GAT: Platform for automatic context-aware mobile services for m-tourism

Despite the recent advances in mobile tourism systems, most of the wayfinding applications have still to deal with some problems: a huge amount of tourist information to manage, guidance for indoor and outdoor environments, and the need of users to have programming knowledge about many mobile phone platforms. In this study, we propose the GAT platform to overcome these problems. In GAT, users are able to generate wayfinding applications for indoor and outdoor environments through a web form without the need for programming skills, assisted by a system of automatic generation and update of points of interest.     

A model for learning objects adaptation in light of mobile and context-aware computing

The growth usage of mobile technologies and devices such as smartphones and tablets, and the almost ubiquitous wireless communication set the stage for the development of novel kinds of applications. One possibility is exploiting this scenario in the field of education, so creating more intelligent, flexible and customizable systems. Mobile devices can be used to help students to learn, considering their learning styles, surroundings, devices and profiles. In this way, the main goal of this article is to propose EduAdapt, an architectural model for the adaptation of learning objects considering device characteristics, learning style and other student’s context information. To make this adaptation we used inferences and rules in a proposed ontology, named OntoAdapt. We believe that such ontology can help recommending learning objects to students or adapt these objects according to the context (context-aware computing). We evaluate this proposal in two ways. Firstly, we used scenarios and metrics to assess the ontology. Secondly, we developed a prototype of EduAdapt model and submitted to a class of 20 students with the intention of evaluating the usability and adherence to adapted objects, resulting in a 78 % of acceptance. In brief, the evaluation presented encouraging results, indicating that the proposed model would be useful in the learning process.     

A context-aware scheme for privacy-preserving location-based services

We address issues related to privacy protection in location-based services (LBSs). Most existing privacy-preserving LBS techniques either require a trusted third-party (anonymizer) or use cryptographic protocols that are computationally and communicationally expensive. Our design of privacy-preserving techniques is principled on not requiring a trusted third-party while being highly efficient in terms of time and space complexities. The problem has two interesting and challenging characteristics: First, the degree of privacy protection and LBS accuracy depends on the context, such as population and road density, around a user’s location. Second, an adversary may violate a user’s location privacy in two ways: (i) based on the user’s location information contained in the LBS query payload and (ii) by inferring a user’s geographical location based on the device’s IP address. To address these challenges, we introduce CAP, a context-aware privacy-preserving LBS system with integrated protection for both data privacy and communication anonymity. We have implemented CAP and integrated it with Google Maps, a popular LBS system. Theoretical analysis and experimental results validate CAP’s effectiveness on privacy protection, LBS accuracy, and communication QoS (Quality-of-Service).     

A new mobile payment scheme for roaming services

Due to the advance of mobile network technologies, mobile personal devices are used to perform electronic payment. This paper proposes a new on-line payment scheme for mobile network. The proposed scheme is not only performed in the home domain, but also can be performed in visited domain. Our scheme provides consumer anonymity, authentication, non-repudiation and data integrity properties. The consumer can make transaction with shop, vendor machine and WAP site based on our scheme. Our scheme only includes symmetric encryption and one-way hash function, it takes lower computation cost and is more suitable for mobile device.     

A framework for context-aware self-adaptive mobile applications SPL

Mobile Applications are rapidly emerging as a convenient medium for using a variety of services. Over time and with the high penetration of smartphones in society, self-adaptation has become an essential capability required by mobile application users. In an ideal scenario, an application is required to adjust its behavior according to the current context of its use. This raises the challenge in mobile computing towards the design and development of applications that sense and react to contextual changes to provide a value-added user experience. In its general sense, context information can relate to the environment, the user, or the device status. In this paper, we propose a novel framework for building context aware and adaptive mobile applications. Based on feature modeling and Software Product Lines (SPL) concepts, this framework guides the modeling of adaptability at design time and supports context awareness and adaptability at runtime. In the core of the approach, is a feature meta-model that incorporates, in addition to SPL concepts, application feature priorities to drive the adaptability. A tool, based on that feature model, is presented to model the mobile application features and to derive the SPL members. A mobile framework, built on top of OSGI framework to dynamically adapt the application at runtime is also described.     

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 techniques suffer because of the added complexity required for collecting and managing context information. This paper presents a component-based middleware architecture which facilitates the development and deployment of context-aware applications via reusable components. The main contribution of this approach is the combination of a development methodology with the middleware architecture, which together bring significant value to developers of context-aware applications. Further contributions include the following: The methodology utilizes separation of concerns, thus decreasing the developmental cost and improving the productivity. The design and implementation of context-aware applications are also eased via the use of reusable components, called context plug-ins. Finally, the middleware architecture facilitates the deployment and management of the context plug-ins in a resource-aware manner. The proposed methodology and middleware architecture are evaluated both quantitatively and qualitatively.     

A survey on context-aware mobile visual recognition

The phenomenal growth of the usage of mobile devices (e.g., mobile phones and tablet PCs) opens up a new service, namely mobile visual recognition, which has been widely used in many areas, such as mobile shopping and augmented reality. The rich contextual information (e.g., location, time and direction information), easily acquired by the mobile devices, provides useful clues to facilitate mobile visual recognition, including speeding up the recognition time and improving the recognition performance. This survey focuses on recent advances in Context-Aware Mobile Visual Recognition (CAMVR) and reviews related work regarding to different contextual information, recognition methods, recognition types, and various application scenarios. Finally, we discuss future research directions in this field.     

E-MIIM: an ensemble-learning-based context-aware mobile telephony model for intelligent interruption management

AI & SOCIETY - Nowadays, mobile telephony interruptions in our daily life activities are common because of the inappropriate ringing notifications of incoming phone calls in different contexts....     

Modular framework support for context-aware mobile cinema

In this paper we describe a novel approach for interactive cinema based on context-aware narration using handheld computers. The paper describes both the artistic approach and the ubiquitous computing framework developed to realize the scenario. This framework has been used in various projects, including the described video production course at the ISNM, where five interactive cinema concepts have been developed and shown during a public demonstration. In our approach, a new type of user experience has been established by placing the viewer inside the movie’s physical locations during playback. Moreover, the developed ubiquitous computing framework provides a foundation for future work in the area of ad-hoc, service-oriented Ubicomp scenarios.     

Lightweight security for mobile commerce transactions

This paper describes a lightweight security mechanism for protecting electronic transactions conducted over the mobile platform. In a typical mobile computing environment, one or more of the transacting parties are based on some wireless handheld devices. Electronic transactions conducted over the mobile platform are gaining popularity and it is widely accepted that mobile computing is a natural extension of the wired Internet computing world. However, security over the mobile platform is more critical due to the open nature of wireless networks. Furthermore, security is more difficult to implement on the mobile platform because of the resource limitation of mobile handheld devices. Therefore, security mechanisms for protecting traditional computer communications need to be revisited so as to ensure that electronic transactions involving mobile devices can be secured and implemented in an effective manner. This research is part of our effort in designing security infrastructure for electronic commerce systems, which extend from the wired to the wireless Internet. A lightweight mechanism was designed to meet the security needs in face of the resource constraints. The proposed mechanism is proven to be practical in real deployment environment.     

A JESS-enabled context elicitation system for providing context-aware Web services

Providing context-aware Web services is an adaptive process of delivering contextually matched Web services to meet service requesters’ needs. We define the term “context” from two perspectives: one from service requesters; and the other from Web services. From the former perspective, context is defined as the surrounding environment affecting requesters’ services discovery and access, such as requesters’ preferences, locations, activities, and accessible network and devices. From the latter perspective, context is defined as the surrounding environment affecting Web services delivery and execution, such as networks and protocols for service binding, devices and platforms for service execution, and so on. This paper presents a Java Expert System Shell (JESS)-enabled context elicitation system featuring an ontology-based context model that formally describes and acquires contextual information pertaining to service requesters and Web services. Based on the context elicitation system, we present a context-aware services-oriented architecture for providing context-aware Web service request, publication, and discovery. Implementation details of the context elicitation system and the evaluation results of context-aware service provision are also reported.     

A context-aware mobile application framework using audio watermarking

Multimedia Systems - In this paper, we propose a proximity-based indoor positioning system which is capable of monitoring mobile device user’s indoor locations where the commonly used GPS...     

A concurrency control scheme for mobile transactions in broadcast disk environments

Broadcast disk technique has been often used to disseminate frequently requested data efficiently to a large volume of mobile clients over wireless channels. In broadcast disk environments, a server often broadcasts different data items with differing frequencies to reflect the skewed data access patterns of mobile clients. Previously proposed concurrency control methods for mobile transactions in wireless broadcast environments are focused on the mobile transactions with uniform data access patterns. These protocols perform poorly in broadcast disk environments where the data access patterns of mobile transactions are skewed. In broadcast disk environments, the time length of a broadcast cycle usually becomes large to reflect the skewed data access patterns. This will often cause read-only transactions to access old data items rather than the latest data items. Furthermore, updating mobile transactions will be frequently aborted and restarted in the final validation stage due to the update conflict of the same data items with high access frequencies. This problem will increase the average response time of the update mobile transactions and waste the uplink communication bandwidth. In this paper, we extend the existing FBOCC concurrency control method to efficiently handle mobile transactions with skewed data access patterns in broadcast disk environments. Our method allows read-only transactions to access the more updated data, and reduces the average response time of updating transactions through early aborts and restarts. Our method also reduces the amount of uplink communication bandwidth for the final validation of the update transactions. We present an in-depth experimental analysis of our method by comparing with existing concurrency control protocols. Our performance analysis shows that it significantly decreases the average response time and the amount of uplink bandwidths over existing methods.     

Conceptual data modeling for realizing context-aware services

Recently, context-aware applications, which provide customized services using personalized contextual information, have gained much attention. However, core IT technologies for realizing context-aware services are not sufficient to support the actual development of context-aware applications. Especially, it is very hard to find studies on context-aware data modeling that can provide different responses even for the same information according to users’ situation. In practice, most context-aware services are managing contextual information in the phase of application development in a rather ad-hoc way. Unfortunately, this approach has an obvious limitation of expansibility when the amount of rapidly increasing contextual information is considered. In this paper, we first define the concept of contextual dependency among data objects. Second, we provide a context-aware data modeling methodology for modeling contextual information into the Entity-Relationship Diagram (ERD, for short) based on contextual dependency. Finally, we design a simple scenario for context-aware services, construct an ERD from the scenario based on the discovered design rules, and implement a prototype of the service.     

A user-centric evaluation of context-aware recommendations for a mobile news service

Traditional recommender systems provide personal suggestions based on the user’s preferences, without taking into account any additional contextual information, such as time or device type. The added value of contextual information for the recommendation process is highly dependent on the application domain, the type of contextual information, and variations in users’ usage behavior in different contextual situations. This paper investigates whether users utilize a mobile news service in different contextual situations and whether the context has an influence on their consumption behavior. Furthermore, the importance of context for the recommendation process is investigated by comparing the user satisfaction with recommendations based on an explicit static profile, content-based recommendations using the actual user behavior but ignoring the context, and context-aware content-based recommendations incorporating user behavior as well as context. Considering the recommendations based on the static profile as a reference condition, the results indicate a significant improvement for recommendations that are based on the actual user behavior. This improvement is due to the discrepancy between explicitly stated preferences (initial profile) and the actual consumption behavior of the user. The context-aware content-based recommendations did not significantly outperform the content-based recommendations in our user study. Context-aware content-based recommendations may induce a higher user satisfaction after a longer period of service operation, enabling the recommender to overcome the cold-start problem and distinguish user preferences in various contextual situations.     

An application framework for mobile,context-aware trails

In this paper we describe the design, implementation and evaluation of a software framework that supports the development of mobile, context-aware trails-based applications. A trail is a contextually scheduled collection of activities and represents a generic model that can be used to satisfy the activity management requirements of a wide range of context-based time management applications. Trails overcome limitations with traditional time management techniques based on static to-do lists by dynamically reordering activities based on emergent context.     

Online role mining for context-aware mobile service recommendation

Finding and recommending suitable services for mobile devices are increasingly important due to the popularity of mobile Internet. While recent research has attempted to use role-based approaches to recommend services, role discovery is still an ongoing research topic. Using role-based approaches, popular mobile services can be recommended to other members in the same role group in a context- dependent manner. This paper proposes several role mining algorithms, to suit different application requirements, that automatically group users according to their interests and habits dynamically. Most importantly, we propose an online role mining algorithm that can discover role patterns efficiently and incrementally. Finally, we present a complete, question-based framework that can efficiently perform role mining for context-aware service recommendation in a mobile environment—where a device may not be always connected to the server and/or scalability of the role mining algorithm running on the server is critical.