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Artificial Intelligence for Smart City Vision 2040 in Gulf RegionThis chapter delves into the transformative potential of Artificial Intelligence (AI) in spearheading the smart city vision by 2040 in the Gulf Region. It emphasizes the integration of AI with smart city governance, strategy, and infrastructure, underlining the pivotal role AI plays in digital transformation. The discourse navigates through strategic areas such as the exploitation of Large Language Models for enhancing smart city services, the utilization of AI in analyzing social network content and crowdsourcing applications, and leveraging AI’s reasoning capabilities to bolster predictive analytics and smart city services innovation. The chapter also showcases how AI-driven innovation fosters the development of new markets and industries within the smart city ecosystem. Highlighting the Gulf Region’s strategic investment in human capital and technology, the authors present a vision where smart cities serve as hubs of sustainability, innovation, and economic growth. Through the lens of the Smart City GSUTI Framework, the narrative illustrates the comprehensive integration of governance, strategy, utilization frameworks, technologies, and infrastructural capabilities. This holistic approach ensures that AI not only enhances the quality of life and economic prosperity in the Gulf Region but also positions it as a global leader in smart city development. The chapter is a call to action for leveraging AI’s potential to transform the Gulf Region into a model for sustainable, innovative, and smart urban development by 2040.
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The Role of Government in Ensuring Sustainability in Smart Urban Development: A Case Study of KuwaitThe emergence of smart cities, metropolises that integrate physical infrastructure, digital technology, and data analytics, and that focus on urban sustainability, have profoundly changed urban development. In the modern digital era, robust infrastructure has become an indispensable catalyst for urban advancement. Kuwait is dedicated to the integration of diverse renewable energy technologies in the development of smart cities that enhance energy security, promote innovation, and contribute to global climate change mitigation efforts. Focusing on smart cities within Gulf Cooperation Council (GCC) countries, a review is presented of how successfully they have effectively combined technology, infrastructure, and sustainability to serve as models for new global and regional developments. Insights into what makes a city smart are provided in different settings.
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A Holistic Framework for Smart Cities Governance in the Gulf Region: From Hype to Sustainable ImpactThis introductory chapter lays the foundation for a Holistic Smart City framework organized around five pillars namely: Smart City Governance – Strategy – Utilization – Technology – Infrastructure (GSUTI) model. Smart cities governance establishes the overarching structure for effective management, emphasizing data integrity, regulatory resilience, and civic engagement. The strategy pillar integrates vision, mission, and strategic initiatives aligned with sustainable development goals, ensuring resource allocation and innovation resilience. The Utilization Framework encompasses diverse domains like transportation, energy, and healthcare, thus prioritizing initiatives and monitoring impact, enabling technologies that drive smart city innovation, leveraging artificial intelligence (AI) (Chui et al., 2018), Internet of Things, blockchain, and cybersecurity to enhance efficiency and service delivery. Infrastructures and capabilities encompass physical and data ecosystems, from buildings and transportation hubs to big data streams and social media content. The chapter sets the context for the scientific discussion, offering practical insights into strategic consultation, performance monitoring, technology management, and data governance. It outlines directions for smart city development in the Gulf Region, including bold visions, megaprojects, national-level initiatives, data-driven services, and AI-driven excellence. This holistic framework provides a roadmap for smart city development, fostering sustainability, innovation, and societal well-being across the Gulf Region and beyond.
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Transforming Learning in STEAM: How AI Tools and Language Models Catalyze Educational AdvancementTechnology-enhanced learning (TEL), particularly in science, technology, engineering, arts, and math (STEAM), revolutionizes educational approaches by fostering active, transformative learning and expediting the learning process. TEL employs various tools like online courses, artificial intelligence (AI) technologies, virtual reality (VR), simulations, makerspaces, visual learning, and project-based learning, all contributing to accelerated learning in STEAM. A notable TEL innovation is the emergence of Large Language Models (LLMs) and AI chatbots, exemplified by the release of GPT-3 in December 2022. These tools utilize extensive parameters to generate natural language and perform tasks such as classification and prediction, thereby offering personalized and collaborative learning experiences essential for STEAM education. The generative pre-training transformer (GPT), a leading model in natural language processing (NLP), excels in generating human-like text and handling complex tasks like translation, summarization, and question answering. This chapter explores TEL environments that support transformative learning in STEAM, focusing on AI models. It reviews research on TEL’s impact on STEAM education, discussing the constructionism theory and emphasizing TEL’s role in creating engaging, student-centered learning experiences. However, challenges like technology access, instructor training, infrastructure, internet connectivity, and hardware resources are crucial. Additionally, the rise of AI brings ethical concerns regarding privacy, security, and potential biases in AI algorithms. Despite these hurdles, TEL’s potential to enhance STEAM learning experiences and accelerate the educational process is significant. By effectively implementing TEL strategies and leveraging LLMs and AI tools, educators can substantially improve learning outcomes in STEAM education.
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Enhancing Scientific Rigor With Editorial Roles and AI: Insights From Evaluating Manuscripts in Digital Health and Personalized MedicineIn the evolving landscape of open-access scientific journals, the roles of editors and reviewers are crucial in ensuring quality and integrity. This chapter analyzes the experiences of two college professors—a cell biologist/biophysicist and a computer scientist—who, in addition to various fields of study, have edited and reviewed over 50 high-impact journal manuscripts related to digital health (DH) and precision/personalized medicine (PM). Their journey underscores the importance of multi-disciplinary approaches and artificial intelligence (AI) in evaluating complex research. The chapter highlights specific cases of DH and PM illustrating how digital solutions and AI have shaped their perspectives. Key elements of robust manuscript evaluation, such as methodological rigor and clinical relevance, are discussed. The chapter explores the emerging role of AI in enhancing the editorial process, from initial screening to detailed analysis. The findings advocate for active participation in peer review and editorial roles, emphasizing their benefits.
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How artificial intelligence affects the future of pharmacy practiceArtificial intelligence (AI) will play an increasingly important role in the future of pharmacy practice.is transforming traditional pharmacy practice and can improve patient care and drug management. Artificial intelligence (AI) is changing the role of pharmacists in the healthcare system. The integration of artificial intelligence(AL) in pharmacy practice created many opportunities for pharmacists and other majors in the pharmacy field but also challenges, because beginnings may include many challenges even if researchers, scientists, and people with experience talk about it in the field of artificial intelligence(AL) in pharmacy, it has not been addressed sufficiently. Artificial intelligence (AL) can have a significant impact on pharmacists' focus, shifting it away from dispensing drugs and toward delivering a larger variety of patient services. Pharmacists may use Al to help patients get the most out of their prescriptions and stay healthy, artificial intelligence (AL) systems may hold the promise of brief duties and tasks by increasing productivity and decreasing the time and effort for pharmacists which due to increases the quality of patients service and this is our aim as a healthcare provider. Artificial intelligence (AI) may be a useful tool for patients to guide how and where to obtain the most cost-effective health care and how to best communicate with health care professionals; improve the value of data from wearable devices; provide daily lifestyle guidance; integrate diet and exercise, and supporting compliance and adherence to treatment.
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Visioning the Future of Higher Education Through Artificial IntelligenceThe dawn of Artificial Intelligence (AI) in higher education (HE) is not just on the horizon; it's here, promising a transformative leap forward. This shift is not simply about adopting new technologies; it's about redefining educational paradigms to meet specific challenges – from enhancing support and critical thinking to improving outcomes and fostering teamwork. This chapter outlines a comprehensive strategy to integrate AI into HE, spotlighting personalized learning, content generation, and remote learning, among others, as key domains ripe for AI's influence. An effective AI strategy will foster excellence and enable HE institutions to unlock the potential of technology for students and faculty alike. At its core, the proposed AI development strategy targets five critical areas: training, career growth, skill enhancement, learning, and team building. These areas ensure that all HE community members are well-equipped to navigate the AI-enhanced landscape of future jobs and challenges. However, realizing the full benefits of AI transcends the deployment of tools and systems; it requires strategic planning, investment in people, and policy changes. HE must cultivate champions to spearhead this transformation, emphasizing that success is not just measured in output but in the cultivation of socially responsible citizens. To harness AI's full capacity, we must transcend outdated stereotypes and metrics, fostering an educational environment that prepares students for the future. The ultimate goal is not just to integrate AI into HE but to use it as a catalyst for growth, innovation, and a better future for all.
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The Artificial Intelligence (AI) Landscape in Higher Education (HE): Current Developments, Opportunities, and ThreatsThe evolution of Artificial Intelligence (AI) in higher education marks a paradigm shift, driving significant changes in pedagogical approaches and learning methodologies. With the rise of generative AI and artificial general intelligence (AGI), institutions have witnessed a transformative era where traditional content creation and delivery are being redefined. Start-ups like OpenAI and Anthropic have been at the forefront, offering tools like ChatGPT and Claude-3, which reshape natural language processing and forecast a future where AI integrations are seamless and pervasive. This chapter provides a critical overview of the current AI-driven applications enhancing personalized learning, content generation, and remote learning. Tools such as Mainstay, CourseGenie, and AIDES demonstrate AI's capacity to improve student engagement and success rates, while Degreed and Gnowbe showcase the broadening horizons of AI in skills building and microlearning experiences. Furthermore, platforms like Elicit and Research Rabbit exemplify the transformation in research and academic writing, albeit not without raising ethical concerns. In conclusion, AI's permanence in the educational landscape is unquestionable, calling for strategic frameworks that empower educators and students to harness its benefits effectively. The imminent expansion of the AI tool ecosystem necessitates preparedness for substantial shifts in educational practices, where ethical considerations and value-based strategies become paramount. Higher education institutions must align with this technological momentum, ensuring AI's potential is maximized in an ethical, inclusive, and impactful manner.
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Digital Intersections: Synergies Between the Gig Economy and Evolution of the Smart CityTechnology and a gig economy have affected how people are employed, with shorter-term, more flexible, and technologically mediated work arrangements increasingly becoming the norm. The digital platform, which acts both as a marketplace and a “shadow employer,” makes this possible, with workers provided with unprecedented autonomy and flexibility. The authors examine the interplay between the gig economy and the concept of the smart city – an urban environment reliant upon information and communication technologies – and focus on how technological integrations such as blockchain, the collective network of connected devices, and the technology that facilitates communication between devices and the cloud, as well as between the devices themselves (Internet of Things [IoT]), and 5G, bolster opportunities for gig workers to carve out an existence in a perpetually changing landscape. Examples are provided for the global giant Amazon and the regional businesses Talabat and Raha in the Gulf Cooperation Council (GCC). Application of real-time tracking, precision-driven management, and decentralized transactions, provides gig workers new opportunities for employment in their evolving digital smart-city environment.
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Innovation, leadership, and education: How Effat University is paving the way for Vision 2030Higher education institutions like Effat University play a critical role in realizing the ambitious goals of Saudi Arabia’s Vision 2030, which emphasizes adaptability, agility, and sustainability in the educational sector. With the higher education landscape undergoing rapid transformation globally, institutions are compelled to rethink curricula and align more closely with the changing needs of students, industry, and the government. Effat University, situated at the confluence of Saudi Arabia’s Vision 2030 and the global Sustainable Development Goals (SDGs), shows adaptability, agility, and sustainability in the higher education sector. At the heart of Effat’s mission lies the IQRA core values, anchoring its academic and administrative endeavors and fostering graduates who are holistic, ethically grounded, and attuned to global challenges. This book chapter investigates Effat University’s distinctive approach, fortified by innovative initiatives, transformative leadership, expansive research activities, and the unwavering IQRA principles, as it positions itself to further the goals of Vision 2030 and the SDGs. Effat’s research, diverse in its scope and impact, ranges from cutting-edge technological advancements to interdisciplinary collaborations that address both local and global challenges. Using a mixed-method approach and drawing from internal data and insights from the university’s archives the chapter underscores Effat University’s commitment to innovation, interdisciplinary education, research excellence, international collaborations, and sustainable practices, all harmonized by the guiding IQRA values. These concerted efforts resonate deeply with Vision 2030 and the SDGs, setting the stage for sustained academic excellence and solid foundation for future academic and societal progress.
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The challenges for the next generation digital health: The disruptive character of artificial intelligence and machine learningArtificial Intelligence is not a technology. Artificial Intelligence is a robust strategy for the digital transformation of anything. This bold characteristic of AI is the focus of this introductory chapter. We elaborate on the unique value proposition of AI and its contribution to the formulation of the emerging, next-generation value-based ecosystem for Digital Health. Then main discussion of the chapter is dedicated on disruptive scenarios and use case for AI-Enabled next-generation Generation Digital Health Services and Solutions. We aim by this short coverage and discussion to highlight bold directions for the utilization of AI in the eHealth context. We are also commenting on various technological, business, strategic and ethical aspects of AI. Last but not least, we convey the main message of the chapter: A robust, resilient strategy for the training and upskilling of stakeholders in healthcare in the foundations, models and strategy of AI is required. We are somehow carriers of a bold change in our societies and in our healthcare ecosystem. It is up to us, as humans with intuition and decision-making capability, to envision the way that the disruptive technology of AI will add value to healthcare, patients' health status and people' wellbeing in the next few years.
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Chapter 14. Transformative leadership and sustainable innovation in higher education: Setting the context.Transformative leadership is a holistic and bold approach for the next generation of higher education. In this chapter, we provide an introductory, definitive discussion of the phenomenon and integrate it with the concept of sustainable innovation. In Section 1, we introduce a high-level integrated approach to transformative leadership in higher education institutions. We define and discuss diverse pillars. In Section 2, we propose a contextual framework for transformative leadership as a value space. In an effort to provide guidelines and principles for the crafting of a transformative leadership strategy, we propose indicative actions and initiatives for the deployment of transformative leadership in higher education. Finally, in Section 4, we summarized some simple designs for tools and instruments to support the documentation of the transformative leadership strategy, including the transformative leadership scorecard and the systematic overview of the portfolio of transformative educational programs. We also comment on the significance of social impact and research, innovation, and sustainability aspects of the strategy. The contribution of this chapter is multi-fold. It can be used as a reference document for administrators interested in the design and execution of transformative leadership in universities and colleges. It also provided guiding principles for researchers interested in further contributions in the domain.
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Automated Recognition of Human Emotions from EEG Signals Using Signal Processing and Machine Learning TechniquesOne of the most difficult challenges in pattern recognition, machine learning, and artificial intelligence is emotion recognition. For automatic emotion recognition, voices, images, and electroencephalography (EEG) signals have been employed. Emotion recognition systems based on brain activity are extremely useful in a variety of sectors. In today’s computer age, providing reliable information on emotion recognition is a critical task. Because emotional activity is complicated, it is critical to apply cutting-edge technology and profit from signal processing and machine learning methods while learning about it. Although individuals have been interested in documenting emotional activities over the past decade, there are still fundamental issues that must be addressed in order to take advantage of technology in the understanding of emotion activity. In this chapter, we will go over the most recent signal processing and machine learning algorithms for detecting emotion activity information in the system. We will also cover the difficulties and significant considerations associated with emotion recognition. Several open concepts will be presented for future research to use in understanding the challenges with emotion recognition. Finally, we present some specific examples of emotion recognition using EEG signals employing various AI and signal processing techniques.
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Artificial Intelligence-Enabled EEG Signal Processing-Based Detection of Epileptic SeizuresEpilepsy affects numerous people worldwide. Electroencephalography (EEG) is an important tool in the diagnosis of epilepsy. Real-time seizure onset detection is critical for accurate evaluation, presurgical assessment, seizure prevention, and emergency warnings and overall improving patients’ quality of life, but manually examining EEG signals is tedious and time-consuming. To assist neurologists, many automatic systems have been proposed to support neurologists utilizing conventional techniques, and these have performed well in detecting epilepsy. Big data applications, particularly biomedical signals, are becoming more appealing in this era as data collection and storage have expanded in recent years. Because data mining approaches are not adaptable to the new needs, big data processing to extract knowledge is difficult. In this chapter, we review AI-enabled signal processing-based approaches for detecting epileptic seizures using EEG signals including with examples.
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Research and Education Skills as a core part of Digital Transformation in Healthcare in Saudi ArabiaThe adoption of digitalization technologies in healthcare systems is crucial for improving the delivery of medical services, facilitating patient access, and enhancing the overall patient experience. However, the experience and challenges of the Saudi healthcare system in adopting digital transformation have received little attention in the literature. Thus, this chapter aims to provide an overview of the digital transformation process in the Saudi healthcare system. The authors also shed light on the major challenges and suggested technology-based solutions. This chapter was written in light of the available global and local literature discussing the digitization of the health sector. Moreover, the Saudi governmental documents and official reports were utilized to include the latest updates and future plans for the local digital transformation strategy. In paving the way toward digital transformation, many challenges have been faced in areas such as medical records unification, technical infrastructure, and workforce capability. Solutions such as telemedicine applications, artificial intelligence, cybersecurity, and blockchain have been gradually applied to achieve the goal of transformation by 2030. Saudi Arabia's digital transformation began in 2018, with the implementation of the Vision 2030’s rapid digital change. With the emergence of the COVID-19 pandemic, a leap in utilizing digital health solutions has been noticed locally. Nevertheless, more action plans are needed to address the challenges and implement suitable solutions accordingly.
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Digital health as a bold contribution to sustainable and social inclusive development.In this volume we tried to provide indicative complementary aspects of the Next Generation eHealth. In the concluding chapter of the book we elaborate with the capacity of Digital Health Ecosystem to serve as a bold enabler of the Sustainable Development Goals. We elaborate on the enabling technologies, the stakeholders and the emerging marketplace of digital health services as key determinants of the so-called Sustainable Health Ecosystem. We also discuss the Digital health as a pivotal pillar of Social Inclusive Development and we provide some directions. This chapter can serve as a reference for a contextual framework of Digital Health as a Sustainable Development enabler.
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Data Governance in Healthcare OrganizationsThe Next Generation eHealth has a critical data goverance component. In order also to have an effective design and implementation of a robust Data Strategy, a holistic approach to Data governance is requires. In this context, this chapter introduces the readers to the concept of Data Governance as it is applied in Health Organizations. We, elaborate on the state of the art and also, we summarize in a compact way a sophisticated approach for the collection of data and evidence for drafting resilient Data Governance Strategies in health organizations. The main contribution of the chapter is the communication of best practices for the design and implementation of Data Governance and Data Strategy policies. The approach can be re-used by various stakeholders, and contributes to the body of knowledge of Data Governance strategy for next generation eHealth services and applications.
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Enhancing patient welfare through responsible and AI-driven healthcare innovation: Progress made in OECD countries and the case of Greece.The rapid advancement of Artificial Intelligence (AI) in healthcare presents challenges and opportunities for patient welfare. New policies, governance, and interoperability standards have been introduced necessitating patient and stakeholder engagement. The Organization for Economic Cooperation and Development (OECD) countries have prioritized health transformation through the use of health data, digital tools, and AI-driven healthcare innovation. AI has enormous potential to improve activities from research to treatment, administration, patient welfare, and value for money. However, responsible development is crucial to avoid misuse. This chapter explores the ethical considerations of AI-generated healthcare innovation, emphasizing the need for a balance between AI-driven progress and patient welfare. It examines progress in OECD countries, with a specific focus on enhancing patient welfare in Greece. Challenges related to treatment, data privacy, transparency, fairness, algorithmic bias, informed consent, and impact on healthcare professionals are discussed. Regulatory frameworks are considered as well as professional guidelines in the context of international collaboration. The chapter provides insights and recommendations for a responsible and patient-centric approach, prioritizing patient welfare while navigating ethical dimensions.
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Designing robust and resilient data strategy in health clusters (HC): Use cases identification for efficiency and performance enhancement.The design, implementation of execution of Data Strategy within a health cluster is a sophisticated process. Diverse actors, stakeholders and business functions are involved. The need for designing roadmaps for the implementation of the strategy, also incorporates the identification of use cases for novel initiatives, services and systems. In this chapter we communicate our experience in designing use cases as carriers of enhanced efficiency and performance that is data driven. This is a high value intellectual effort aiming to strategize the allocation of resources and the design of new robust and resilient systems to promote efficiency and performance. We exploit the outcomes of maturity assessment for Data Governance and Data Strategy and we provide a systematic methodology for the implementation of a resilient strategy in the health cluster.
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Transformative leadership in Kuwait Direct Investment Promotion Authority: Investing in talent, innovation, and the next generationDigital transformation is becoming a necessity for all organizations all over the world. The importance of digital transformation is not only applicable to the private sector but also extends to the public sector. Kuwait boasts the Kuwait Direct Investment Promotion Authority (KDIPA), a pivotal entity entrusted with the mission of spearheading investment promotion across diverse sectors. More importantly, the focus has been recently on investing on digital transformation technologies where their statistics shows that 33% of their investment are in the emerging technologies. However, the success of KDIPA was not a mere chance or coincidence where it is really attributed to the transformative leadership that it has. It started to invest in projects that develop the talents and skills of Kuwaitis to create sustainable development and bring innovative technologies to the state of Kuwait. This chapter provides an overview of digital transformation and the role of KDIPA and its transformative leadership in attaining the Strategic Development Goals (SDGs) for a new Kuwait Vision of 2035.
