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.

Includes Case Studies from a Range of Event SitesIntroduction 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

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

In this fascinating book, New Yorker business columnist James Surowiecki explores a deceptively simple idea: Large groups of people are smarter than an elite few, no matter how brilliant—better at solving problems, fostering innovation, coming to wise decisions, even predicting the future. With boundless erudition and in delightfully clear prose, Surowiecki ranges across fields as diverse as popular culture, psychology, ant biology, behavioral economics, artificial intelligence, military history, and politics to show how this simple idea offers important lessons for how we live our lives, select our leaders, run our companies, and think about our world.

Presents a system for crowd management which integrates security with the other concerns for the health and safety for crowds, looking at the theories and practices of the management processes, plans, monitoring and evaluation of crowds. Structured into four sections written by experts with global experience in their field of excellence.