Textbook in PDF format Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced Computational Intelligence algorithms for the analysis of data involved in applications, such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. The book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, Artificial Intelligence, and Computer Science to optimize environmental resources. Computational Intelligence in the field of sustainable computing combines Computer Science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. In addition, data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modeling, data analysis, and Artificial Intelligence (AI) are finding applications in energy networks and thus making our environment more sustainable. - Presents computational, intelligence–based data analysis for sustainable computing applications such as pattern recognition, biomedical imaging, sustainable cities, sustainable transport, sustainable agriculture, and sustainable financial management - Develops research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resources - Includes three foundational chapters dedicated to providing an overview of computational intelligence and optimization techniques and their applications for sustainable computing Introduction 1. Journey of computational intelligence in sustainable computing and optimization techniques: An introduction 2. Designing computational intelligence techniques based smart framework for sustainable computing 3. Multiple parameter optimization methods based on computational intelligence techniques in context of sustainable computing 4. IoT-based vulnerability assessment for sustainable computing: Threats, current solutions, and open challenges 5. Amalgamation of optimization techniques in big data analytics through granular computing: A roadmap to smart industry framework 6. Computational intelligence for data analysis in pattern recognition and biomedical fields 7. A block chain and artificial intelligence–enabled smart IoT framework for the development of sustainable city 8. Computational intelligence–based heuristic approach for maximizing energy efficiency in sustainable transportation and mobility 9. Computational intelligence for sustainable computing in health care informatics 10. Computational intelligence for sustainable computing in traditional medical system Ayurveda 11. Computational intelligence approach for anomaly detection and prediction in health care information 12. Artificial intelligence–based computational intelligence solutions for robotic automation 13. Developing green computing awareness based on optimization techniques for environmental sustainability