This book applies both industrial engineering and computational intelligence to demonstrate intelligent machines that solve real-world problems in various smart environments. It presents fundamental concepts and the latest advances in multi-criteria decision-making (MCDM) techniques and their application to smart environments. Though managers and engineers often use multi-criteria analysis in making complex decisions, many core problems are too difficult to model mathematically or have simply not yet been modeled.
In response, as well as discussing AI-based approaches, Soft Computing for Smart Environments covers various optimization techniques, decision analytics, and data science in applying soft computing techniques to a defined set of smart environments, including smart and sustainable cities, disaster response systems, and smart campuses.
This state-of-the-art book will be essential reading for both undergraduate and graduate students, researchers, practitioners, and decision-makers interested in advanced MCDM techniques for management and engineering in relation to smart environments.
Preface. Authors. 1. An Innovative Framework to Evaluate Smart and Sustainable Cities Using Fuzzy MCDM Method. 2. A Conceptual Design and Evaluation Framework for Assessing Smart Health Technologies. 3. An Intelligent Approach for Assessing Smart Disaster Response Systems. 4. A Facilitating Paradigm for Analyzing the Adaptation of Internet of Things Obstacles (IoTBs) to Waste Management in Smart Cities. 5. A Fusion Approach for Cloud Service Performance Assessment and Selection from Smart Data, 6. An Evaluation Approach for Prioritizing Performance of Sustainability Indicators for Smart Campuses. 7. Sustainable Supplier Selection for Smart Supply Chain. 8. Analyzing and Evaluating Smart Card Systems for Public Transportation. Index.