Risk management is a process through which an organization methodically analyses risks inherent in all of its operational activities with the aim of minimizing damage to physical assets or occupational health hazards. Risk Management, therefore, should be a central element in the management strategy of any organization as it plays a crucial role in giving the organization a sustainable operational advantage. Safety Science: Methods to Prevent Incidents and Worker Health Damage at the Workplace is a handbook for management students and working professionals (safety professionals, human resource managers, insurance officers etc.) interested in the science of risk management and methods to implements safety standards at the workplace. The book introduces readers to the concept of occupational risk and occupational health management. It explains the concepts relevant to these topics such as safety economy valuation and asset integrity management. Assessment tools related to qualitative and quantitative risk management, incident and vulnerability analysis are also provided. Additionally, readers will find information on the human factors and methods to improve human engagement in risk management as well as information about current safety standards and systems in organizations around the world.

A smart city uses technology to provide services and solve problems to improve urban policy efficiency, reduce waste, improve quality of life, and maximize social inclusion. By 2050, 66% of the world's population is expected to be urban, which is a key driver of a global trend toward the creation of smart cities. This trend creates many opportunities for urban planning committees to learn how to design, modernize, and operate smart cities intelligently and effectively. Facets of a Smart City: Computational and Experimental Techniques for Sustainable Urban Development is a collection of topics that are relevant to the design of a smart city. This book aims to complement technical journal articles that require advanced knowledge of the subject of smart cities and applications for readers. It aims to bridge knowledge gaps in sustainable urban design by providing background information via case studies to facilitate students, recent graduates and new practitioners in urban design and planning. Key Features: - This book features 9 chapters that cover 6 major domains, which include (i) information modelling, (ii) internet of things, (iii) intelligent transportation systems, (iv) water supply, (v) waste management and (vi) sustainable environment - Computational techniques are included in the book. These include artificial neural networks, stochastic models, particle swarm optimization, machine learning, and adaptive neuro-fuzzy Inference systems. - Goals of case studies presented in this book use computational techniques to offer readers examples of supervised, unsupervised and reinforcement learning strategies in the context of smart city applications - References are provided for further reading