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Pervasive computing environments such as a pervasive campus domain, shopping, etc. will become commonplaces in the near future. The key to enhance these system environments with services relies on the ability to effectively model and represent contextual information, as well as spontaneity in downloading and executing the service interface on a mobile device. The system needs to provide an infrastructure that handles the interaction between a client device that requests a service and a server which responds to the client's request via Web service calls. The system should relieve end‐users from low‐level tasks of matching services with locations or other context information. The mobile users do not need to know or have any knowledge of where the service resides, how to call a service, what the service API detail is and how to execute a service once downloaded. All these low‐level tasks can be handled implicitly by a system. The aim of this paper is to investigate the notion of context‐aware regulated services, and how they should be designed, and implemented.

The paper presents a detailed design, and prototype implementation of the system, called mobile hanging services (MHS), that provides the ability to execute mobile code (service application) on demand and control entities' behaviours in accessing services in pervasive computing environments. Extensive evaluation of this prototype is also provided.

The framework presented in this paper enables a novel contextual services infrastructure that allows services to be described at a high level of abstraction and to be regulated by contextual policies. This contextual policy governs the visibility and execution of contextual services in the environment. In addition, a range of contextual services is developed to illustrate different types of services used in the framework.

The main contribution of this paper is a high‐level model of a system for context‐aware regulated services, which consists of environments (domains and spaces), contextual software components, entities and computing devices.

This paper aims to propose a conceptual model that will guide development of mobile applications to support value-added business-to-business (B2B) sales activities.

The paper reviews the concepts of context-aware applications and context-marketing, then examines B2B selling and the creation of value, utilizing Terho’s model of value-based selling, and presenting the potential role of context-aware B2B selling in creating value. Terho’s model is then combined with a taxonomy of context modeling to produce step-by-step a conceptual model for developing context-aware B2B sales applications (CABS).

By mapping the context-aware application development taxonomy against each stage of Terho’s “value-based selling” model, the CABS model is proposed. This model provides a platform for the B2B salesforce, their customers and information technology (IT) staff to work together in developing requirements and prototypes for mobile B2B context-aware applications.

The CABS model would require empirical testing to assess its viability and suitability. This would initially be done via focus groups in targeted sales organizations.

The CABS model could utilized by sales staff and their customers to develop requirements for mobile context-aware applications to support B2B activity. In addition, the CABS model could be utilized in joint application design processes to enable sales and IT staff to work together in developing prototype mobile applications.

While context-aware applications are beginning to transform business-to-sale (B2C) sales activities, it is clear that B2B sales could also benefit from these types of applications, but little progress has been made in understanding or developing their potential. The CABS model enables B2B sales staff and their customers to recognize these benefits and facilitate working with IT staff in defining requirements and developing prototypes.

The purpose of this paper is to propose an intelligent service recommendation model. The paper formulates the service adaptation process by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rule based reasoning.

The authors formulate the service adaptation process by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rule based reasoning. Bayesian Network is used to classify the incoming call (high priority call, low priority call and unknown calls), fuzzy linguistic variables and membership degrees to define the context situations, the rules for adopting the policies of implementing a service, fitness degree computation and service recommendation. In addition to this the paper proposes maximum to minimum priority based context attributes matching algorithm for rule selection based on fitness degree of rules. The context aware mobile is tested for library and class room scenario to exemplify the proposed service recommendation engine and demonstrate its effectiveness.

First, it was found that there was reduction in application searching time in different contexts. For example, if user enters into the library, the proposed mobile will be adapted to the library situation automatically by configuring its desktop and internal settings to facilitate the library services like book search, web link, silent mode and friends search. Second, the design of the recommendation engine, utilizing contextual parameters like Location (class room, college campus, house, etc.) Personal (age, name), Temporal (time, date), Physical (fall, normal), and schedule agendas, was found to be of importance.

Exploitation of hybrid fuzzy system, Bayesian Networks and the utility theory (usage history and context history) for modeling and implementation.

This paper aims to address privacy concerns that arise from the use of mobile recommender systems when processing contextual information relating to the user. Mobile recommender systems aim to solve the information overload problem by recommending products or services to users of Web services on mobile devices, such as smartphones or tablets, at any given point in time and in any possible location. They use recommendation methods, such as collaborative filtering or content-based filtering and use a considerable amount of contextual information to provide relevant recommendations. However, because of privacy concerns, users are not willing to provide the required personal information that would allow their views to be recorded and make these systems usable.

This work is focused on user privacy by providing a method for context privacy-preservation and privacy protection at user interface level. Thus, a set of algorithms that are part of the method has been designed with privacy protection in mind, which is done by using realistic dummy parameter creation. To demonstrate the applicability of the method, a relevant context-aware data set has been used to run performance and usability tests.

The proposed method has been experimentally evaluated using performance and usability evaluation tests and is shown that with a small decrease in terms of performance, user privacy can be protected.

This is a novel research paper that proposed a method for protecting the privacy of mobile recommender systems users when context parameters are used.

The 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.

This 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.

The 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.

The 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.

Context awareness is one of the key aspects of pervasive computing systems. In such systems, a plethora of dynamic context information needs to be constantly retrieved, soundly interpreted, rapidly processed, maintained in various repositories, and securely disseminated. Thus, a flexible, scalable and interoperable context representation scheme needs to be established and solid context management mechanisms need to be adopted, which will perform well in large‐scale distributed pervasive systems. This paper elaborates on the COMPACT context middleware that has been designed to cope with the issues above and saturate pervasive computing environments with context awareness functionality.

The design of context‐aware mobile applications can be improved through a clear and in‐depth understanding of context and how it can be used to meet users' requirements. Using tourism as a case application, this paper aims to address the lack of understanding of context and tourists' goals.

This is achieved through a literature review of existing research and focus groups to gather information needs for tasks commonly executed by tourists.

This paper proposes the TILES (temporal, identity, location, environmental and social) model to define and classify five main contextual types, and properties associated with each type for tourism‐related applications. The TILES model (with 32 factors) derived from the analysis of the literature review is refined through inputs from two focus groups to incorporate an additional ten factors.

The TILES model can be generalised to support domains other than tourism, such as medical and edutainment.

The model will help to achieve a better understanding of context, users' information needs and their goals. In addition, this work extends findings in the field of context‐aware computing and information retrieval on mobile devices. Solution providers will also be able to adopt TILES as a framework for guiding the design of their context‐aware mobile applications.

Mobile computing research has been focused on developing technologies for handheld devices such as mobile phones, notebook computers, and mobile IP. Today, emphasis is increasing on context‐aware computing, which aims to build the intelligence into mobile devices to sense and respond to the user's context. The purpose of this paper is to present a context‐aware mobile computing model (ContextAlert) that senses the user's context and intelligently configures the mobile phone alert mode accordingly.

The paper proposes a three‐step approach in designing the model based on the embedded sensor data (accelerometer, GPS antenna, and microphone) of a G1 Adriod phone. As adaptivity is essential for context‐aware computing, within this model a new learning mechanism is presented to maintain a constant adaptivity rate for new learning while keeping the catastrophic forgetting problem minimal.

The model has been evaluated in many aspects using data collected from human subjects. The experiment results show that the proposed model performs well and yields a promising result.

This paper is distinguished from other previous papers by: first, using multiple sensors embeded in the mobile phone, which is more realistic for detecting the user's context than having various sensors attached to different parts of user's body; second, by being a novel model that uses sensed contextual information to provide a service that better synchronizes the user's daily life with a context‐aware alert mode. With this service, the user can avoid the problems such as forgetting to switch to vibrate mode while in a meeting or a movie theater, and taking the risk of picking up a phone call while driving, and third, being an adaptive learning algorithm that maintains a constant adaptivity rate for new learning while keeping the catastrophic forgetting problem minimal.

Context‐aware mobile computing extends the horizons of the conventional computing model to a ubiquitous computing environment that serves users at anytime, anywhere. To achieve this, mobile applications need to adapt their behaviors to the changing context. The purpose of this paper is to present a generalized adaptive middleware infrastructure for context‐aware computing.

Owing to the vague nature of context and uncertainty in context aggregation for making adaptation decisions, the paper proposes a fuzzy‐based service adaptation model (FSAM) to improve the generality and effectiveness of service adaptation using fuzzy theory.

By the means of fuzzification of the context and measuring the fitness degree between the current context and the predefined optimal context, FSAM selects the most suitable policy to adopt for the most appropriate service. The paper evaluates the middleware together with the FSAM inference engine by using a Campus Assistant application.

The paper is of value in presenting a generalized adaptive middleware infrastructure for context‐aware computing and also comparing the performance of the fuzzy‐based solution with a conventional threshold‐based approach for context‐aware adaptation.

Context‐aware services platforms aim at supporting the handling of contextual information in order to provide better user‐tailored services. This paper proposes a novel services platform architecture to support mobile context‐aware applications, giving emphasis to the configurability of the platforms generic functionality. The paper introduces concepts and a language to cope with configurability aspects. The paper also reports on the implementation of a prototype, which implements a Web services‐based context‐aware services platform that runs on top of 3G networks.