Towards Ambient Business

Ubiquitous computing enables the development of new innovative applications and services. Particularly influential on future business services will be the connection of the real with the virtual world by embedding computers or smallest processors, memory chips, and sensors into the environment and into physical objects, as well as using natural, multimodal customer interaction. Bearing in mind that ubiquitous computing entails the interaction of mobile smart objects and local smart environments hosted by different service providers, we propose an open approach to encourage the development of new and innovative smart applications and services. Considering the Open Source community, we assert that such an open approach reveals innovation potentials that cannot be achieved in proprietary information system environments. Most research projects, as well as commercial initiatives, however, focus mainly on specific, proprietary applications like smart shopping environments, and do not incorporate further prospects of using an open approach. Therefore, this chapter discusses as a first step the impact of Open Innovation in a world of ubiquitous computing from an economic perspective. Then, the design of an Open Object Information Infrastructure (OOII) that enables Open Innovation in the context of ubiquitous computing is presented. Finally, an innovative smart service called the Federative Library (FedLib), which represents a first instantiation of the OOII, is introduced to demonstrate the feasibility of the design.

Enabling Programmable Ubiquitous Computing Environments

Emerging pervasive computing scenarios involve client applications that dynamically collect information directly from the local environment. The sophisticated distribution and dynamics involved in these applications place an increased burden on developers that create applications for these environments. The heightened desire for rapid deployment of a wide variety of pervasive computing applications demands a new approach to application development in which domain experts with minimal programming expertise are empowered to rapidly construct and deploy domainspecific applications. This chapter introduces the DAIS (Declarative Applications in Immersive Sensor networks) middleware that abstracts a heterogeneous and dynamic pervasive computing environment into intuitive and accessible programming constructs. At the programming interface level, this requires exposing some aspects of the physical world to the developer, and DAIS accomplishes this through a suite of novel programming abstractions that enable on-demand access to dynamic local data sources. A fundamental component of the model is a hierarchical view of pervasive computing middleware that allows devices with differing capabilities to support differing amounts of functionality. This chapter reports on our design of the DAIS middleware and highlights the abstractions, the programming interface, and the reification of the middleware on a heterogeneous combination of client devices and resource-constrained sensors.

M-Traffic

Traffic information is crucial in metropolitan areas, where a high concentration of moving vehicles causes traffic congestion and blockage. Appropriate traffic information received at the proper time helps users to avoid unnecessary delays, choosing the fastest route that serves their purposes. This work presents Mobile Traffic (M-Traffic), a multiplatform online traffic information system, which provides real-time traffic information based on image processing, sensor’s data, and traveller behaviour models. This system has a modular architecture that allows it to easily be adapted to new data sources and additional distribution platforms. In order to estimate route delay and feed the optimal routing algorithm, a traffic microscopic simulation model was developed, and simulation results are presented. This mobile information service ubiquitously provides users with traffic information regarding their needs and preferences, according to an alert system, which allows a personalized pre-definition of warning messages.

Model-Driven Development for Pervasive Information Systems

This chapter focuses on design methodologies for pervasive information systems (PIS). It aims to contribute to the efficiency and effectiveness of software development of ubiquitous services/applications supported on pervasive information systems. Pervasive information systems are comprised of conveniently orchestrated embedded or mobile computing devices that offer innovative ways to support existing and new business models. Those systems are characterized as having a potentially large number of interactive heterogeneous embedded/mobile computing devices that collect, process, and communicate information. Also, they are the target of technological innovations. Therefore, changes in requirements or in technology require frequent modifications of software at device and system levels. Software design and evolution for those require suitable approaches that consider such demands and characteristics of pervasive information systems. Model-driven development approaches (which essentially centre the focus of development on models, and involve concepts such as Platform-Independent Models, Platform-Specific Models, model transformations, and use of established standards) currently in research at academic and industrial arenas in the design of large systems, offer potential benefits that can be applied to the design and evolution of these pervasive information systems. In this chapter, we raise issues and propose strategies related to the software development of PIS using a model-driven development perspective.

Privacy Threats in Emerging Ubicomp Applications

Realisation of the Ubicomp vision in the real world creates significant threats to personal privacy due to constant information collection by numerous tiny sensors, active information exchange over short and long distances, long-term storage of large quantities of data, and reasoning based on collected and stored data. An analysis of more than 100 Ubicomp scenarios, however, shows that applications are often proposed without considering privacy issues, whereas existing privacyenhancing technologies mainly have been developed for networked applications and, thus, are not always applicable to emerging applications for smart spaces and personal devices, especially because the users and their data are not spatially separated in such applications. A partial solution to the problem of users’ privacy protection could be to allow users to control how their personal data can be used. The authors’ experience with mobile phone data collection, nevertheless, suggests that when users give their consent for the data collection, they don’t fully understand the possible privacy implications. Thus, application developers should pay attention to privacy protection; otherwise, such problems could result in users not accepting Ubicomp applications. This chapter suggests guidelines for estimating threats to privacy, depending on real world application settings and the choice of technology; and guidelines for the choice and development of technological safeguards against privacy threats.

Kinetic User Interfaces

This chapter presents a conceptual framework for an emerging type of user interfaces for mobile ubiquitous computing systems, and focuses in particular on the interaction through motion of people and objects in physical space. We introduce the notion of Kinetic User Interface as a unifying framework and a middleware for the design of pervasive interfaces, in which motion is considered as the primary input modality.

Designing for Tasks in Ubiquitous Computing

The traditional desktop computing paradigm has had major successes. It also should be noted that we are in a day and age where many good computer and device users are increasingly finding themselves being required to perform their activities not in offices/desktops but in real-world settings. Ubiquitous computing can make possible in the real-world setting what would have otherwise been impossible through desktop computing. However, there is a world of difference between the real-world and the desktop settings. The move from the desktop to the real-world settings raises various issues when we consider the nature of tasks that the ubiquitous devices/applications would be expected to support and the real-world context in which they will be used. A careful study of the nature of tasks in ubiquitous computing can make some design requirements in the development of ubiquitous applications more evident. This chapter proposes ubiquitous application design and evaluation considerations emerging from a deeper understanding of the nature of tasks in ubiquitous computing.

Context-Aware Mobile Learning on the Semantic Web

This chapter focuses on the theoretical and technological aspects of designing mobile learning (m-learning) services that deliver context-aware learning resources from various locations and devices. Context-aware learning is an important requirement for next generation intelligent m-learning systems. The use of context in mobile devices is receiving increasing attention in mobile and ubiquitous computing research. In this research work, context reflects timeliness and mobility to nurture pervasive instruction throughout the learning ecosystem. In this context of ubiquity that is supported by a new generation of mobile wireless networks and smart mobile devices, it is clear that the notion of context plays a fundamental role since it influences the computational capabilities of the used technology. In particular, three types of context awareness are being considered in this work —platform-awareness, learner-awareness, and task-awareness. In this research work, these contextual elements are defined at the semantic level in order to facilitate discoverability of context-compliant learning resources, adaptability of content and services to devices of various capabilities, and adaptability of services to task at hand and interaction history. The work presented in this chapter contributes towards this direction, making use of the progress in Semantic Web theory and mobile computing to enable context-aware learning that satisfies learning timeliness and mobility requirements.

Device Localization in Ubiquitous Computing Environments

In this chapter, we will study the localization problem in ubiquitous computing environments. In general, localization refers to the problem of obtaining (semi-) accurate physical location of the devices in a dynamic environment in which only a small subset of the devices know their exact location. Using localization techniques, other devices can indirectly derive their own location by means of some measurement data such as distance and angle to their neighbors. Localization is now regarded as an enabling technology for ubiquitous computing environments because it can substantially increase the performance of other fundamental tasks such as routing, energy conservation, and network security. Localization is also a difficult problem because it is computationally intractable. Furthermore, it has to be implemented in a highly dynamic and distributed environment in which measurement data is often subject to noise. In this chapter, we will give an overview of localization in terms of its common applications, its hardware capacities, its algorithms, and its computational complexity.

Mobile Phone and Visual Tags

The growing ubiquity and usability of smart mobile phones can be exploited to develop popular and realistic pervasive computing applications. Adding image processing capabilities to a mobile phone equipped with a built-in camera makes it an easy-to-use device for linking physical objects to a networked computing environment. This chapter describes an extensible and portable programming platform that, using bi-dimensional visual tags, turns mass-market camera-phones into a system able to capture digital information from real objects, use such information to download specific application code, and act as a GUI for interacting with object-dependent computational services. The system includes a module for on-phone extraction of visual coded information and supports the dynamic download of mobile applications.