You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A systematic literature review on activity recognition with context-awareness techniques for mitigation of disasters 
Chapter Title:  Context interaction (sensing, acquisition, modelling) 
1. Abstract of Cited Paper (BIB001):  In this paper, the authors describe a method of accurately detecting human activity using a smartphone accelerometer paired with a dedicated chest sensor. The design, implementation, testing and validation of a custom mobility classifier are also presented. Offline analysis was carried out to compare this custom classifier to de-facto machine learning algorithms, including C4.5, CART, SVM, Multi-Layer Perceptrons, and Naïve Bayes. A series of trials were carried out in Ireland, initially involving N=6 individuals to test the feasibility of the system, before a final trial with N=24 subjects took place in the Netherlands. The protocol used and analysis of 1165min of recorded activities from these trials are described in detail in this paper. Analysis of collected data indicate that accelerometers placed in these locations, are capable of recognizing activities including sitting, standing, lying, walking, running and cycling with accuracies as high as 98%. 
2. Abstract of Cited Paper (BIB002):  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. 
3. Abstract of Cited Paper (BIB003):  Disasters and emergencies are featured by their unexpected consequences on the human being life. Crisis Management Systems (CMS) handling them require effective collaboration between their services, and need dynamic adaptation at runtime when an execution context change occurs. To manage disasters, several approaches are proposed in the literature where few of them have advocated context-awareness as a solution to reduce and avoid disasters' consequences. By using specific platforms, each approach have addressed a particular concern of the disaster, and did not cover all its life-cycle phases; this fact does decreases the large-scale use of their proposals. This paper presents a context-aware dynamic adaptation approach that deals with the impact of context changes onto running service-based applications of a CMS. This approach is specified on the Service Component Architecture (SCA) and implemented with the FraSCAti Platform. A CMS example is unrolled to demonstrate what context-aware adaptation can do for disaster management.

Literature Review:
In Figure 6 (a) context, interaction showed 13 publications from the selected primary studies that dealt with important issues in CA application. These are challenging issues as far as CA researches are concern BIB001 BIB002 . In addition, BIB003 addressed CA issue and profer solution for mitigation of crowd disaster using AR in a crowd scenario. In recent years, lots of considerable interest in context sensing for pervasive computing are conceived BIB004 , meanwhile only few are used in disaster related problem. Likewise context acquisition, inference and modelling that affect people in the society was attempted to address crowd disaster in BIB003 . This is obvious because most researches in this domain often address similar issues related to users' environment, computing and communication. Irrespective of the domain either of the issues plays major role. Moreso crowd activity has direct relationship with human, lives while using mobile devices for service within the environment. It is therefore, important, for research in this domain to take care of how these issues can be incorporated to improve on the existing studies for effective AR monitoring using CA, in order to facilitate research and development for mitigation of crowd disaster.