Preprocessing techniques for context recognition from accelerometer data

The ubiquity of communication devices such as smartphones has led to the emergence of context-aware services that are able to respond to specific user activities or contexts. These services allow communication providers to develop new, added-value services for a wide range of applications such as social networking, elderly care and near-emergency early warning systems. At the core of these services is the ability to detect specific physical settings or the context a user is in, using either internal or external sensors. For example, using built-in accelerometers, it is possible to determine whether a user is walking or running at a specific time of day. By correlating this knowledge with GPS data, it is possible to provide specific information services to users with similar daily routines. This article presents a survey of the techniques for extracting this activity information from raw accelerometer data. The techniques that can be implemented in mobile devices range from classical signal processing techniques such as FFT to contemporary string-based methods. We present experimental results to compare and evaluate the accuracy of the various techniques using real data sets collected from daily activities.     

A prediction and auto-execution system of smartphone application services based on user context-awareness

Smartphones have emerged as suitable environments for user context-awareness and intelligent service provision due to the high penetration rate, the high usability, various embedded sensors, and so on. In particular, its most unique characteristic is the usage of various applications. However, the most of existing studies through the three steps process (log collection, context inference, and service provision) did not consider smartphone applications (Apps) as the target service. Smartphone users still have to use Apps with manual controls by own decision. Therefore, in this paper, we propose a system to predict smartphone applications based on inferring user context. We define a mobile context model with a new level of context (Situation) and its inference method to perceive a user’s intention or purpose related to the App usage. Based on the Situation context, the system predicts Apps which can be useful and helpful for a user and automatically executes it on his/her smartphone. With the proposed system, it will be possible to autonomously provide and manage smartphone application services without users’ perception or intervention.     

A novel mobile device user interface with integrated social networking services

Modern mobile devices support accessing Web-based social networking services from the user interface (UI) of Web browsers, applications, and mobile widgets. While effectively accessing these services, people may find it tedious to switch between multiple user interfaces in order to be aware of the latest content. Aiming for an improved user experience, we experimented with integration of these services into mobile devices' main user interface. The integrated content is presented beyond application silos and automatically filtered to highlight the relevant elements. A mobile system called LinkedUI was developed and deployed in one lab test and one field study. Three findings emerge from these studies. Firstly, it is feasible to construct an alternative device UI that supports integration of Web content across applications and services via hyperlinking. Time, publisher (e.g., contacts), content types, and geographical locations are key dimensions for association of content. Secondly, the alternative device UI enables better usability of accessing social networking services than accessing them from individual Web sites on mobile devices. It helps people to be aware of the latest content during microbreaks. Thirdly, automatic filtering, on the basis of one user's data, is one promising approach to identifying relevant content. Given filtered content, most people using the automatic filtering approved the functionality and experienced a better sense of control that is arguably due to the reduced information volume.     

An Adaptive Middleware for Context-Sensitive Communications for Real-Time Applications in Ubiquitous Computing Environments

Context-sensitivity is an important expected capability in applications in ubiquitous computing (ubicomp) environments. These applications need to use different contextual information from the user, host device, on board sensors, network, and the ambient environments to systematically adapt their actions. In addition, some context-sensitive applications may use specific contextual conditions to trigger impromptu and possibly short-lived interactions with applications in other devices. This property, referred to as context-sensitive or context-aware communications, allows applications to form short-range mobile ad hoc networks consisting of mobile and stationary devices, sensors, and other computing resources. Real-time applications, especially those having reactive behavior, running on embedded devices and requiring context-sensitive communications support, pose new challenges related to systematic representation of specific contexts, associations of contexts with real-time actions, timely context data collection and propagation, and transparent context-sensitive connection establishment. An object-based middleware can be effective to meet these challenges if such a middleware can provide a well-defined development framework as well as lightweight runtime services. In this paper, an adaptive and object-based middleware, called reconfigurable context-sensitive middleware (RCSM) is presented to facilitate context-sensitive communications in ubicomp environments. To facilitates context-sensitive communications, RCSM provides a context-aware interface definition language for specifying context-sensitive interfaces of real-time objects, an object container framework for generating interfaces-specific context-analyzers, and a context-sensitive object request broker for context-sensitive object discovery and impromptu connection management. RCSM is adaptive in the sense that depending on the context-sensitive behavior of the applications, it adapts its object discovery and connection management mechanisms.     

A mobility constraint model to infer sensor behaviour in forest fire risk monitoring

Wireless sensor networks (WSNs) play an important role in forest fire risk monitoring. Various applications are in operation. However, the use of mobile sensors in forest risk monitoring remains largely unexplored. Our research contributes to fill this gap by designing a model which abstracts mobility constraints within different types of contexts for the inference of mobile sensor behaviour. This behaviour is focused on achieving a suitable spatial coverage of the WSN when monitoring forest fire risk. The proposed mobility constraint model makes use of a Bayesian network approach and consists of three components: (1) a context typology describing different contexts in which a WSN monitors a dynamic phenomenon; (2) a context graph encoding probabilistic dependencies among variables of interest; and (3) contextual rules encoding expert knowledge and application requirements needed for the inference of sensor behaviour. As an illustration, the model is used to simulate the behaviour of a mobile WSN to obtain a suitable spatial coverage in low and high fire risk scenarios. It is shown that the implemented Bayesian network within the mobility constraint model can successfully infer behaviour such as sleeping sensors, moving sensors, or deploying more sensors to enhance spatial coverage. Furthermore, the mobility constraint model contributes towards mobile sensing in which the mobile sensor behaviour is driven by constraints on the state of the phenomenon and the sensing system.     

Autonomic control and personalization of a wireless access network

As ICT services are becoming more ubiquitous and mobile and access technologies grow to be more heterogeneous and complex, we are witnessing the increasing importance of two related needs: (i) users need to be able to configure and personalize their services with minimal effort; (ii) operators desire to engineer and manage their networks easily and efficiently, limiting human agency as far as possible. We propose a possible solution to reach these goals. Our vision, developed in the so-called Simplicity project, is based on a personalization device, which, together with a brokerage framework, offers transparent service configuration and runtime adaptation, according to user preferences and computing/networking context conditions. The capabilities of this framework can be exploited: (i) on the user side, to personalize services, to improve the portability of services over heterogeneous terminals and devices, to adapt services to available networking and terminal technologies; (ii) on the network side, to give operators more powerful tools to define new solutions for distributed, technology-independent, self-organizing, autonomic networking systems. Such systems could be designed so as to be able to react autonomously to changing contexts and environments.In this paper, we first describe the main aspects of the Simplicity solution. We then want to show that our approach is indeed viable. To prove this point, we present an application which exploits the capabilities of the Simplicity system: a mechanism to drive mobile users towards the most appropriate point of access to the network, taking into account both user preferences and network context. We use simulation to evaluate the performance of this procedure in a specific case study, where the aim is to balance the load in an 802.11b access network scenario. The numerical results show the effectiveness of the proposed procedure when compared to a legacy scenario and to another solution from literature.To give ample proof of the feasibility of our solution, we also designed and implemented a real prototype. The prototype enables not only the load to be balanced among different 802.11 access points, but also network and application services to be differentiated as a function of user profiles and network load. The main aspects of this prototype are presented in this paper.     

Ubiquitous conference management system for mobile recommendation services based on mobilizing social networks: A case study of u-conference

In this paper, we propose a social network-based mechanism to be aware of user contexts and to provide contextually relevant mobile services to users. A social network among users is regarded as the channel for exchanging and propagating their contexts. To efficiently discover the contexts of a certain users the contexts of his neighbors can be fused to provide mobile recommendation service to mobile subscribers. However, since the social network of a user has been fragmented into more than one, it is difficult to put the number of contexts from the fragmented social networks together (Jung, 2009b). Thereby, we mobilize all possible on- and off-line social networks to build an ego-centric social network. We have implemented the proposed system, which is called u-conference system, by collecting the social network dataset from online (e.g., Facebook, Twitter, CyWorld, and co-authoring patterns in major Korean journals) and offline (e.g., co-participation patterns in a number of Korean domestic conferences). Once we have implemented the system, we have provided mobile services to the conference participants by sending text messages about time schedule of relevant presentations.     

Social networking on smartphones: When mobile phones become addictive

As the penetration of mobile phones in societies increases, there is a large growth in the use of mobile phones especially among the youth. This trend is followed by the fast growth in use of online social networking services (SNS). Extensive use of technology can lead to addiction. This study finds that the use of SNS mobile applications is a significant predictor of mobile addiction. The result also shows that the use of SNS mobile applications is affected by both SNS network size and SNS intensity of the user. This study has implications for academia as well as governmental and non-for-profit organizations regarding the effect of mobile phones on individual’s and public health.     

Cross-community context management in Cooperating Smart Spaces

Recently, social networks have become the most prevalent IT paradigm, as the vast majority of Internet users maintain one or multiple social networking accounts. These accounts, irrespectively of the underlying service, contain rich information and data for the owner’s preferences, social skills, everyday activities, beliefs and interests. Along with these services, the computation, sensing and networking capabilities of the state of the art mobile and portable devices, with their always-on mode, assist users in their everyday lives. Thus, the integration of social networking services with current pervasive computing systems could provide the users with the potential to interact with other users that have similar interests, preferences and expectations; and in general, the same or similar context, for limited or not time periods, in order to ameliorate their overall experience, communicate, socialise and improve their everyday activities with minimal effort. This paper introduces a cross-community context management framework that is suitable for Cooperating Smart Spaces, which couple the advantages of pervasive computing and social networking. This framework goes beyond the state of the art, among others, in that cross-community context from a multitude of sources is collected and processed to enhance the end user experience and increase the perceived value of the services provided.     

Semantic management of multiple contexts in a pervasive computing framework

Mobile devices can perceive greater details of user states with the increasing integration of mobile sensors into a pervasive computing framework, yet they consume large amounts of batteries and computational resources. This paper proposes a semantic management method which efficiently integrates multiple contexts into the mobile system by analyzing the semantic hierarchy and temporal relations. The proposed method semantically decides the recognition order of the contexts and identifies each context using a corresponding dynamic Bayesian network (DBN). To sort out the contexts, we designed a semantic network using a knowledge-driven approach, whereas DBNs are constructed with a data-driven approach. The proposed method was validated on a pervasive computing framework, which included multiple mobile sensors (such as motion sensors, data-gloves, and bio-signal sensors). Experimental results showed that the semantic management of multiple contexts dramatically reduced the recognition cost.     

Mobile guides: Taxonomy of architectures,context awareness,technologies and applications

Portable devices are increasingly employed in a wide range of mobile guidance applications. Typical examples are guides in urban areas, museum guides, and exhibition space aids. The demand is for the delivery of context-specific services, wherein the context is typically identified by a combination of data related to location, time, user profile, device profile, network conditions and usage scenario. A context-aware mobile guide is intended to provide guidance services adjusted to the context of the received request. The adjustment may refer to tailoring the user interface to the perceived context, as well as delivering the right type of information to the right person at the right time and the right location. It may also refer to intermediary adaptation, as in the case of mobile multimedia transmission. This paper offers a taxonomy of mobile guides considering multiple criteria. The taxonomy considers several aspects of the mobile applications space, including context awareness, client architectures, mobile user interfaces, as well as offered functionalities, highlighting functional, architectural, technological, and implementation issues. Existing implementations are classified accordingly and a discussion of research issues and emerging trends is offered.     

Unsupervised context detection using wireless signals

The sensing context plays an important role in many pervasive and mobile computing applications. Continuing from previous work [D. Phung, B. Adams, S. Venkatesh, Computable social patterns from sparse sensor data, in: Proceedings of First International Workshop on Location Web, World Wide Web Conference (WWW), New York, NY, USA, 2008, ACM 69–72.], we present an unsupervised framework for extracting user context in indoor environments with existing wireless infrastructures. Our novel approach casts context detection into an incremental, unsupervised clustering setting. Using WiFi observations consisting of access point identification and signal strengths freely available in office or public spaces, we adapt a density-based clustering technique to recover basic forms of user contexts that include user motion state and significant places the user visits from time to time. High-level user context, termed rhythms, comprising sequences of significant places are derived from the above low-level context by employing probabilistic clustering techniques, latent Dirichlet allocation and its n-gram temporal extension. These user contexts can enable a wide range of context-ware application services. Experimental results with real data in comparison with existing methods are presented to validate the proposed approach. Our motion classification algorithm operates in real-time, and achieves a 10% improvement over an existing method; significant locations are detected with over 90% accuracy and near perfect cluster purity. Richer indoor context and meaningful rhythms, such as typical daily routines or meeting patterns, are also inferred automatically from collected raw WiFi signals.     

社交网络中的位置隐私保护研究

随着智能终端设备和社交网络服务的广泛使用,移动互联网发展的一个重要趋势是社交、位置和移动相融合,在这些应用中,位置是一项非常重要的信息。该文从位置隐私泄露的风险出发,介绍了几种位置隐私保护技术,比较它们的优劣,提出了移动感知的匿位区域生成方法,通过信息熵理论将用户位置的不可推测性最大化,实现了社交网络中个人隐私保护。     

Context-awareness in wearable and ubiquitous computing

A common focus shared by researchers in mobile, ubiquitous and wearable computing is the attempt to break away from the traditional desktop computing paradigm. Computational services need to become as mobile as their users. Whether that service mobility is achieved by equipping the user with computational power or by instrumenting the environment, all services need to be extended to take advantage of the constantly changing context in which they are accessed. This paper will report on work carried out by the Future Computing Environments Group at Georgia Tech to provide infrastructure for context-aware computing. We will describe some of the fundamental issues involved in contextaware computing, solutions we have generated to provide a flexible infrastructure and several applications that take advantage of context awareness to allow freedom from traditional desktop computing.     

Triggering information by context

With the increased availability of personal computers with attached sensors to capture their environment, there is a big opportunity forcontext-aware applications; these automatically provide information and/or take actions according to the user's present context, as detected by sensors. When well designed, these applications provide an opportunity to tailor the provision of information closely to the user's current needs. A sub-set of context-aware applications arediscrete applications, where discrete pieces of information are attached to individual contexts, to be triggered when the user enters those contexts. The advantage of discrete applications is that authoring them can be solely a creative process rather than a programming process: it can be a task akin to creating simple web pages. This paper looks at a general system that can be used in any discrete context-aware application. It propounds a general triggering rule, and investigates how this rule applies in practical applications.     

Design and validation of a light inference system to support embedded context reasoning

Embedded context management in resource-constrained devices (e.g. mobile phones, autonomous sensors or smart objects) imposes special requirements in terms of lightness for data modelling and reasoning. In this paper, we explore the state-of-the-art on data representation and reasoning tools for embedded mobile reasoning and propose a light inference system (LIS) aiming at simplifying embedded inference processes offering a set of functionalities to avoid redundancy in context management operations. The system is part of a service-oriented mobile software framework, conceived to facilitate the creation of context-aware applications—it decouples sensor data acquisition and context processing from the application logic. LIS, composed of several modules, encapsulates existing lightweight tools for ontology data management and rule-based reasoning, and it is ready to run on Java-enabled handheld devices. Data management and reasoning processes are designed to handle a general ontology that enables communication among framework components. Both the applications running on top of the framework and the framework components themselves can configure the rule and query sets in order to retrieve the information they need from LIS. In order to test LIS features in a real application scenario, an ‘Activity Monitor’ has been designed and implemented: a personal health-persuasive application that provides feedback on the user’s lifestyle, combining data from physical and virtual sensors. In this case of use, LIS is used to timely evaluate the user’s activity level, to decide on the convenience of triggering notifications and to determine the best interface or channel to deliver these context-aware alerts.     

Ubiquitous enterprise service adaptations based on contextual user behavior

Recent advances in mobile technologies and infrastructures have created the demand for ubiquitous access to enterprise services from mobile handheld devices. Further, with the invention of new interaction devices, the context in which the services are being used becomes an integral part of the activity carried out with the system. Traditional human–computer interface (HCI) theories are now inadequate for developing these context-aware applications, as we believe that the notion of context should be extended to different categories: computing contexts, user contexts, and physical contexts for ubiquitous computing. This demands a new paradigm for system requirements elicitation and design in order to make good use of such extended context information captured from mobile user behavior. Instead of redesigning or adapting existing enterprise services in an ad hoc manner, we introduce a methodology for the elicitation of context-aware adaptation requirements and the matching of context-awareness features to the target context by capability matching. For the implementation of such adaptations, we propose the use of three tiers of views: user interface views, data views, and process views. This approach centers on a novel notion of process views to ubiquitous service adaptation, where mobile users may execute a more concise version or modified procedure of the original process according to their behavior under different contexts. The process view also serves as the key mechanism for integrating user interface views and data views. Based on this model, we analyze the design and implementation issues of some common ubiquitous access situations and show how to adapt them systematically into a context-aware application by considering the requirements of a ubiquitous enterprise information system.

Contextual influences on user satisfaction with mobile computing: findings from two healthcare organizations

Mobile information technologies (IT) are transforming individual work practices and organizations. These devices are extending not only the boundaries of the ‘office’ in space and time, but also the social context within which use occurs. In this paper, we investigate how extra-organizational influences can impact user satisfaction with mobile systems. The findings from our longitudinal study highlight the interrelatedness of different use contexts and their importance in perceptions of user satisfaction. The data indicate that varying social contexts of individual use (individual as employee, as professional, as private user, and as member of society) result in different social influences that affect the individual's perceptions of user satisfaction with the mobile technology. While existing theories explain user satisfaction with IT within the organizational context, our findings suggest that future studies of mobile IT in organizations should accommodate such extra-organizational contextual influences.     

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.     

Privacy policies for shared content in social network sites

Social networking is one of the major technological phenomena of the Web 2.0, with hundreds of millions of subscribed users. Social networks enable a form of self-expression for users and help them to socialize and share content with other users. In spite of the fact that content sharing represents one of the prominent features of existing Social network sites, they do not provide any mechanisms for collective management of privacy settings for shared content. In this paper, using game theory, we model the problem of collective enforcement of privacy policies on shared data. In particular, we propose a solution that offers automated ways to share images based on an extended notion of content ownership. Building upon the Clarke-Tax mechanism, we describe a simple mechanism that promotes truthfulness and that rewards users who promote co-ownership. Our approach enables social network users to compose friendship based policies based on distances from an agreed upon central user selected using several social networks metrics. We integrate our design with inference techniques that free the users from the burden of manually selecting privacy preferences for each picture. To the best of our knowledge, this is the first time such a privacy protection mechanism for social networking has been proposed. We also extend our mechanism so as to support collective enforcement across multiple social network sites. In the paper, we also show a proof-of-concept application, which we implemented in the context of Facebook, one of today’s most popular social networks. Through our implementation, we show the feasibility of such approach and show that it can be implemented with a minimal increase in overhead to end-users. We complete our analysis by conducting a user study to investigate users’ understanding of co-ownership, usefulness and understanding of our approach. Users responded favorably to the approach, indicating a general understanding of co-ownership and the auction, and found the approach to be both useful and fair.