Crowd density estimation using deep learning for Hajj pilgrimage video analytics

Background: This paper focuses on advances in crowd control study with an emphasis on high-density crowds, particularly Hajj crowds. Video analysis and visual surveillance have been of increasing importance in order to enhance the safety and security of pilgrimages in Makkah, Saudi Arabia. Hajj is considered to be a particularly distinctive event, with hundreds of thousands of people gathering in a small space, which does not allow a precise analysis of video footage using advanced video and computer vision algorithms. This research proposes an algorithm based on a Convolutional Neural Networks model specifically for Hajj applications. Additionally, the work introduces a system for counting and then estimating the crowd density. Methods: The model adopts an architecture which detects each person in the crowd, spots head location with a bounding box and does the counting in our own novel dataset (HAJJ-Crowd). Results: Our algorithm outperforms the state-of-the-art method, and attains a remarkable Mean Absolute Error result of 200 (average of 82.0 improvement) and Mean Square Error of 240 (average of 135.54 improvement). Conclusions: In our new HAJJ-Crowd dataset for evaluation and testing, we have a density map and prediction results of some standard methods.

Big Data Analytics Strategy Framework: A Case of Crowd Management During the Hajj Pilgrimage, Mecca, Saudi Arabia

The objective of the present study was an investigation of applications of big data analytics in Hajj and Umrah for pilgrims, who come to Saudi Arabia every year for tourism and observation of religious rites as per the sacred beliefs of Islam. It has now become a necessity to see more applications of big data analytics in these pilgrimages because of the growing number of people every year. Therefore, crowd control, crowd management and conflict management are essential for reduction of stress, troubles, fatalities, accidents, theft and possible deaths during Hajj and Umrah events. Developing a predictive data analytic model for Hajj and Umrah will improve the efficiency, gross domestic product (GDP), surveillance, revenue generation, opportunities and satisfaction for the pilgrimages. In this paper, review of big data tools was presented along with their use in the decision support system and how it can be used for surveillance and crowd management. A robust big data framework applicable for Hajj and Umrah events was also presented in this paper. This was meant to aid seamless adoption and implementation of big data applications across sectors and government parastatals involved in Hajj and Umrah. The presented framework was also included all the relevant use cases related to these pilgrimages.

Crowd control: Reducing individual estimation bias by sharing biased social information

Cognitive biases are widespread in humans and animals alike, and can sometimes be reinforced by social interactions. One prime bias in judgment and decision-making is the human tendency to underestimate large quantities. Previous research on social influence in estimation tasks has generally focused on the impact of single estimates on individual and collective accuracy, showing that randomly sharing estimates does not reduce the underestimation bias. Here, we test a method of social information sharing that exploits the known relationship between the true value and the level of underestimation, and study if it can counteract the underestimation bias. We performed estimation experiments in which participants had to estimate a series of quantities twice, before and after receiving estimates from one or several group members. Our purpose was threefold: to study (i) whether restructuring the sharing of social information can reduce the underestimation bias, (ii) how the number of estimates received affects the sensitivity to social influence and estimation accuracy, and (iii) the mechanisms underlying the integration of multiple estimates. Our restructuring of social interactions successfully countered the underestimation bias. Moreover, we find that sharing more than one estimate also reduces the underestimation bias. Underlying our results are a human tendency to herd, to trust larger estimates than one’s own more than smaller estimates, and to follow disparate social information less. Using a computational modeling approach, we demonstrate that these effects are indeed key to explain the experimental results. Overall, our results show that existing knowledge on biases can be used to dampen their negative effects and boost judgment accuracy, paving the way for combating other cognitive biases threatening collective systems.

Crowd density estimation using deep learning for Hajj pilgrimage video analytics

Background: This paper focuses on advances in crowd control study with an emphasis on high-density crowds, particularly Hajj crowds. Video analysis and visual surveillance have been of increasing importance in order to enhance the safety and security of pilgrimages in Makkah, Saudi Arabia. Hajj is considered to be a particularly distinctive event, with hundreds of thousands of people gathering in a small space, which does not allow a precise analysis of video footage using advanced video and computer vision algorithms. This paper aims to propose an algorithm based on a Convolutional Neural Networks model specifically for Hajj applications. Additionally, the work introduces a system for counting and then estimating the crowd density. Methods: The model adopts an architecture which detects each person in the crowd, spots head location with a bounding box and does the counting in our own novel dataset (HAJJ-Crowd). Results: Our algorithm outperforms the state-of-the-art method, and attains a remarkable Mean Absolute Error result of 200 (average of 82.0 improvement) and Mean Square Error of 240 (average of 135.54 improvement). Conclusions: In our new HAJJ-Crowd dataset for evaluation and testing, we have a density map and prediction results of some standard methods.

An Organisational and Task Analysis to Inform Police Physical Education and Defensive Tactics Training

<p><b>"For to win one hundred victories in one hundred battles is not the acme of skill. To subdue the enemy without fighting is the acme of skill”. Sun Tzu.</b></p> <p>In the preparation for front-line policing, the teaching of Physical Education and Defensive Tactics (PE and DT) should integrate a number of tactics and techniques, and focus on operationally relevant scenario training. This study used a mixed-method approach (comprising of interviews, observations, focus groups, and a questionnaire), and involved 350 police officers and staff in New Zealand. It sought to identify the critical PE and DT related tasks front-line officers complete, to allow for an evidence based approach to informing the design and development of the training curriculum. The study identified two major topics that it was commonly considered should be part of the PE and DT curriculum: (1) empty-hand techniques and appointments (equipment); and (2) ceremonial (military drill), physical conditioning, and crowd control training. A number of underpinning principles also emerged as being important: the need for self-awareness, confidence, contributing to team effectiveness, and expecting the unexpected. Officers identified situations involving non-compliant and violent people to be the most critical to be trained for, with a focus on easily transferred and effective restraint and self-defence techniques and tactics. Tasks that were judged easy to learn (such as pepper spraying dogs) were deemed to be the least critical tasks to include in the curriculum. Analysis of data related to difficulty, importance, and frequency responses by various officer demographics, showed that those policing in the most rural locations reported using force and communications on non-compliant people less often than other officers.</p>

An Organisational and Task Analysis to Inform Police Physical Education and Defensive Tactics Training

<p><b>"For to win one hundred victories in one hundred battles is not the acme of skill. To subdue the enemy without fighting is the acme of skill”. Sun Tzu.</b></p> <p>In the preparation for front-line policing, the teaching of Physical Education and Defensive Tactics (PE and DT) should integrate a number of tactics and techniques, and focus on operationally relevant scenario training. This study used a mixed-method approach (comprising of interviews, observations, focus groups, and a questionnaire), and involved 350 police officers and staff in New Zealand. It sought to identify the critical PE and DT related tasks front-line officers complete, to allow for an evidence based approach to informing the design and development of the training curriculum. The study identified two major topics that it was commonly considered should be part of the PE and DT curriculum: (1) empty-hand techniques and appointments (equipment); and (2) ceremonial (military drill), physical conditioning, and crowd control training. A number of underpinning principles also emerged as being important: the need for self-awareness, confidence, contributing to team effectiveness, and expecting the unexpected. Officers identified situations involving non-compliant and violent people to be the most critical to be trained for, with a focus on easily transferred and effective restraint and self-defence techniques and tactics. Tasks that were judged easy to learn (such as pepper spraying dogs) were deemed to be the least critical tasks to include in the curriculum. Analysis of data related to difficulty, importance, and frequency responses by various officer demographics, showed that those policing in the most rural locations reported using force and communications on non-compliant people less often than other officers.</p>

Composite Metamaterials: Classification, Design, Laws and Future Applications

The development of science and applications have reached a stage where the naturally existed materials are not meeting the required properties. Metamaterials (MMs) are artificial materials that obtain their properties from their accurately engineered meta-atoms rather than the characteristics of their constituents. The size of the meta-atom is small compared to light’s wavelength. A metamaterial (MM) is a term means beyond material which has been engineered in order to possess properties that does not exist in naturally-found materials. Currently, they are made of multiple elements such as plastics and metals. They are being organized in iterating patterns at a scale that is smaller than wavelengths of the phenomena it influences. The properties of the MMs are not derived from the forming materials but their delicate size, geometry, shape, orientation, and arrangement. These properties maintain MMs to manipulate the electromagnetic waves via promoting, hindering, absorbing waves to attain an interest that goes beyond the natural materials’ potency. The apt design of MMs maintains them of influencing the electromagnetic radiation or sound in a distinctive technique never found in natural materials. The potential applications of MMs are wide, starting from medical, aerospace, sensors, solar-power management, crowd control, antennas, army equipment and reaching earthquakes shielding and seismic materials.

Virodrone – A Flying Virus Fighter

In This paper presents an application for drone named VIRODRONE- A drone designed for Fighting Viral Diseases. Time and safety are two main factors in such viral diseases to address this both this drone is designed. It has the facility of crowd screening, crowd control and sanitization. If no of people at any place at that instant is more than 5 it will give warning to maintain social distancing and if no of people is 0 it will go and sanitize that place. A drone useful for fighting in such pandemic situation.

Kinetic Projectile Injuries Treated During Civil Protests in Los Angeles: A Case Series

Introduction: During protests following the death of George Floyd, kinetic impact projectiles (KIP) were used by law enforcement as a method of crowd control . We describe the injuries seen at a single Level 1 trauma center in Los Angeles over a two-day period of protests to add to the collective understanding of the public health ramifications of crowd-control weapons used in the setting of protests. Case Series: We reviewed the emergency department visits of 14 patients who presented to our facility due to injuries sustained from KIPs over a 48-hour period during civil protests after the death of George Floyd. Conclusion: Less lethal weapons can cause significant injuries and may not be appropriate for the purposes of crowd control, especially when used outside of established guidelines.