Accelerating Digital Transformation with the Cloud and the Internet of Things (IoT)

Accelerating Digital Transformation with the Cloud and the Internet of Things (IoT) is a reference for IT engineers and decision-makers who may engage in IoT platform pilot projects. The resources covered in this book help establish plans for sustainable operations and management and assist with the long-term procurement of relevant IoT technologies. The aim of the book is to be exhaustive and holistic by pointing out numerous issues and related solution options that guide with daily challenges when deploying and running IoT platforms.

The book is divided into three parts where each part includes relevant theoretical chapters and applied case studies. Part One focuses on architectural and federation options for the design and implementation of IoT platforms that foster strategic collaboration opportunities. Part Two addresses vertical security challenges across IoT platform layers. Finally, Part Three shows how IoT is driving the digital transformation wheel through existing and forthcoming case studies.

Title of Book
Cover image
Title page
Table of Contents
Copyright
Part 1: Cloud and IoT ecosystem
Chapter 1: Cloud-to-things continuum: technical challenges and economical opportunities
Introduction
1.1. From cloud to edge: the emergence of IoT in cloud computing
1.1.1. The building blocks of the cloud-to-things continuum
1.1.2. Overview of the cloud-to-things continuum
1.1.3. Data flow in the cloud-to-things continuum
1.1.4. Harnessing the power of cloud-to-things continuum: opportunities for social welfare, cost savings, and business growth
1.2. Technical challenges of cloud-to-things continuum
1.2.1. Connectivity challenges: interoperability, standards, and protocols
1.2.2. Security challenges: authentication, authorization, and data privacy
1.2.3. Scalability challenges: handling massive amounts of data generated by IoT devices
1.3. From connected devices to connected business: how cloud-to-things is enabling digital transformation?
1.3.1. Digital transformation: why it matters and how cloud-to-things continuum can help?
1.3.2. Harnessing the synergy of IoT and cloud computing to drive digital transformation
1.3.3. IoT and cloud computing: key enablers for business agility and competitive advantage
1.3.4. Real life applications
1.4. Business challenges of cloud-to-things continuum
1.4.1. Data ownership and governance issues in the IoT and cloud era
1.4.2. Overcoming organizational silos: integration challenges of IoT and cloud in the business environment
1.4.3. Barriers to cloud adoption for IoT applications
1.4.4. Legal and regulatory hurdles in IoT and cloud computing
1.4.5. Business model innovation: creating new revenue streams with cloud-to-things continuum
1.4.6. Cost and resource allocation issues in implementing IoT and cloud solutions
1.4.7. Balancing innovation and risk in IoT and cloud adoption
1.4.8. Maximizing ROI in IoT and cloud investments
1.5. Conclusion
Chapter 2: Cloud-based IoT platforms for digital transformation
Introduction
2.1. IoT platform definition and overview
2.2. Key elements and features of IoT platforms
2.2.1. Device management
2.2.2. Communication management
2.2.3. Data management
2.2.4. Application management
2.3. IoT platform categories
2.3.1. Commercial IoT platforms
2.3.2. Open source IoT platforms
2.3.3. Hybrid IoT platforms
2.4. IoT platforms for enabling digital transformation
2.4.1. IoT platforms for climate change
2.4.2. Smart city platforms for societal change
2.4.3. Business transformation
2.5. Considerations for selecting a cloud-based IoT platform
2.6. Challenges and future trends in cloud-based IoT platforms
2.6.1. Common challenges in implementing IoT platforms and utilization obstacles
2.6.2. Evolving trends and advances in IoT platform technologies
Chapter 3: Enabling digital transformation with IoT cloud applications and services
3.1. Introduction
3.2. Laying the foundation for scalability and flexibility: technology infrastructure
3.2.1. Revolutionizing business operations with next generation ERP systems
3.2.2. Harnessing the power of CRM through digital transformation
3.2.3. Enhancing product information flow with digital transformation: a paradigm shift
3.2.4. Essential technology stack for effective digital transformation
3.2.5. Key performance indicators (KPIs) to gauge scalability
3.3. Agile development and operations
3.3.1. Agile practices
3.3.2. Overcoming Agile & DevOps challenges in cloud-to-things environments
3.3.3. Enhancing operational efficiency and security in the cloud-to-things continuum
3.3.4. KPIs to gauge security compliance
3.4. Creating digital experiences
3.4.1. Harnessing data and analytics: stimulus for digital transformation
3.4.2. Redefining leadership: skilled talent pool
3.4.3. Increasing footfall: customer-centric approach
3.4.4. Embracing affordable strategies: cost efficiency
3.5. Data-driven decision-making
3.5.1. Leveraging open datasets
3.5.2. Data analytics techniques
3.5.3. Real-time data processing and analysis
3.6. Conclusion
Chapter 4: Strategies for driving IoT data to the cloud in digital transformation initiatives
4.1. Introduction
4.2. IoT data in digital transformation
4.2.1. Types of IoT data
4.2.2. Significance of IoT data
4.3. Cloud computing for IoT data management
4.3.1. Adaptability to data fluctuation
4.3.2. Advanced data analytics
4.3.3. Data governance in the cloud
4.3.4. Edge-to-cloud orchestration
4.3.5. Data collection at the edge
4.4. IoT data lifecycle in digital transformation
4.4.1. Stages of the IoT data lifecycle
4.4.2. The role of IoT data lifecycle in driving digital transformation
4.5. Real-life use cases of IoT data in cloud-driven digital transformation
4.6. Conclusion
Chapter 5: Unlocking value with the cloud-to-things continuum
5.1. Introduction
5.2. Tracing the cloud-to-thing value chain
5.2.1. IoT data mining to increase business value
5.2.2. Value of association patterns in IoT data
5.2.3. Sequence analysis in IoT data
5.2.4. Classification in IoT data mining
5.2.5. IoT data clustering
5.2.6. Forecasting with IoT data
5.3. Enhanced business value through real-time IoT data
5.3.1. Real-time data utilization
5.4. Case studies of increased value proposition
5.4.1. Education sector
5.4.2. Healthcare sector
5.4.3. Environment protection sector
5.4.4. Precision agriculture
5.4.5. Cyber security sector
5.4.6. Energy management sector
5.4.7. Transportation sector
5.5. Cloud-to-things continuum: adding value to digital transformation
Chapter 6: IoT inter-cloud interoperability for sustainable digital transformation
6.1. Introduction
6.1.1. IoT and inter-cloud computing
6.1.2. Interoperability in digital transformation
6.2. Understanding IoT and inter-cloud computing
6.2.1. Inter-cloud computing: features and characteristics
6.2.2. IoT challenges in inter-cloud environments
6.3. IoT inter-cloud interoperability
6.3.1. Standardization matters
6.3.2. Strategies for achieving inter-cloud interoperability in IoT
6.4. Sustainable digital transformation through IoT inter-cloud interoperability
6.4.1. Economic sustainability: cost-effective integration
6.4.2. Environmental sustainability: efficient resource utilization
6.4.3. Social sustainability: enhanced user experience and inclusivity
6.5. Real-life use cases
6.5.1. Healthcare: seamless data flow across multiple cloud providers
6.5.2. Smart cities: integrated urban management across platforms
6.5.3. Manufacturing: streamlined supply chain with interoperable IoT
6.6. Future directions in IoT inter-cloud interoperability
6.6.1. Advances in semantic interoperability
6.6.2. AI and ML for seamless data integration
6.6.3. Predicting the evolution of standards and protocols
6.7. Conclusion
Chapter 7: The Enterprise IoT
7.1. Introduction
7.2. Consumer IoT vs enterprise IoT
7.2.1. Scalability aspects
7.2.2. Connectivity aspects
7.2.3. Security aspects
7.2.4. Data processing and analytics aspects
7.2.5. Maintenance and device management aspects
7.3. Cloud-to-things infrastructure in enterprise IoT platforms
7.3.1. Cloud layer infrastructure
7.3.2. Edge layer infrastructure
7.3.3. Device layer infrastructure
7.3.4. Key enterprise IoT platforms
7.3.5. Interoperability challenges in enterprise IoT cloud platforms
7.4. AI and IoT integration in enterprises
7.4.1. Predictive maintenance and reduced downtime
7.4.2. Enhanced operational efficiency and optimization
7.4.3. Personalized customer experiences and improved products
7.4.4. Improved safety and security
7.4.5. New business models and revenue streams
7.5. Enterprise IoT in action: case studies
7.5.1. Environmental monitoring
7.5.2. Smart buildings and smart cities
7.5.3. Employee productivity and customer services
7.6. Conclusion
Part 2: IoT cloud security
Chapter 8: IoT cloud security in digital transformation
8.1. Introduction
8.2. Information security background
8.2.1. Vulnerability assessment
8.2.2. Threat modeling
8.2.3. Cyber attack
8.2.4. Risk analysis
8.3. IoT vulnerabilities and their cloud implications
8.3.1. Understanding IoT vulnerabilities
8.3.2. Cloud-specific threats in an IoT-integrated environment
8.3.3. Potential attacks in IoT cloud networks
8.4. Best practices for ensuring IoT-cloud security
8.4.1. Risk evaluation of IoT-cloud systems
8.4.2. Security protocols for IoT-cloud systems
8.4.3. IoT device software/firmware maintenance
8.4.4. Regulatory compliance and security standards
8.5. Securing critical infrastructures in IoT-cloud environments
8.5.1. Cybersecurity workflow in critical infrastructure protection
8.5.2. Critical infrastructures are at risk!
8.6. Threats and mitigation strategies in IoT-based digital transformation
8.6.1. The evolving threat landscape in IoT
8.6.2. Emerging threats in the cloud-to-things model
8.6.3. Threat modeling in IoT
8.6.4. Mitigation strategies
8.6.5. Case studies: overcoming IoT security threats
8.7. Conclusion
Chapter 9: Discovering and analyzing IoT-cloud vulnerabilities
9.1. Introduction
9.2. Understanding IoT-cloud vulnerabilities
9.2.1. IoT-cloud vulnerability challenges and specific risks
9.2.2. Vulnerability lifecycle
9.2.3. Common types of vulnerabilities
9.3. Discovering vulnerabilities
9.3.1. Vulnerability discovery methods
9.3.2. Tools for discovering vulnerabilities in IoT and cloud systems
9.3.3. The role of testbeds in discovering vulnerabilities
9.4. Analysis and classification of vulnerabilities
9.4.1. Methods for analyzing the identified vulnerabilities
9.4.2. Classifying vulnerabilities
9.5. IoT-cloud vulnerability management
9.5.1. Strategies for managing vulnerabilities in IoT cloud environments
9.5.2. Patch management and regular updates
9.5.3. Data-driven vulnerability management
9.6. Case studies: vulnerabilities and mitigation strategies
9.6.1. Healthcare IoT: protecting sensitive data
9.6.2. Smart city infrastructure: addressing systemic weaknesses
9.6.3. Industrial IoT (IIoT): securing operational technology
9.6.4. Cloud integration: strengthening the IoT backbone
9.7. Conclusion
Chapter 10: IoT security best practices
10.1. Introduction
10.2. Securing IoT devices
10.2.1. Device identity and security management
10.2.2. User access control in IoT devices
10.2.3. Automated firmware updates
10.3. Network security
10.3.1. Intrusion detection and prevention
10.3.2. Advanced encryption techniques for IoT
10.4. Edge and cloud security
10.4.1. Security as a service for edge-enabled IoT systems
10.4.2. Federated identity management
10.5. Leveraging data for security
10.5.1. Data-driven security with SIEM
10.5.2. AI for anomaly detection and network monitoring
10.5.3. Data-centric risk assessment
10.6. Physical security
10.6.1. Device hardening and environmental protections
10.6.2. Access control and surveillance
10.7. Conclusion
Part 3: Cloud based IoT digital transformation in action!
Chapter 11: Smart citizenship through IoT-cloud adoption
11.1. Introduction
11.2. Foundational elements of smart citizenship
11.2.1. Civic engagement
11.2.2. Overcoming the digital divide
11.2.3. Security practices
11.2.4. Awareness of data privacy
11.2.5. Ethical considerations and public trust
11.3. Open Data for smart citizenship empowerment
11.3.1. Open Data catalogs for smart city digital transformation
11.3.2. Technologies enabling Open Data platforms
11.4. Innovative education models for smart citizenship
11.4.1. E-learning and u-learning
11.4.2. Ambient learning spaces
11.5. Practical initiatives and campaigns
11.5.1. Making Sense (Barcelona, Spain)
11.5.2. Smart Citizens Lab (Amsterdam, Netherlands)
11.5.3. GammaSense (Netherlands)
11.5.4. COVID-19: integrated contact tracing systems (South Korea and Singapore)
11.6. Conclusion
Chapter 12: Driving change and innovation with IoT-cloud-based digital transformation
12.1. Introduction
12.2. Managing change: towards digital transformation
12.2.1. Theory of change (ToC)
12.2.2. Driving change through IoT-cloud integration
12.2.3. Societal impact of digital transformation
12.3. Business model transformation
12.3.1. Predictive maintenance as a service (PdMaaS)
12.3.2. Remote equipment monitoring as a service (REMaaS)
12.3.3. Precision agriculture as a service (PAgaaS)
12.3.4. Healthcare as a service (HCaaS)
12.3.5. Supply chain tracking as a service (SCaaS)
12.4. Strategies for implementing change
12.4.1. Identifying change agents
12.4.2. Overcoming challenges
12.4.3. KPIs and metrics
12.5. Enabling readiness to change
12.6. Conclusion
Chapter 13: Digital transformation with IoT and cloud in healthcare
13.1. Introduction
13.2. Healthcare IoT
13.2.1. An overview of IoT devices and sensors for healthcare
13.2.2. The role of cloud computing in healthcare data integration and analysis
13.3. Enhancing patient care with IoT and cloud
13.3.1. Remote patient monitoring and telehealth solutions
13.3.2. Personalized medicine through data analytics
13.4. Healthcare operational efficiency and cost reduction with IoT and cloud
13.4.1. IoT and cloud in hospital and facility management
13.5. IoT data management in healthcare
13.5.1. Challenges in healthcare data management
13.5.2. Data-driven analytics in healthcare
13.6. Case studies of successful IoT integration in healthcare
13.6.1. Analysis of successful digital transformation projects in healthcare
13.6.2. Lessons learned and best practices
13.7. Conclusion
Chapter 14: IoT-cloud for social good in municipality services
14.1. Introduction
14.2. Environmental sustainability with IoT and cloud
14.2.1. Preserving habitats and resources: sensor-driven environmental monitoring
14.2.2. Traffic safety
14.2.3. Enhancing urban life
14.3. Measuring success: challenges and value proposition
14.3.1. Success definition
14.3.2. Value proposition
14.3.3. Evaluation in real-world settings
14.4. Data protection and ethical considerations in IoT implementations
14.4.1. Key principles of data protection
14.4.2. Ethical considerations in IoT implementations for public services
14.5. The future of IoT in public sector services
14.5.1. Striking a balance: innovation, user focus, and societal benefit
14.5.2. Privacy guidelines for ethical and responsible implementation
Chapter 15: Connected mobility solutions
15.1. Introduction
15.2. Understanding mobility services and transportation logistics
15.2.1. Mobility services
15.2.2. Transportation logistics
15.3. Evolution of connected mobility
15.3.1. Projected trends in connected mobility
15.3.2. Core components of vehicle connectivity
15.3.3. Software-defined vehicle
15.4. Transformation of connected transportation
15.4.1. Evolution of connected transportation over the past decade
15.4.2. The integration of IoT and cloud in transportation
15.5. Mobility solutions
15.5.1. Mobility as a service (MaaS)
15.5.2. In-vehicle connectivity
15.6. Transportation solutions
15.6.1. Smart city traffic management system
15.6.2. Predictive maintenance for fleet vehicles
15.7. Business aspects of smart vehicles and connected transportation
15.7.1. Business models
15.7.2. Economic impact
15.8. The future of connected mobility and transportation
Chapter 16: IoT-cloud business case studies and investment roadmap for sustainable digital transformation
16.1. Introduction
16.2. Synthesis of IoT and cloud computing impact
16.2.1. The paradigm of sustainability
16.2.2. The engine of innovation
16.2.3. The framework of resilience
16.3. Advanced business cases
16.3.1. Innovative partnerships
16.3.2. Scaling solutions
16.3.3. Cross-sector impact
16.3.4. Cross-sectoral impact
16.4. Crafting a future-ready investment roadmap
16.4.1. Investment in emerging technologies
16.4.2. Funding models and financial instruments
16.4.3. Developing a future-ready roadmap
16.5. Synthesis of key themes and takeaways
16.6. Conclusion
Index

YA

Yacine Atif

Yacine Atif is a Professor at Skovde University in Sweden since January 2016. He received a PhD degree in Computer Science from Hong Kong University of Science and Technology (HKUST) in 1996. After graduation, he worked at Purdue University in USA as a Post-Doc and then joined a faculty position at Nanyang Technological University (NTU) in Singapore. Since 1999 he was affiliated with UAE University as a faculty, then Program Chair of Enterprise Systems at the College of Information Technology. bringing together ideas of educational design and architectural abstractions used in software engineering. He focuses on the evolution of smart cities induced by the emergence of Internet of Things technologies. More specifically, he investigates IoT platform models in urban informatics and install new competences for digital smart citizens. He has 25 years of academic publishing experience in Computer Science subjects, with focus on technical aspects related to Internet evolutions that support sustainable digital developments. I worked on innovative smart environment projects (e.g., smart-parking, smart-campus, smart-energy, smart-city, etc.), as well as related cybersecurity issues that could hamper these developments. I strive to empower smart- citizenship through education and research publications to facilitate sustainable transitions.

Affiliations and expertise

Professor, School of Informatics University of Skövde, Sweden

SM

Sujith Samuel Mathew

Sujith Samuel Mathew received his Ph.D. in Computer Science from the University of Adelaide, South Australia. His research interests are in distributed and mobile computing, with focus on the Internet of Things (IoT) and related smart city applications. He has over twenty years of experience working both in the IT industry and academia. He has held positions as Group Leader, Technical Evangelist, and Software Engineer within the IT industry. In academia, he has been teaching IT courses and pursuing his research interests in parallel. Presently, he is an Associate Professor with the College of Interdisciplinary Studies (CIS) at Zayed University in Abu Dhabi. He has twenty years of experience in the IT academia and industry focusing on software technologies, distributed systems, and mobile computing. Published articles in peer reviewed journals, led research groups, and continues to work with innovative projects in smart city applications.

Affiliations and expertise

Associate Professor, College of Interdisciplinary Studies, Zayed University, Abu Dhabi, United Arab Emirates

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Accelerating Digital Transformation with the Cloud and the Internet of Things (IoT)

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