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.

A Semantic Preprocessing Framework for Breaking News Detection to Support Future Drone Journalism Services

Nowadays, news coverage implies the existence of video footage and sound, from which arises the need for fast reflexes by media organizations. Social media and mobile journalists assist in fulfilling this requirement, but quick on-site presence is not always feasible. In the past few years, Unmanned Aerial Vehicles (UAVs), and specifically drones, have evolved to accessible recreational and business tools. Drones could help journalists and news organizations capture and share breaking news stories. Media corporations and individual professionals are waiting for the appropriate flight regulation and data handling framework to enable their usage to become widespread. Drone journalism services upgrade the usage of drones in day-to-day news reporting operations, offering multiple benefits. This paper proposes a system for operating an individual drone or a set of drones, aiming to mediate real-time breaking news coverage. Apart from the definition of the system requirements and the architecture design of the whole system, the current work focuses on data retrieval and the semantics preprocessing framework that will be the basis of the final implementation. The ultimate goal of this project is to implement a whole system that will utilize data retrieved from news media organizations, social media, and mobile journalists to provide alerts, geolocation inference, and flight planning.

Home Automation and Security System Using Internet of Things

The internet of things (IoT) is viewed as something that connects everyday objects like smart TV and smart phones. Automation is the future of human civilization. It's like operating various devices and machinery with minimum or no human intervention. In this chapter, home appliances and other electronic devices are proposed to be controlled over internet with the help of website or smartphone. Speech recognition technology has been implemented in this chapter which will help complete or partially visually impaired people or persons with physical disability. Smart CCTV concept has been developed in this chapter which will allow to operate the web camera whenever it detects motion and sleep at other times which will save energy as well as storage unlike current CCTV scenario. Also, smart CCTV captures images and video footage and provides the real-time status of the place via a registered email address, website, and mobile app. If you are outside, you can check the status of your home and be in line with it, and you will activate the home appliances from the web site and through speech.

Svět prken, která znamenají svět. O projektu Divadelního oddělení Národního muzea – Dokumentace současných divadelních budov

This paper presents an extensive research project carried out by the Theatre Department at the National Museum. This document, the Catalogue of Contemporary Theatre Buildings, maps out in detail the sites where theatre is performed in the Czech Republic today. It focuses not only on professional venues, but also registers other, often unconventional, places where theatre thrives, such as churches, public spaces, cultural centres, private apartments, gymnasia, cinemas, shopping centres, etc. In the first section, the outline of the project is presented, starting from the initial idea through to the people involved and technical support for its implementation, to a description of how the obtained material was processed into a comprehensive and clear archival collection. In the second part, the study focuses on some valuable findings on contemporary theatre in the Czech Republic, obtained by the author during the cataloguing process. Using photographs, textual materials, video footage and interviews with employees of the documented institutions, the project aims to find answers to general questions of a social nature: How does neatness or untidiness indicate a citizen‘s relationship to the place in which they live? How do people understand the terms ‘community centre’ and ‘public service’?

Landslide investigations during pandemic restrictions: initial assessment of recent peat landslides in Ireland

Landslides involving peat are relatively common in Ireland, upland areas of Great Britain and subantarctic islands. Bogflows and bog slides are less common types of peat failure and almost unknown outside Ireland. Unusually, three of these occurred in 2020 including one bogflow at a windfarm that gained much adverse media attention, and a small but damaging peat slide was also reported. The aim of this paper is to determine the extent to which the new bog slide and bogflows are consistent with previous examples in terms of their contexts, characteristics and possible causes, particularly relating to commercial forestry operations. Aerial video footage of all three landslides obtained by local people using drones, and ground-based footage of one of them in progress, allowed a detailed examination of their characteristics and contexts to be made despite the global travel and activity restrictions caused by the coronavirus pandemic. The windfarm bogflow appears to have resulted from removal of toe support by an earlier peat flow that was itself probably caused by construction of an access road; the other two landslides were most likely triggered by rainfall. All three are consistent with previous examples of their respective types in their general characteristics and appear to be associated with well-known causal factors including hydrological, topographic and/or forestry influences. Forestry operations probably contributed to the occurrence of two of the landslides and restricted the expansion of two of them.

Police Use of Force Escalation and De-escalation: The Use of Systematic Social Observation With Video Footage

As police agencies continue to incorporate body-worn cameras, it becomes increasingly important for researchers and practitioners to explore how to best use these data to better understand patterns of suspect and police behavior. Thus, drawing on a joint project between the Federal Law Enforcement Training Centers and Arizona State University, we expand on prior research demonstrating how social systematic observation (SSO) can be used with video footage to methodically detail the evolving nature of police-suspect encounters. We then illustrate how the data could be evaluated within the framework of escalation and de-escalation using an expanded version of the Resistance Force Comparative Scale (RFCS) first developed and employed in 2001. Finally, we assess the merits and challenges of using video footage to account for suspect and police behaviors in relation to escalation and de-escalation.

THE FLOODING AFTER DAMAGE OF A WARSHIP WITH COMPLEX INTERNAL COMPARTMENTS – EXPERIMENTS ON A FULLY CONSTRAINED MODEL IN CALM WATER AND REGULAR BEAM SEAS

In order to provide data to assist in developing and validating a numerical code to simulate the flooding immediately following damage scale model experiments were conducted on a fully constrained model to investigate the progressive flooding through a complex series of internal compartments within a generic destroyer type hull form. A 3.268 metre long model of a generic destroyer hull form with a simplified, typical internal arrangement was constructed to cover the configuration of greatest interest. A very rapid damage opening scenario was simulated by rupturing a taut membrane covering an opening. The model was instrumented to measure the levels of water and the air pressures in various compartments. In addition, video footage was obtained of the flooding process from both internally and externally of the model. Previous work presented by Macfarlane et al. (2010) showed the results for the unconstrained model. This paper reports on the outcomes from the experimental program where the model was fully constrained in all six degrees of freedom. Firstly, tests were conducted in calm water with damage opening extents ranging from 50% to 100%. When the damage opening was only 50% the rate of rise of water in each of the compartments was only marginally slower than for the 100% damage extent case. Secondly, the test results in calm water were compared against results from tests in regular beam seas. A ‘set-up’ of water inside each of the compartments on the 2nd Deck was found during the wave tests. The result of this is that the mean equilibrium water level in each compartment in the regular beam sea cases is noticeably higher than the equivalent calm water case, particularly for the two compartments on the port side, away from the damage. Finally, analysis of the data from further calm water and beam sea tests suggests that a similar result also occurs when the model is fixed at various non-zero heel angles.

The Effect of Visitors on Zoo Reptile Behaviour during the COVID-19 Pandemic

Visitors to zoos can have positive, neutral, or negative relationships with zoo animals. This makes human–animal interactions (HAIs) an essential component of welfare and an important consideration in species selection for zoo exhibits and in enclosure designs. We measured the effect of visitors on reptiles by comparing open and closed periods during the lockdowns in response to the COVID-19 pandemic in the UK in a low-resolution dataset for thirteen species of reptiles and a high-resolution dataset focussing on just one of these. Scan sampling on thirteen reptile species (two chelonians and eleven squamates) showed species-specific differences in response to the presence/absence of visitors, with most taxa being only weakly affected. High-resolution scan sampling via video footage of an off-show and on-show enclosure was carried out for tokay geckos (Gekko gecko) over the open and closed periods. In this part of the study, tokay geckos were significantly more visible during zoo closure than when visitors were present on-exhibit, but there was no change in off-show animals, indicating the effect of visitors as opposed to other factors, such as seasonality, which applied equally to both on- and off-show animals. The high-resolution study showed that a significant effect was present for tokay geckos, even though the low-resolution suggested that they were more weakly affected than other taxa. Our results indicate that, for cryptic species such as this, more intensive sampling may be required to properly understand visitor effects. Our data do not allow the interpretation of effects on welfare but show that such assessments require a species-specific approach.

Discovering Video Integrity through Blockchains

Video surveillance has been increasing in popularity in the recent years. This is due to the advancements in the sensor technology that has led to increased affordability of cameras and other video capturing approaches. This has led to a large number of organizations and individuals utilizing the video surveillance to deter criminals from committing the crime. This evidence can be utilized in court to facilitate the justice department effectively for investigation. As there have also been improvements in the approaches to tamper and edit the video footage effectively, there is a need to achieve video integrity to effectively prove the authenticity of the footage. For this purpose, this research article has been effective in achieving video integrity evaluation through the utilization of the distributed Blockchain framework. The presented technique utilizes Advanced Encryption System along with Blockchain framework to achieve effective and useful video integrity evaluation. The experimental outcome has been effective in demonstrating the superiority of the proposed approach.