Introduction To Crowd Science

Includes Case Studies from a Range of Event Sites Introduction to Crowd Science examines the growing rate of crowd-related accidents and incidents around the world. Using tools, methods, and worked examples gleaned from over 20 years of experience, this text provides an understanding of crowd safety. It establishes how crowd accidents and incidents (specifically mass fatalities in crowded spaces) can occur. The author explores the underlying causes and implements techniques for crowd risk analysis and crowd safety engineering that can help minimize and even eliminate occurrences altogether. Understand Overall Crowd Dynamics and Levels of Complex Structure The book outlines a simple modeling approach to crowd risk analysis and crowds safety in places of public assembly. With consideration for major events, and large-scale urban environments, the material focuses on the practical elements of developing the crowd risk analysis and crowd safety aspects of an event plan. It outlines a range of modeling techniques, including line diagrams that represent crowd flow, calculations of the speed at which a space can fill, and the time it takes for that space to reach critical and crush density. It also determines what to consider during the event planning and approval (licensing/permitting) phases of the event process. Introduction to Crowd Science addresses key questions and presents a systematic approach to managing crowd risks in complex sites. It provides an understanding of the complexity of a site, that helps youplan for crowds in public places.

Applied Crowd Science outlines the theory and applications of the crowd safety course that Prof. Keith Still has developed and taught worldwide for over thirty years. It includes the background and applications of the crowd risk assessment tools, as well as essays and case studies from international users (UK, Ireland, Canada, Australia, Holland, Belgium and Japan). Keith’s courses are mandatory training for all UK Police Public Event Commanders. The text covers legislation and guidance for crowd safety in places of public assembly, and outlines the requirements of a crowd risk assessment for mass gatherings. It draws on Prof. Still’s expert witness experience, highlighting both the problems you need to understand for your event planning.

This well-grounded and practical guide highlights the underlying causes of crowd disasters and mass fatalities-giving readers insight into the root causes of crowd-related accidents. It presents a clearer understanding of crowd dynamics and provides the reader with fundamental modeling techniques to plan and manage and improve crowd safety in places of public assembly. The book is written for students and professionals in a number of areas such as event planning, licensing/approval, and event operation, including emergency services.

Applied Crowd Science outlines the theory and applications of the crowd safety course that Keith Still has developed and taught worldwide for over thirty years. It includes the background and applications of the crowd risk assessment tools, as well as essays and case studies from international users (UK, Ireland, Canada, Australia, Holland, Belgium and Japan) -- see Support Material on www.routledge.com/9781138626560. Keith’s courses are mandatory training for all UK Police Public Event Commanders. The text covers legislation and guidance for crowd safety in places of public assembly, and outlines the requirements of a crowd risk assessment for mass gatherings. It draws on Prof. Still’s expert witness experience, highlighting both the problems you need to understand for your event planning.

Group and Crowd Behavior for Computer Vision provides a multidisciplinary perspective on how to solve the problem of group and crowd analysis and modeling, combining insights from the social sciences with technological ideas in computer vision and pattern recognition. The book answers many unresolved issues in group and crowd behavior, with Part One providing an introduction to the problems of analyzing groups and crowds that stresses that they should not be considered as completely diverse entities, but as an aggregation of people. Part Two focuses on features and representations with the aim of recognizing the presence of groups and crowds in image and video data. It discusses low level processing methods to individuate when and where a group or crowd is placed in the scene, spanning from the use of people detectors toward more ad-hoc strategies to individuate group and crowd formations. Part Three discusses methods for analyzing the behavior of groups and the crowd once they have been detected, showing how to extract semantic information, predicting/tracking the movement of a group, the formation or disaggregation of a group/crowd and the identification of different kinds of groups/crowds depending on their behavior. The final section focuses on identifying and promoting datasets for group/crowd analysis and modeling, presenting and discussing metrics for evaluating the pros and cons of the various models and methods. This book gives computer vision researcher techniques for segmentation and grouping, tracking and reasoning for solving group and crowd modeling and analysis, as well as more general problems in computer vision and machine learning. Presents the first book to cover the topic of modeling and analysis of groups in computer vision Discusses the topics of group and crowd modeling from a cross-disciplinary perspective, using social science anthropological theories translated into computer vision algorithms Focuses on group and crowd analysis metrics Discusses real industrial systems dealing with the problem of analyzing groups and crowds

Academic Crowdsourcing in the Humanities lays the foundations for a theoretical framework to understand the value of crowdsourcing, an avenue that is increasingly becoming important to academia as the web transforms collaboration and communication and blurs institutional and professional boundaries. Crowdsourcing projects in the humanities have, for the most part, focused on the generation or enhancement of content in a variety of ways, leveraging the rich resources of knowledge, creativity, effort and interest among the public to contribute to academic discourse. This book explores methodologies, tactics and the "citizen science" involved. Addresses crowdsourcing for the humanities and cultural material Provides a systematic, academic analysis of crowdsourcing concepts and methodologies Situates crowdsourcing conceptually within the context of related concepts, such as ‘citizen science’, ‘wisdom of crowds’, and ‘public engagement’

“The Knowledge Machine is the most stunningly illuminating book of the last several decades regarding the all-important scientific enterprise.” —Rebecca Newberger Goldstein, author of Plato at the Googleplex A paradigm-shifting work, The Knowledge Machine revolutionizes our understanding of the origins and structure of science. • Why is science so powerful? • Why did it take so long—two thousand years after the invention of philosophy and mathematics—for the human race to start using science to learn the secrets of the universe? In a groundbreaking work that blends science, philosophy, and history, leading philosopher of science Michael Strevens answers these challenging questions, showing how science came about only once thinkers stumbled upon the astonishing idea that scientific breakthroughs could be accomplished by breaking the rules of logical argument. Like such classic works as Karl Popper’s The Logic of Scientific Discovery and Thomas Kuhn’s The Structure of Scientific Revolutions, The Knowledge Machine grapples with the meaning and origins of science, using a plethora of vivid historical examples to demonstrate that scientists willfully ignore religion, theoretical beauty, and even philosophy to embrace a constricted code of argument whose very narrowness channels unprecedented energy into empirical observation and experimentation. Strevens calls this scientific code the iron rule of explanation, and reveals the way in which the rule, precisely because it is unreasonably close-minded, overcomes individual prejudices to lead humanity inexorably toward the secrets of nature. “With a mixture of philosophical and historical argument, and written in an engrossing style” (Alan Ryan), The Knowledge Machine provides captivating portraits of some of the greatest luminaries in science’s history, including Isaac Newton, the chief architect of modern science and its foundational theories of motion and gravitation; William Whewell, perhaps the greatest philosopher-scientist of the early nineteenth century; and Murray Gell-Mann, discoverer of the quark. Today, Strevens argues, in the face of threats from a changing climate and global pandemics, the idiosyncratic but highly effective scientific knowledge machine must be protected from politicians, commercial interests, and even scientists themselves who seek to open it up, to make it less narrow and more rational—and thus to undermine its devotedly empirical search for truth. Rich with illuminating and often delightfully quirky illustrations, The Knowledge Machine, written in a winningly accessible style that belies the import of its revisionist and groundbreaking concepts, radically reframes much of what we thought we knew about the origins of the modern world.