Context-aware Mobile Applications Research Articles

Exploiting personal web servers for mobile context-aware applications

AbstractThere is an increasing trend in moving desktop applications to web browsers, even when the web server is running on the same desktop machine. In this paper, we go further in this direction and show how to combine a web server, a web application framework (enhanced to support desktop-like Model–View–Controller interaction) and a context-aware architecture to develop web-based mobile context-aware applications. By using this approach we take advantage of the well-established web paradigm to design the graphical user interfaces (GUIs) and the inherent ability of the web to mash up applications with external components (such as Google Maps). On top of that, since the web server runs on the device itself, the application can access local resources (such as disk space or sensing devices, which are indispensable for context-aware systems) avoiding the sandbox model of the web browsers. To illustrate our approach we show how a mobile hypermedia system has been built on top of our platform.

Advances in mobile web information systems

Over the years, advances in mobile technologies are gradually bringing the full potential of desktop computers to potable mobile devices. As a matter of the fact that the number of mobile phone users is already much higher than desktop users, most Internet andWeb based services such as search engine querying, news reading, multimedia downloading, instant messaging, online shopping, and also social networking will soon be accessed mainly through a large variety of mobile devices instead of desktop computers. This theme issue looks at the new development in mobileWeb information systems such as location-based applications, mobile payment systems, mobile context-aware applications, and mobile Web data search engines. It is based on the regular submissions and the extended best papers from the 9th International Conference on Mobile Web Information Systems (MobiWIS 2012), which was held at Niagara Falls, Ontario,

Mobile Applications for Natural Parks: Guidelines Study for the Development of a Mobile Device Application

Abstract Context aware mobile applications are being adopted as a premium solution to enhance and augment the user experience of visitors of natural parks and other public and open spaces. Under this assumption, this paper reports on a selection of existent mobile park applications featuring a set of tests that helped electing their key features. The performed evaluation also allowed setting up a proposal for design guidelines aiming the development of such a kind of applications.

Investigation of a hierarchical context-aware architecture for rule-based customisation of mobile computing service

The continuous technical progress in mobile device built-in modules and embedded sensing techniques creates opportunities for context-aware mobile applications. The context-aware computing paradigm exploits the relevant context as implicit input to characterise the user and physical environment and provide a computing service customised to the contextual situation. However, heterogeneity in techniques, complexity of contextual situation, and gap between raw sensor data and usable context keep the techniques from truly integration for extensive use. Studies in this area mainly focus on feasibility demonstration of the emerging techniques, and they lack general architecture support and appropriate service customisation strategy. This investigation aims to provide general system architecture and technical approaches to deal with the heterogeneity problem and efficiently utilise the dynamic context towards proactive computing service that is customised to the contextual situation. The main efforts of this investigation are the approaches to gathering, handling, and utilising the dynamic context information in an efficient way and the decision making and optimisation methods for computing service customisation. In brief, the highlights of this thesis cover the following aspects: (1) a hierarchical context-aware computing architecture supporting interoperable distribution and further use of context; (2) an in-depth analysis and classification of context and the corresponding context acquisition methods; (3) context modelling and context data representation for efficient and interoperable use of context; (4) a rule-based service customisation strategy with a rule generation mechanism to supervise the service customisation. In addition, feasibility demonstration of the proposed system and contribution justification of this investigation are conducted through case studies and prototype implementations. One case study uses mobile built-in sensing techniques to improve the usability and efficiency of mobile applications constrained by resource limitation, and the other employs the mobile terminal and embedded sensing techniques to predict users’ expectations for home facility automatic control. Results demonstrate the feasibility of the proposed context handling architecture and service customisation methods. It shows great potential for employing the context of the computing environment for context-aware adaptation in pervasive and mobile applications but also indicates some underlying problems for further study.

Multidimensional context-aware social network architecture for mobile crowdsensing

This article proposes a multidimensional context-aware social network architecture, which aims to provide a mobile ecosystem to enable context awareness in the development and utilization of mobile crowdsensing applications. This mobile ecosystem is constructed to provide context awareness capabilities for different roles (i.e., users or developers) in the system and facilitate interactions between them. This system can ease the development of context-aware mobile applications, and enable context-aware mobile crowdsensing considering environmental, personal, and social information. We present a flow of context-aware solutions designed on this system, and highlight the orchestrations and advantages of different context-aware schemes in the system for different types of users (requesters and participants) in mobile crowdsensing. We demonstrate the feasibility of the proposed mobile ecosystem by presenting a novel context-aware mobile crowdsensing application called Smart City, and evaluate the system performance based on this application.

A pluggable middleware architecture for developing context-aware mobile applications

The proliferation of powerful smartphone devices provides a great opportunity for context-aware mobile applications becoming mainstream. However, we argue that conventional software development tec...

Activity Theory Approach to Developing Context-Aware Mobile Learning Systems for Understanding Scientific Phenomenon and Theories

Mobile computing offers potential opportunities for students’ learning especially when it combines a sensing device such as RFID (Radio Frequency Identification). Researchers have indicated that a key feature of in-field learning supported by mobile devices and technology is context awareness, with which context and functionality provided by the learning system are adapted to the user’s situation. However, the design of context-aware mobile learning systems provides the authors with major challenges in terms of both defining use context as well as developing appropriate concepts relevant to the design of contextual information on the systems. Educators have highlighted the role of activity in science development and learning, implying that activity theory can be used to design a mobile learning environment. This paper presents the use of activity theory as a framework for describing the design of a context aware mobile learning application. A case study for the design of a mobile learning application for science learning is described using activity theory.

Evaluating Mobile Applications in Virtual Environments

Context plays a central role in mobile applications but is very difficult to control, and therefore, the evaluation of context-aware applications can be challenging. Traditionally, researchers had to choose either field-based or lab-based studies but recently, virtual environments have been proposed as a middle-ground between those two methods. In this paper, the authors review previous work on using virtual environments to evaluate mobile applications. the authors identify and classify different approaches to simulate specific aspects of the real world, and analyse their relative properties with respect to evaluating different facets of context-aware mobile applications. Based on this analysis, the authors derive criteria and selection strategies that can help researchers in picking specific evaluation approaches. The authors also point out a number of research challenges in this area as well as a number of promising areas for future research.

안드로이드에서 상황 인지 스마트폰 애플리케이션을 위한 컴포넌트 기반 애플리케이션 프레임워크

This paper presents a framework for context-aware smart phone applications based on Android. The mobile context-aware system is composed of a low level context collection module, a high level context generation module and a service provision module. Existing android system cannot provide an appropriate application framework to integrate these independent modules. In this paper, we provide an application framework which make each module a component, and provide appropriate services to each component. This framework hides the Android platform, so that the complexity for organical combination can be minimized and the application developers can make the mobile context-aware applications easily.

Programming mobile context-aware applications with TOTAM

In tuple space approaches to context-aware mobile systems, the notion of context is defined by the presence or absence of certain tuples in the tuple space. Existing approaches define such presence either by collocation of devices holding the tuples or by replication of tuples across all devices. We show that both approaches can lead to an erroneous perception of context. Collocation ties the perception of context to network connectivity which does not always yield the expected result. Tuple replication can cause that a certain context is perceived even if the device has left the context a long time ago. We propose a tuple space approach in which tuples themselves carry a predicate that determines whether they are in the right context or not. We present a practical API for our approach and show its use by means of the implementation of various mobile applications. Benchmarks show that our approach can lead to a significant increase in performance compared to other approaches.

Multivariate context collection in mobile sensor networks

We focus on the treatment of quality-stamped contextual information in mobile sensor networks. Sensing nodes capture and forward context for consumption by mobile context aware applications. Due to the dynamic network topology the quality indicators seen by consumers vary over time. Context quality is a decreasing function of time and context can be consumed with a certain delay from its capturing time. We propose the sequential assessment of the network-circulated context information according to the Generalized Secretary Problem, a known paradigm in the Optimal Stopping Theory. The consumer node delays the processing (consumption) of incoming context until better quality is attained. We extend this basic model to include the cardinality of contextual components (i.e., different types of measurements coming from, possibly, different sources). Hence, the consumer node is interested not only in the higher possible quality of context but also in the widest possible range of context parameters (context “quantity”). We compare our findings to simple consumption strategies and pinpoint the advantages of the proposed model.

The Future of Mobile E-health Application Development: Exploring HTML5 for Context-aware Diabetes Monitoring

According to predictions of information technology research and advisory firms, such as Gartner, hybrid HTML5 appli- cations will be the future for mobile application development. In this paper, we explore the feasibility of using HTML5 and related web application standards for the development of mobile e-health applications, using a diabetes monitoring application as a practical use case. Context-awareness and visualizing multivariate data with parallel coordinates for decision support are key features of this mobile e-health application. We compare the strengths and weaknesses of the hybrid HTML5 approach with native mobile applications, and report on practical experiences with the development and usage of the application. Our experiments show that developers of fairly advanced context-aware mobile applications can definitely benefit from the HTML5 application portability across different mobile platforms. However, compared to native applications, they should be aware of missing features such as secure storage, non-negligible performance penalties of JavaScript business logic on a mobile platform, and an inferior user experience.

Technical Feasibility of a Mobile Context-Aware (Social) Learning Schedule Framework

The purpose of this paper is to show the technical feasibility of implementing their mobile context-aware learning schedule (mCALS) framework as a software application on a mobile device using current technologies, prior to its actual implementation. This process draws a set of compatible mobile and context-aware technologies at present and can be used as a reference point for implementing generic mobile context-aware applications. The authors’ mCALS framework retrieves the learner’s location and available time contexts via the built-in learning schedule (i.e., electronic organizer) on a mobile device. These contexts together with the learner’s learning styles and knowledge level (on a selected topic) are used as the basis for the software application to suggest learning materials that are appropriate for the learner, at the time of usage. This retrieval approach eliminates the use of context-aware technologies and the need to directly request the user to enter context information at the time of usage. The authors develop a fully functional prototype of this framework for learners to plan their individual as well as social learning activities amongst one another to make their individual learning processes collaborative and as a way to enhance individual and social learning experiences.

A context management framework for context‐aware applications in mobile spaces

PurposeThe rapid proliferation of mobile context aware applications has resulted in an increased research interest towards developing specialized context data management strategies for mobile entities. The purpose of this paper is to aim to develop a new way to model mobile entities and manage their contexts accordingly.Design/methodology/approachThis paper proposes the concept of “Mobile Space” to model mobile entities and presents strategies to manage the various contexts associated therein. To handle availability related issues, two system services are designed: the “Availability Updating Service” which is an identifier based mechanism and is designed to keep track of mobile objects and handle availability related issues, and the “Application Callback Service” which is a publish/subscribe based mechanism to handle application disruptions and interruptions arising due to mobility.FindingsThe paper presents a detailed study of the proposed framework and a description of the underlying services and the components therein to validate the framework. Experimental results carried out in WiFi and 3G environments indicate that the proposed techniques can support mobile applications and minimize application disruptions with minimal overhead.Originality/valueThe proposed context management framework is generic in nature and is not designed for a specific class of applications. Any mobile context aware application can leverage on the framework and utilize the provided functionalities to manage application disruptions. Also, the decoupling of mobile application layer and the underlying context data management layer renders context data management layer transparent to the application design.

A plane tracker for AEC-automation applications

Purpose We propose a new registration algorithm and computing framework, the keg tracker, for estimating a camera's position and orientation for a general class of mobile context-aware applications in architecture, engineering, and construction (AEC). Method By studying two classic types of natural marker-based registration algorithms, homographyfrom-detection and homography-from-tracking, and overcoming their specific limitations of jitter and drift, our method applies two global constraints (geometric and appearance) to prevent tracking errors from propagating between consecutive frames. Results & Discussion The proposed method is able to achieve an increase in both stability and accuracy, while being fast enough for real-time applications. Experiments on both synthesized and real world test cases demonstrate that our method is superior to existing state-of-the-art registration algorithms. The paper also explores several AEC-applications of our method in context-aware computing and desktop augmented reality.

Optimal, quality-aware scheduling of data consumption in mobile ad hoc networks

In this paper we study the delivery of quality contextual information in mobile ad-hoc networks. We consider that information has a certain quality level that fades over time. Mobile context-aware applications receive and process disseminated information given that the corresponding quality is above the lowest level. The necessity for optimally scheduling information delivery arises from the dynamic nature of the network, e.g., probabilistic spreading, caching, deferred delivery, and mobility of nodes. We propose two policies for optimal scheduling information delivery consumption based on the Optimal Stopping Theory. The mobile nodes delay the reporting of information to mobile context-aware applications in search for better quality. The proposed policies efficiently deal with the delivery of quality information in mobile ad-hoc networks.

Usability study of ME2.0

Mobile context-aware applications execute in the background of hosts mobile devices. The applications source process and aggregate hosts' contextual and personal information. This information is di...

Efficient Location Prediction in Mobile Cellular Networks

Mobile context-aware applications are capable of predicting the context of the user in order to operate pro-actively and provide advanced services. We propose an efficient spatial context classifier and a short-term predictor for the future location of a mobile user in cellular networks. We introduce different variants of the considered location predictor dealing with location (cell) identifiers and directions. Symbolic location classification is treated as a supervised learning problem. We evaluate the prediction efficiency and accuracy of the proposed predictors through synthetic and real-world traces and compare our solution with existing algorithms for location prediction. Our findings are very promising for the location prediction problem and the adoption of proactive context-aware applications and services.

An Adaptive Machine Learning Algorithm for Location Prediction

Context-awareness is viewed as one of the most important aspects in the emerging pervasive computing paradigm. Mobile context-aware applications are required to sense and react to changing environment conditions. Such applications, usually, need to recognize, classify and predict context in order to act efficiently, beforehand, for the benefit of the user. In this paper, we propose a novel adaptive mobility prediction algorithm, which deals with location context representation and trajectory prediction of moving users. Machine Learning (ML) is used for trajectory classification. Our algorithm adopts spatial and temporal on-line clustering, and relies on Adaptive Resonance Theory (ART) for trajectory prediction. The proposed algorithm applies a Hausdorff-like distance over the extracted trajectories handling location prediction. Since our approach is time-sensitive, the Hausdorff distance is considered more advantageous than a simple Euclidean norm. Two learning methods (non-reinforcement and reinforcement learning) are presented and evaluated. Finally, we compare our algorithm with Offline kMeans and Online kMeans algorithms. Our findings are very promising for the use of the proposed algorithm in mobile context aware applications.

AN ARCHITECTURE TO SUPPORT PERSONALIZED INTERACTION ACROSS MULTIPLE DIGITALLY AUGMENTED SPACES

Any physical space can be augmented with digital information, associated to various locations or artefacts contained in it. In this paper, an abstract architecture is presented, supporting interaction with mobile context aware applications in public digitally augmented spaces. We focus on how this architecture supports personalization of interaction and adaptation. The main goal of the architecture is to allow users to benefit of a uniform and personalized experience across different contexts and spaces. Among the concerns are: to support high interoperability and flexibility and to address issues of privacy and user control. The framework has been tested in typical augmented spaces: a library and a museum. The paper concludes with a set of examples of use of the defined framework that cover typical situations for intra-space and across spaces usage.