Cybersecurity And Data Science Innovations For Sustainable Development Of Heicc
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Cybersecurity and Data Science Innovations for Sustainable Development of HEICC
"Brings together a collection of chapters that explore the intersection of Cyber security, data science, and sustainable development across key sectors: healthcare, education, industry, cities, and communities. As the world becomes increasingly interconnected, the challenges and opportunities presented by this convergence are more complex than ever before"--
Cybersecurity and Data Science Innovations for Sustainable Development of HEICC
Cybersecurity and Data Science Innovations for Sustainable Development of HEICC: Healthcare, Education, Industry, Cities, and Communities brings together a collection of chapters that explore the intersection of cybersecurity, data science, and sustainable development across key sectors: healthcare, education, industry, cities, and communities. It delves into cybersecurity advancements and examines how innovations in cybersecurity are shaping the landscape of healthcare, education, industry, and urban environments. Data science advancements take center stage, showcasing the transformative power of data analytics in improving outcomes across HEICC sectors. Whether it’s optimizing resource allocation in healthcare, protecting patient privacy, personalizing learning experiences in education, enhancing efficiency in industry, or fostering sustainable development in cities and communities, data science offers unprecedented opportunities for innovation and progress. Key points: Healthcare system security and privacy, protecting patient data, and enabling development of novel healthcare solutions Securing educational data, improving online learning security, and harnessing data analytics for tailored education approaches Manufacturing, finance, and transportation. Diving into critical infrastructure security, detecting and mitigating cyber threats, and using data‐driven insights for better industrial operations Helping cities and communities develop sustainably, smart city security challenges, data privacy in urban environments, data analytics for urban planning, and community cybersecurity awareness This book serves as a comprehensive guide for researchers, practitioners, policymakers, and stakeholders navigating the complex landscape of cybersecurity and data science in the pursuit of sustainable development across HEICC domains.
Machine Learning and Robotics in Urban Planning and Management
The integration of advanced technologies has led to drastic changes in the field of urban planning and management. When using large amounts of data from numerous sources, machine learning models can mimic past scenarios which predict future events. Urban planners use these predictions when making infrastructure or administrative decisions geared towards a highly efficient and sustainable urban environment. Machine learning algorithms can reduce the wait times at intersections, stop-and-go traffic, and overall congestion by adjusting signal timings on a real-time basis according to live density of vehicles. Conventional bottlenecks are identified and possible route changes proposed to generate improved traffic flow across regions. Further research may continue encouraging urban planning and management innovation. Machine Learning and Robotics in Urban Planning and Management explores the integration of machine learning and robotics technology in urban and regional development. It examines solutions for traffic management, infrastructure improvements, and prediction models using intelligent technology. This book covers topics such as neural networks, smart cities, and transportation systems, and is a useful resource for urban developers, business owners, scientists, civil engineers, academicians, and researchers.