A systematic literature review on activity recognition with context-awareness techniques for mitigation of disasters <s> Accurate and timeliness of sensed information <s> Due to the rapid aging of the European population, an effort needs to be made to ensure that the elderly can live longer independently with minimal support of the working-age population. The Confidence project aims to do this by unobtrusively monitoring their activity to recognize falls and other health problems. This is achieved by equipping the user with radio tags, from which the locations of body parts are determined, thus enabling posture and movement reconstruction. In the paper we first give a general overview of the research on fall detection and activity recognition. We proceed to describe the machine learning approach to activity recognition to be used in the Confidence project. In this approach, the attributes characterizing the user’s behavior and a machine learning algorithm must be selected. The attributes we consider are the locations of body parts in the reference coordinate system (fixed with respect to the environment), the locations of body parts in a body coordinate system (affixed to the user’s body) and the angles between adjacent body parts. Eight machine learning algorithms are compared. The highest classification accuracy of over 95 % is achieved by Support Vector Machine used on the reference attributes and angles. <s> BIB001 </s> A systematic literature review on activity recognition with context-awareness techniques for mitigation of disasters <s> Accurate and timeliness of sensed information <s> Each year, crowd disasters happen in different areas of the world. How and why do such disasters happen? Are the fatalities caused by relentless behavior of people or a psychological state of panic that makes the crowd ‘go mad’? Or are they a tragic consequence of a breakdown of coordination? These and other questions are addressed, based on a qualitative analysis of publicly available videos and materials, which document the planning and organization of the Love Parade in Duisburg, Germany, and the crowd disaster on July 24, 2010. Our analysis reveals a number of misunderstandings that have widely spread. We also provide a new perspective on concepts such as ‘intentional pushing’, ‘mass panic’, ‘stampede’, and ‘crowd crushes’. The focus of our analysis is on the contributing causal factors and their mutual interdependencies, not on legal issues or the judgment of personal or institutional responsibilities. Video recordings show that people stumbled and piled up due to a ‘domino effect’, resulting from a phenomenon called ‘crowd turbulence’ or ‘crowd quake’. Crowd quakes are a typical reason for crowd disasters, to be distinguished from crowd disasters resulting from ‘mass panic’ or ‘crowd crushes’. In Duisburg, crowd turbulence was the consequence of amplifying feedback and cascading effects, which are typical for systemic instabilities. Accordingly, things can go terribly wrong in spite of no bad intentions from anyone. Comparing the incident in Duisburg with others, we give recommendations to help prevent future crowd disasters. In particular, we introduce a new scale to assess the criticality of conditions in the crowd. This may allow preventative measures to be taken earlier on. Furthermore, we discuss the merits and limitations of citizen science for public investigation, considering that today, almost every event is recorded and reflected in the World Wide Web. <s> BIB002 </s> A systematic literature review on activity recognition with context-awareness techniques for mitigation of disasters <s> Accurate and timeliness of sensed information <s> Abstract Our research works focuses on the design and implementation of a novel ubiquitous multi context-aware mobile phone sensing network for mitigation of crowd disasters using machine-to-machine (M2M) communications. A mobile sensor network system integrated with wireless multimedia sensor networks (WMSNs) was designed for effective prediction of a stampede during crowd disasters. This proposed sensor network consists of mobile devices that are used as crowd monitoring participant nodes that employ light sensors, accelerometers, as well as audio and video sensors to collect the relevant data. Real-time crowd dynamics modeling and real-time activity modeling have been achieved by implementing the algorithms developed for Context Acquisition and multi-context fusion. Dynamic crowd monitoring was achieved by implementing the context based region identification and grouping of participants, distributed crowd behavior estimation, and stampede prediction based on distributed consensus. The implementation of the proposed architecture in Android smartphone provides light-weight, easy to deploy, context aware wireless services for effective crowd disaster mitigation and generation of an in time alert to take measures to avoid the occurrence of a stampede. The system has been tested and illustrated within a group of people for stampede prediction by using empirically collected data. <s> BIB003
ATSI for critical situations is important to react to human safety in real time BIB003 . Figure 6 indicates that only one of the selected studies takes cognisance of this important issue of human safety in literature. Also,  identified the importance of time and information as a critical factor responsible for the causes of stampede in any crowded area in its paper titled 'Causes and prevention of crowd disaster' where he proposed the first model to described stampede accident. Based on the first model, one can deduce the fact that any CA framework with the suggested characteristics can adequately support a risk reduction for stampede occurrence to prevent crowd disaster in a crowded area. The solution in previous research on Muslim pilgrimage in Hall et al. (2009), Helbing and BIB002 and BIB001 , once led to structural alternation and re-arrangement of the pilgrimage, which prevented deadly occurrence of stampede during the Moitinho de Almeida (2016) and BIB003 study, is a welcome development that needs continuation of such research to meet up with the present dynamic and technological advancement using novel approach.