Work -- 7 Conclusions -- References -- Reconfigurable Antennas for Trustable Things -- 1 Introduction -- 2 Electronically Steerable Parasitic Array Radiator Antenna for Trustable Things -- 2.1 Concept -- 2.2 Design -- 2.3 Realization -- 3 Applications -- 3.1 Direction of Arrival Estimation -- 3.2 Power Pattern Cross-Correlation Algorithm -- 3.3 Interpolation-Based Estimation -- 3.4 Multiplane Calibration for 2D DoA Estimation -- 3.5 DoA-Based Object Positioning -- 3.6 Single-Anchor Positioning System -- 3.7 Calibration-Free Indoor Localization -- 3.8 Other Applications -- References -- AI-Enhanced Connection Management for Cellular Networks -- 1 Introduction -- 2 Related Work -- 2.1 Data Rate Estimation -- 2.2 Interface Selection -- 3 Use Case and Research Challenge -- 4 Data Collection and Analysis -- 5 Uplink Data Rate Estimation -- 6 Interface Decision -- 7 Conclusion -- References -- Vehicle Communication Platform to Anything-VehicleCAPTAIN -- 1 Introduction -- 2 Problem Statement -- 3 VehicleCAPTAIN-A V2X Platform for Research and Development -- 3.1 The Platform -- 3.2 Message Library -- 3.3 ROS2 Support -- 4 Verification -- 4.1 Test Methodology -- 4.2 Results -- 4.3 Discussion -- 5 Key Performance Indicators -- 5.1 Use Cases Within InSecTT -- 5.2 Use Cases Within the Virtual Vehicle Research GmbH -- 6 Conclusion -- References. , AI-Enhanced UWB-Based Localisation in Wireless Networks -- 1 Introduction -- 2 Method Overview -- 3 AI for Solving UWB-Based Localisation Challenges -- 3.1 Localisation Challenges -- 3.2 AI Algorithms in UWB-Based Localisation Systems -- 4 Overview of Related Work -- 5 Application Example -- 5.1 KNN for LOS/NLOS Detection -- 5.2 KNN for Error Mitigation and Trustworthiness -- 6 Conclusion -- References -- Industrial Applications -- Approaches for Automating Cybersecurity Testing of Connected Vehicles -- 1 Introduction -- 2 State of the Art and Related Work -- 3 Automotive Cybersecurtiy Lifecycle Management -- 3.1 Threat Modeling -- 4 Cybersecurity Testing -- 4.1 Learning-Based Testing -- 4.2 Model-Based Test Case Generation -- 4.3 Testing Platform -- 4.4 Automated Test Execution -- 4.5 Fuzzing -- 5 Conclusion -- References -- Solar-Based Energy Harvesting and Low-Power Wireless Networks -- 1 Introduction -- 1.1 Solar-Based Energy Harvesting -- 2 Low-Power Network Protocols -- 2.1 Bluetooth Low Energy -- 2.2 IEEE 802.15.4 and Thread -- 2.3 EPhESOS Protocol -- 2.4 UWB Localisation -- 3 Power Consumption in Different Scenarios -- 3.1 Measurement Setup and Hardware -- 3.2 Power Consumption with Increasing Update Period -- 4 Available Energy in Real-World Scenarios -- 5 Experimental Results -- 6 Conclusion -- References -- Location Awareness in HealthCare -- 1 Terminology and Technology -- 1.1 Positioning, Localization, Tracking and Navigation -- 1.2 RF-Based Indoor Localization Technologies -- 1.3 Non-RF Based Localization Technologies -- 2 Pedestrian Dead Reckoning (PDR) -- 3 Others -- 3.1 Outdoor Localization Technologies -- 3.2 Technology Overview -- 4 Designing an End-To-End IoT Solution -- 4.1 Commissioning -- 4.2 Low Power Wide Area Networks (LPWAN) -- 4.3 Battery Lifetime -- 4.4 Going from Indoor to Outdoor -- 4.5 APIs for Location Services. , 4.6 Visualizing on a Map -- 4.7 Security and Privacy Aspects -- 5 Healthcare Use-Cases -- 5.1 Asset Tracking -- 5.2 Mass Casualty Incident (MCI) -- 5.3 Bed Management -- 5.4 Hospital Wayfinding -- 6 Use-Case Concept Demonstrator -- 6.1 Architecture -- 6.2 GeoJSON Server -- 6.3 Client Authentication -- 6.4 FHIR Compatibility -- 6.5 Location and Privacy -- 6.6 Additional Features -- 7 Conclusions/Next Steps -- References -- Driver Distraction Detection Using Artificial Intelligence and Smart Devices -- 1 Introduction -- 2 Definitions and Background -- 3 System Design -- 4 Machine Learning-Based Components -- 4.1 Use Case Definition and Components' Architecture -- 4.2 Data Acquisition and Pre-processing -- 4.3 Machine Learning Model Training and Experimental Results -- 4.4 Model Deployment on Smart Devices -- 5 Dashboard Application for Driver Distraction -- 6 Related Work -- 7 Conclusion and Future Work -- References -- Working with AIoT Solutions in Embedded Software Applications. Recommendations, Guidelines, and Lessons Learned -- 1 Introduction -- 2 Project Description and Goals -- 3 Project Design -- 4 Machine Learning in Embedded Systems -- 5 Communication Platform -- 5.1 Design Layout -- 5.2 Message Queuing with RabbitMQ -- 5.3 Inter-Process Messaging -- 6 Data Extraction -- 7 Training Data Set and Model -- 7.1 Design Stage 1 -- 7.2 Design Stage 2 -- 7.3 Alternative Model Setup -- 8 Cloud or Edge? -- 9 Security -- 10 Conclusion -- Appendix A -- Appendix B -- References -- Artificial Intelligence for Wireless Avionics Intra-Communications -- 1 Introduction -- 2 Use Case Objectives -- 3 Link Between Scenarios and Building Blocks -- 4 State of the Art -- 5 AI/IoT Added Value -- 6 Scenarios -- 6.1 Scenario 1: Interference Detection and Cancellation -- 6.2 Scenario 2: Verification and Validation of WAICs -- 6.3 Scenario 3: Battery-Less Devices. , 7 Performance Evaluation.

Additional Edition: Print version: Karner, Michael Intelligent Secure Trustable Things Cham : Springer International Publishing AG,c2024 ISBN 9783031540486

Language: English

Subjects: Computer Science

Keywords: Electronic books. ; Electronic books.

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UID:

Format: 1 online resource (446 pages)

Edition: 1st ed. 2024.

ISBN: 3-031-54049-2

Series Statement: Studies in Computational Intelligence, 1147

Content: This open access book provides an overview about results of the InSecTT project. Artificial Intelligence of Things (AIoT) is the natural evolution for both Artificial Intelligence (AI) and Internet of Things (IoT) because they are mutually beneficial. AI increases the value of the IoT through machine learning by transforming the data into useful information, while the IoT increases the value of AI through connectivity and data exchange. Therefore, InSecTT—Intelligent Secure Trustable Things, a pan-European effort with over 50 key partners from 12 countries (EU and Turkey), provides intelligent, secure and trustworthy systems for industrial applications to provide comprehensive cost-efficient solutions of intelligent, end-to-end secure, trustworthy connectivity and interoperability to bring the Internet of Things and Artificial Intelligence together. InSecTT creates trust in AI-based intelligent systems and solutions as a major part of the AIoT. InSecTT fosters cooperation between big industrial players from various domains, a number of highly innovative SMEs distributed all over Europe and cutting-edge research organizations and universities. The project features a big variety of industry-driven use cases embedded into various application domains where Europe is in a leading position, i.e., smart infrastructure, building, manufacturing, automotive, aeronautics, railway, urban public transport, maritime as well as health. The demonstration of InSecTT solutions in well-known real-world environments like airports, trains, ports and the health sector shows their applicability on both high and broad level, going from citizens to European stakeholders. The first part of the book provides an introduction into the main topics of the InSecTT project: How to bring Internet of Things and Artificial Intelligence together to form the Artificial Intelligence of Things, a reference architecture for such kind of systems and how to develop trustworthy, ethical AI systems. In the second part, we show the development of essential technologies for creating trustworthy AIoT systems. The third part of the book is composed of a broad variety of examples on how to design, develop and validate trustworthy AIoT systems for industrial applications (including automotive, avionics, smart infrastructure, health care, manufacturing and railway).

Note: Introduction -- Technology Development -- Industrial Applications.

Additional Edition: ISBN 3-031-54048-4

Language: English

DOI: 10.1007/978-3-031-54049-3

UID:

Format: 1 online resource (446 pages)

Edition: 1st ed.

ISBN: 3-031-54049-2

Series Statement: Studies in Computational Intelligence Series ; v.1147

Note: Intro -- Acknowledgements -- Contents -- Contributors -- Abbreviations -- Introduction -- Going to the Edge: Bringing Artificial Intelligence and Internet of Things Together -- 1 Introduction -- 2 Objectives -- 3 Trustworthiness -- 4 Building on a Sound Basis -- 5 Driven Through Industrial Applications -- 6 Building Technology for Intelligent, Secure, Trustworthy Things -- 7 Reference Architecture for Trustworthy AIoT -- 8 Summary -- References -- The Development of Ethical and Trustworthy AI Systems Requires Appropriate Human-Systems Integration -- 1 Is Trustworthiness of AI a Problem? -- 2 Current Initiatives to Address Trustworthiness of AI -- 2.1 Guidelines and Regulations -- 2.2 Implementation Support -- 2.3 Observed Gaps in Current Initiatives -- 3 From Technology-Centered to Human-Centered Development of Smart Technologies -- 3.1 Orchestrating the Development of Ethical and Trustworthy AI -- 4 Conclusions -- References -- The InSecTT Reference Architecture -- 1 Introduction -- 2 AI in IoT Architectures -- 3 Overview of the InSecTT Architecture -- 3.1 Evolution of the Bubble -- 3.2 Modern Reference Architectures -- 4 Entity Model -- 5 Layered Model -- 5.1 Level 0 -- 5.2 Level 1 -- 5.3 Level 2 -- 5.4 Hardware Interfaces -- 6 Domain Model -- 7 Functionality Model -- 7.1 SW Interfaces -- 8 Information Model -- 9 AI Perspective of the Architecture -- 10 Example Use Cases Alignment -- 10.1 Overview -- 10.2 Entity Model -- 10.3 Functionality model -- 10.4 Interfaces -- 10.5 General Project Overview for Architecture Alignment -- References -- Structuring the Technology Landscape for Successful Innovation in AIoT -- 1 Motivation -- 2 How to Structure Research and Development to Enact an Ambitious Project Vision -- 3 Requirements and Constraints -- 4 Requirement Engineering Process -- 5 Navigating the Landscape: Planning R& -- D Work. , 6 External Alignment -- 7 Documenting Scope, Work and Results -- 8 Progress Assessment and Validation -- 9 Demonstrators -- 10 Preparing for Market: Exploitation -- 11 InSecTT Exploitation Board (EB) -- 12 Use Case Marketplace -- 13 Open Innovation -- 14 Publications to Prepare Markets -- 15 Website and Social Networks -- 16 Industrial Conferences, Trade Fairs and Podcasts -- Technology Development -- InSecTT Technologies for the Enhancement of Industrial Security and Safety -- 1 Introduction -- 2 Background -- 2.1 Industrial Automation and Control Systems -- 3 Selected InSecTT Technologies Targeting Security and Safety -- 3.1 Access Control and Authentication Infrastructure -- 3.2 Intrusion Detection Systems -- 3.3 Tools, Simulators and Datasets -- 3.4 Safety and Security Analysis for AGV Platooning -- 4 Novelty and Applicability of Proposed Technologies -- 5 Conclusions and Future Perspectives -- References -- Algorithmic and Implementation-Based Threats for the Security of Embedded Machine Learning Models -- 1 Introduction -- 2 Threat Models -- 2.1 Formalism -- 2.2 Adversarial Objectives -- 2.3 The System Under Attack -- 2.4 Knowledge and Capacity of an Adversary -- 2.5 Attack Surface -- 3 A Panorama of Algorithmic Attacks -- 3.1 Confidentiality and Privacy Threats -- 3.2 Integrity-Based Attacks -- 3.3 Availability -- 4 A Focus on Physical Attacks -- 4.1 Model Extraction Based on Side-Channel Analysis -- 4.2 Weight-Based Adversarial Attacks -- 5 Protecting ML System -- 5.1 Embedded Authentication Mechanism -- 5.2 Main Defenses Against Algorithmic Attacks -- 5.3 Countermeasures Against Physical Attacks -- 6 Conclusion -- References -- Explainable Anomaly Detection of 12-Lead ECG Signals Using Denoising Autoencoder -- 1 Introduction -- 2 Anomaly Detection and Explainability in Deep Learning. , 3 Denosisng Autoencoder as an Explainable Anomaly Detection Model for ECGs -- 3.1 ECG Data Sets -- 3.2 Model Architecture and Training -- 3.3 Results of Denoising and the Exploration of the Latent Space -- 4 Cloud-Based Service and Visualization of Explainable Anomaly Detection on ECGs -- 5 Conclusion -- References -- Indoor Navigation with a Smartphone -- 1 Introduction -- 2 Encoding Information in QR -- 3 Navigation -- 4 Local to Global Coordinates -- 5 Triage -- 6 Future Work -- 7 Conclusions -- References -- Reconfigurable Antennas for Trustable Things -- 1 Introduction -- 2 Electronically Steerable Parasitic Array Radiator Antenna for Trustable Things -- 2.1 Concept -- 2.2 Design -- 2.3 Realization -- 3 Applications -- 3.1 Direction of Arrival Estimation -- 3.2 Power Pattern Cross-Correlation Algorithm -- 3.3 Interpolation-Based Estimation -- 3.4 Multiplane Calibration for 2D DoA Estimation -- 3.5 DoA-Based Object Positioning -- 3.6 Single-Anchor Positioning System -- 3.7 Calibration-Free Indoor Localization -- 3.8 Other Applications -- References -- AI-Enhanced Connection Management for Cellular Networks -- 1 Introduction -- 2 Related Work -- 2.1 Data Rate Estimation -- 2.2 Interface Selection -- 3 Use Case and Research Challenge -- 4 Data Collection and Analysis -- 5 Uplink Data Rate Estimation -- 6 Interface Decision -- 7 Conclusion -- References -- Vehicle Communication Platform to Anything-VehicleCAPTAIN -- 1 Introduction -- 2 Problem Statement -- 3 VehicleCAPTAIN-A V2X Platform for Research and Development -- 3.1 The Platform -- 3.2 Message Library -- 3.3 ROS2 Support -- 4 Verification -- 4.1 Test Methodology -- 4.2 Results -- 4.3 Discussion -- 5 Key Performance Indicators -- 5.1 Use Cases Within InSecTT -- 5.2 Use Cases Within the Virtual Vehicle Research GmbH -- 6 Conclusion -- References. , AI-Enhanced UWB-Based Localisation in Wireless Networks -- 1 Introduction -- 2 Method Overview -- 3 AI for Solving UWB-Based Localisation Challenges -- 3.1 Localisation Challenges -- 3.2 AI Algorithms in UWB-Based Localisation Systems -- 4 Overview of Related Work -- 5 Application Example -- 5.1 KNN for LOS/NLOS Detection -- 5.2 KNN for Error Mitigation and Trustworthiness -- 6 Conclusion -- References -- Industrial Applications -- Approaches for Automating Cybersecurity Testing of Connected Vehicles -- 1 Introduction -- 2 State of the Art and Related Work -- 3 Automotive Cybersecurtiy Lifecycle Management -- 3.1 Threat Modeling -- 4 Cybersecurity Testing -- 4.1 Learning-Based Testing -- 4.2 Model-Based Test Case Generation -- 4.3 Testing Platform -- 4.4 Automated Test Execution -- 4.5 Fuzzing -- 5 Conclusion -- References -- Solar-Based Energy Harvesting and Low-Power Wireless Networks -- 1 Introduction -- 1.1 Solar-Based Energy Harvesting -- 2 Low-Power Network Protocols -- 2.1 Bluetooth Low Energy -- 2.2 IEEE 802.15.4 and Thread -- 2.3 EPhESOS Protocol -- 2.4 UWB Localisation -- 3 Power Consumption in Different Scenarios -- 3.1 Measurement Setup and Hardware -- 3.2 Power Consumption with Increasing Update Period -- 4 Available Energy in Real-World Scenarios -- 5 Experimental Results -- 6 Conclusion -- References -- Location Awareness in HealthCare -- 1 Terminology and Technology -- 1.1 Positioning, Localization, Tracking and Navigation -- 1.2 RF-Based Indoor Localization Technologies -- 1.3 Non-RF Based Localization Technologies -- 2 Pedestrian Dead Reckoning (PDR) -- 3 Others -- 3.1 Outdoor Localization Technologies -- 3.2 Technology Overview -- 4 Designing an End-To-End IoT Solution -- 4.1 Commissioning -- 4.2 Low Power Wide Area Networks (LPWAN) -- 4.3 Battery Lifetime -- 4.4 Going from Indoor to Outdoor -- 4.5 APIs for Location Services. , 4.6 Visualizing on a Map -- 4.7 Security and Privacy Aspects -- 5 Healthcare Use-Cases -- 5.1 Asset Tracking -- 5.2 Mass Casualty Incident (MCI) -- 5.3 Bed Management -- 5.4 Hospital Wayfinding -- 6 Use-Case Concept Demonstrator -- 6.1 Architecture -- 6.2 GeoJSON Server -- 6.3 Client Authentication -- 6.4 FHIR Compatibility -- 6.5 Location and Privacy -- 6.6 Additional Features -- 7 Conclusions/Next Steps -- References -- Driver Distraction Detection Using Artificial Intelligence and Smart Devices -- 1 Introduction -- 2 Definitions and Background -- 3 System Design -- 4 Machine Learning-Based Components -- 4.1 Use Case Definition and Components' Architecture -- 4.2 Data Acquisition and Pre-processing -- 4.3 Machine Learning Model Training and Experimental Results -- 4.4 Model Deployment on Smart Devices -- 5 Dashboard Application for Driver Distraction -- 6 Related Work -- 7 Conclusion and Future Work -- References -- Working with AIoT Solutions in Embedded Software Applications. Recommendations, Guidelines, and Lessons Learned -- 1 Introduction -- 2 Project Description and Goals -- 3 Project Design -- 4 Machine Learning in Embedded Systems -- 5 Communication Platform -- 5.1 Design Layout -- 5.2 Message Queuing with RabbitMQ -- 5.3 Inter-Process Messaging -- 6 Data Extraction -- 7 Training Data Set and Model -- 7.1 Design Stage 1 -- 7.2 Design Stage 2 -- 7.3 Alternative Model Setup -- 8 Cloud or Edge? -- 9 Security -- 10 Conclusion -- Appendix A -- Appendix B -- References -- Artificial Intelligence for Wireless Avionics Intra-Communications -- 1 Introduction -- 2 Use Case Objectives -- 3 Link Between Scenarios and Building Blocks -- 4 State of the Art -- 5 AI/IoT Added Value -- 6 Scenarios -- 6.1 Scenario 1: Interference Detection and Cancellation -- 6.2 Scenario 2: Verification and Validation of WAICs -- 6.3 Scenario 3: Battery-Less Devices. , 7 Performance Evaluation.

Additional Edition: ISBN 3-031-54048-4

Language: English

UID:

Format: 1 Online-Ressource

ISBN: 9783031540493

Content: This open access book provides an overview about results of the InSecTT project. Artificial Intelligence of Things (AIoT) is the natural evolution for both Artificial Intelligence (AI) and Internet of Things (IoT) because they are mutually beneficial. AI increases the value of the IoT through machine learning by transforming the data into useful information, while the IoT increases the value of AI through connectivity and data exchange. Therefore, InSecTT--Intelligent Secure Trustable Things, a pan-European effort with over 50 key partners from 12 countries (EU and Turkey), provides intelligent, secure and trustworthy systems for industrial applications to provide comprehensive cost-efficient solutions of intelligent, end-to-end secure, trustworthy connectivity and interoperability to bring the Internet of Things and Artificial Intelligence together. InSecTT creates trust in AI-based intelligent systems and solutions as a major part of the AIoT. InSecTT fosters cooperation between big industrial players from various domains, a number of highly innovative SMEs distributed all over Europe and cutting-edge research organizations and universities. The project features a big variety of industry-driven use cases embedded into various application domains where Europe is in a leading position, i.e., smart infrastructure, building, manufacturing, automotive, aeronautics, railway, urban public transport, maritime as well as health. The demonstration of InSecTT solutions in well-known real-world environments like airports, trains, ports and the health sector shows their applicability on both high and broad level, going from citizens to European stakeholders. The first part of the book provides an introduction into the main topics of the InSecTT project: How to bring Internet of Things and Artificial Intelligence together to form the Artificial Intelligence of Things, a reference architecture for such kind of systems and how to develop trustworthy, ethical AI systems. In the second part, we show the development of essential technologies for creating trustworthy AIoT systems. The third part of the book is composed of a broad variety of examples on how to design, develop and validate trustworthy AIoT systems for industrial applications (including automotive, avionics, smart infrastructure, health care, manufacturing and railway)

Note: Introduction -- Technology Development -- Industrial Applications.

Additional Edition: Erscheint auch als ISBN 3031540514

Additional Edition: ISBN 9783031540516

Additional Edition: ISBN 3031540484

Additional Edition: ISBN 9783031540486

Language: English

URL: kostenfrei

UID:

Format: xix, 441 Seiten : , Illustrationen, Diagramme (überwiegend farbig).

ISBN: 978-3-031-54048-6

Series Statement: Studies in computational intelligence volume 1147

Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-3-031-54049-3

Language: English

Subjects: Computer Science

UID:

Format: XIX, 441 p. 212 illus., 192 illus. in color. , online resource.

Edition: 1st ed. 2024.

ISBN: 9783031540493

Series Statement: Studies in Computational Intelligence, 1147

Content: This open access book provides an overview about results of the InSecTT project. Artificial Intelligence of Things (AIoT) is the natural evolution for both Artificial Intelligence (AI) and Internet of Things (IoT) because they are mutually beneficial. AI increases the value of the IoT through machine learning by transforming the data into useful information, while the IoT increases the value of AI through connectivity and data exchange. Therefore, InSecTT-Intelligent Secure Trustable Things, a pan-European effort with over 50 key partners from 12 countries (EU and Turkey), provides intelligent, secure and trustworthy systems for industrial applications to provide comprehensive cost-efficient solutions of intelligent, end-to-end secure, trustworthy connectivity and interoperability to bring the Internet of Things and Artificial Intelligence together. InSecTT creates trust in AI-based intelligent systems and solutions as a major part of the AIoT. InSecTT fosters cooperation between big industrial players from various domains, a number of highly innovative SMEs distributed all over Europe and cutting-edge research organizations and universities. The project features a big variety of industry-driven use cases embedded into various application domains where Europe is in a leading position, i.e., smart infrastructure, building, manufacturing, automotive, aeronautics, railway, urban public transport, maritime as well as health. The demonstration of InSecTT solutions in well-known real-world environments like airports, trains, ports and the health sector shows their applicability on both high and broad level, going from citizens to European stakeholders. The first part of the book provides an introduction into the main topics of the InSecTT project: How to bring Internet of Things and Artificial Intelligence together to form the Artificial Intelligence of Things, a reference architecture for such kind of systems and how to develop trustworthy, ethical AI systems. In the second part, we show the development of essential technologies for creating trustworthy AIoT systems. The third part of the book is composed of a broad variety of examples on how to design, develop and validate trustworthy AIoT systems for industrial applications (including automotive, avionics, smart infrastructure, health care, manufacturing and railway).

Note: Introduction -- Technology Development -- Industrial Applications.

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9783031540486

Additional Edition: Printed edition: ISBN 9783031540509

Additional Edition: Printed edition: ISBN 9783031540516

Language: English

DOI: 10.1007/978-3-031-54049-3

URL: https://doi.org/10.1007/978-3-031-54049-3