Mobile Data Science: Towards Understanding Data-Driven Intelligent Mobile Applications

Due to the popularity of smart mobile phones and context-aware technology, various contextual data relevant to users' diverse activities with mobile phones is available around us. This enables the study on mobile phone data and context-awareness in computing, for the purpose of building data-driven intelligent mobile applications, not only on a single device but also in a distributed environment for the benefit of end users. Based on the availability of mobile phone data, and the usefulness of data-driven applications, in this paper, we discuss about mobile data science that involves in collecting the mobile phone data from various sources and building data-driven models using machine learning techniques, in order to make dynamic decisions intelligently in various day-to-day situations of the users. For this, we first discuss the fundamental concepts and the potentiality of mobile data science to build intelligent applications. We also highlight the key elements and explain various key modules involving in the process of mobile data science. This article is the first in the field to draw a big picture, and thinking about mobile data science, and it's potentiality in developing various data-driven intelligent mobile applications. We believe this study will help both the researchers and application developers for building smart data-driven mobile applications, to assist the end mobile phone users in their daily activities.Comment: Journal, 11 pages, Double Colum

Recommendation & mobile systems - a state of the art for tourism

Recommendation systems have been growing in number over the last fifteen years. To evolve and adapt to the demands of the actual society, many paradigms emerged giving birth to even more paradigms and hybrid approaches. These approaches contain strengths and weaknesses that need to be evaluated according to the knowledge area in which the system is going to be implemented. Mobile devices have also been under an incredible growth rate in every business area, and there are already lots of mobile based systems to assist tourists. This explosive growth gave birth to different mobile applications, each having their own advantages and disadvantages. Since recommendation and mobile systems might as well be integrated, this work intends to present the current state of the art in tourism mobile and recommendation systems, as well as to state their advantages and disadvantages

Mobile Augmented Reality: User Interfaces, Frameworks, and Intelligence

Mobile Augmented Reality (MAR) integrates computer-generated virtual objects with physical environments for mobile devices. MAR systems enable users to interact with MAR devices, such as smartphones and head-worn wearables, and perform seamless transitions from the physical world to a mixed world with digital entities. These MAR systems support user experiences using MAR devices to provide universal access to digital content. Over the past 20 years, several MAR systems have been developed, however, the studies and design of MAR frameworks have not yet been systematically reviewed from the perspective of user-centric design. This article presents the first effort of surveying existing MAR frameworks (count: 37) and further discuss the latest studies on MAR through a top-down approach: (1) MAR applications; (2) MAR visualisation techniques adaptive to user mobility and contexts; (3) systematic evaluation of MAR frameworks, including supported platforms and corresponding features such as tracking, feature extraction, and sensing capabilities; and (4) underlying machine learning approaches supporting intelligent operations within MAR systems. Finally, we summarise the development of emerging research fields and the current state-of-the-art, and discuss the important open challenges and possible theoretical and technical directions. This survey aims to benefit both researchers and MAR system developers alike.Peer reviewe

VANET Applications: Hot Use Cases

Current challenges of car manufacturers are to make roads safe, to achieve free flowing traffic with few congestions, and to reduce pollution by an effective fuel use. To reach these goals, many improvements are performed in-car, but more and more approaches rely on connected cars with communication capabilities between cars, with an infrastructure, or with IoT devices. Monitoring and coordinating vehicles allow then to compute intelligent ways of transportation. Connected cars have introduced a new way of thinking cars - not only as a mean for a driver to go from A to B, but as smart cars - a user extension like the smartphone today. In this report, we introduce concepts and specific vocabulary in order to classify current innovations or ideas on the emerging topic of smart car. We present a graphical categorization showing this evolution in function of the societal evolution. Different perspectives are adopted: a vehicle-centric view, a vehicle-network view, and a user-centric view; described by simple and complex use-cases and illustrated by a list of emerging and current projects from the academic and industrial worlds. We identified an empty space in innovation between the user and his car: paradoxically even if they are both in interaction, they are separated through different application uses. Future challenge is to interlace social concerns of the user within an intelligent and efficient driving

Supporting the development of mobile adaptive learning environments: A case study

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. E. Martín and R. M. Carro, "Supporting the development of mobile adaptive learning environments: A case study" IEEE Transactions on learning technologies, vol. 2, no. 1, pp. 23-36, january-march 2009In this paper, we describe a system to support the generation of adaptive mobile learning environments. In these environments, students and teachers can accomplish different types of individual and collaborative activities in different contexts. Activities are dynamically recommended to users depending on different criteria (user features, context, etc.), and workspaces to support the corresponding activity accomplishment are dynamically generated. In this paper, we present the main characteristics of the mechanism that suggests the most suitable activities at each situation, the system in which this mechanism has been implemented, the authoring tool to facilitate the specification of context-based adaptive m-learning environments, and two environments generated following this approach will be presented. The outcomes of two case studies carried out with students of the first and second courses of “Computer Engineering” at the “Universidad Auto´noma de Madrid” are also presented.This work has been supported by the Spanish Ministry of Science and Education, project number TIN2007-64718

Contextual mobile adaptation

Ubiquitous computing (ubicomp) involves systems that attempt to fit in with users’ context and interaction. Researchers agree that system adaptation is a key issue in ubicomp because it can be hard to predict changes in contexts, needs and uses. Even with the best planning, it is impossible to foresee all uses of software at the design stage. In order for software to continue to be helpful and appropriate it should, ideally, be as dynamic as the environment in which it operates. Changes in user requirements, contexts of use and system resources mean software should also adapt to better support these changes. An area in which adaptation is clearly lacking is in ubicomp systems, especially those designed for mobile devices. By improving techniques and infrastructure to support adaptation it is possible for ubicomp systems to not only sense and adapt to the environments they are running in, but also retrieve and install new functionality so as to better support the dynamic context and needs of users in such environments. Dynamic adaptation of software refers to the act of changing the structure of some part of a software system as it executes, without stopping or restarting it. One of the core goals of this thesis is to discover if such adaptation is feasible, useful and appropriate in the mobile environment, and how designers can create more adaptive and flexible ubicomp systems and associated user experiences. Through a detailed study of existing literature and experience of several early systems, this thesis presents design issues and requirements for adaptive ubicomp systems. This thesis presents the Domino framework, and demonstrates that a mobile collaborative software adaptation framework is achievable. This system can recommend future adaptations based on a history of use. The framework demonstrates that wireless network connections between mobile devices can be used to transport usage logs and software components, with such connections made either in chance encounters or in designed multi–user interactions. Another aim of the thesis is to discover if users can comprehend and smoothly interact with systems that are adapting. To evaluate Domino, a multiplayer game called Castles has been developed, in which game buildings are in fact software modules that are recommended and transferred between players. This evaluation showed that people are comfortable receiving semi–automated software recommendations; these complement traditional recommendation methods such as word of mouth and online forums, with the system’s support freeing users to discuss more in–depth aspects of the system, such as tactics and strategies for use, rather than forcing them to discover, acquire and integrate software by themselves