A systematic literature review on activity recognition with context-awareness techniques for mitigation of disasters <s> Mobile phone sensing <s> In this work, we propose a method for tracking individuals in crowds. Our method is based on a trajectory-based clustering approach that groups trajectories of image features that belong to the same person. The key novelty of our method is to make use of a person's individuality, that is, the gait features and the temporal consistency of local appearance to track each individual in a crowd. Gait features in the frequency domain have been shown to be an effective biometric cue in discriminating between individuals, and our method uses such features for tracking people in crowds for the first time. Unlike existing trajectory-based tracking methods, our method evaluates the dissimilarity of trajectories with respect to a group of three adjacent trajectories. In this way, we incorporate the temporal consistency of local patch appearance to differentiate trajectories of multiple people moving in close proximity. Our experiments show that the use of gait features and the temporal consistency of local appearance contributes to significant performance improvement in tracking people in crowded scenes. <s> BIB001 </s> A systematic literature review on activity recognition with context-awareness techniques for mitigation of disasters <s> Mobile phone sensing <s> This article quantifies the global carbon footprint of mobile communication systems, and discusses its ecological and economic implications. Using up-to-date data and life cycle assessment models, we predict an increase of CO2 equivalent emissions by a factor of three until 2020 compared to 2007, rising from about 86 to 235 Mto CO2e, suggesting a steeper increase than predicted in the well-known SMART2020 report. We provide a breakdown of the global carbon footprint, which reveals that production of mobile devices and global radio access network operation will remain the major contributors, accompanied by an increasing share of emissions due to data transfer in the backbone resulting from rising mobile traffic volumes. The energy bill due to network operation will gain increasing importance in cellular business models. Furthermore, technologies to reduce energy consumption are considered a key enabler for the spread of mobile communications in developing countries. Taking into account several scenarios of technological advancement and rollout, we analyze the overall energy consumption of global radio access networks and illustrate the saving potential of green communication technologies. We conclude that, conditioned on quick implementation and alongside other "classical" improvements of spectral efficiency, these technologies offer the potential to serve three orders of magnitude more traffic with the same overall energy consumption as today. <s> BIB002 </s> A systematic literature review on activity recognition with context-awareness techniques for mitigation of disasters <s> Mobile phone sensing <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
• MPS: Previous studies in crowd monitoring relied on video camera ; CCTV and visual tracking BIB001 ). More than two billion people carry mobile phones BIB002 which can easily help context-awareness application accessible to everyone. The ubiquitous devices with its increasing power of capturing, classifying and transmitting image, acoustic, location and other data, interactively or autonomously using adequate architecture, could act as sensor nodes and location-aware data collection instruments  . The state-of-the-art study already emphasised the benefit of mobile phone integration with CAC as a necessity for making the devices capable of sensing the physical world, processing the current scenario, adapting and reacting to dynamic changes in the environment. However, the need to extend their research to explore the potential of MPS with AR to monitor people in a crowd. This MPS will aids reliable and effective prediction of crowd disaster in case of emergency BIB003 .