Personal service areas for mobile Web applications

Location-based mobile services let wireless mobile users access Web-based information about resources in their immediate vicinities. The authors describe an algorithm that draws on context mobility elements, such as the user's travel direction and speed, to form personal service areas. Their experimental context-aware tourist information system (CATIS) leverages XML technologies and Web services to provide tourist information to mobile users based on these personal service areas and the users' preferences. Because Web service performance depends on the underlying databases, the authors also developed a layered caching scheme for storing environmental data to improve response time.     

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.     

基于无线局域网的室内临近位置检测代理实现

传统基于网络的位置服务系统主要是为远程用户提供查询移动对象位置的信息服务。而现有基于移动终端的位置感知服务不能满足位置上下文应用的要求．为了达到系统自动自发的上下文交互目的。需要在应用中定义一个位置检测代理来捕获移动设备的位置变化事件．生成有效的上下文信息．本文使用简单贝叶斯分类算法实现了基于无线局域网的临近位置检测代理．在室内环境中进行实验表明。该方法可根据实际需要调整位置检测的范围与准确度。具有可行性与灵活性．     

情景感知的物联网服务推荐方法研究

如何根据用户实时的情景高效地为其推荐最为合适的物联网服务,已经成为当前服务计算与物联网领域亟需解决的关键问题之一。针对这一问题,提出了一种基于情景感知的物联网服务推荐方法。首先基于改进的FolkRank算法生成当前用户可用的物联网服务列表;之后,依据用户当前关键的情景构建用户情景信息模型,根据用户的情景模型从服务列表中筛选出最能满足用户当前情景的物联网服务。实验结果表明,所提出的情景感知的物联网服务推荐方法是可行的与有效的。     

Intelligent healthcare service based on context inference using smart device

In the field of “U-Healthcare Service”, many studies have been actively conducted to develop “smart device”-based healthcare applications that enable healthcare providers and patients to be better served through interoperations among various kinds of sensors and wireless network interfaces. In particular, contemporary intelligent healthcare services not only recognize users’ context information through smart devices, computers, and so forth, but also acquire information from heterogeneous sensors to achieve context-aware inference services. Among such information, the weather information is tightly related to diseases such as asthma and allergies. Therefore, there is a high demand for research to utilize the weather information for healthcare services. In this paper, we propose a context inference-based intelligent healthcare service that exploits both the weather conditions information and the diverse healthcare ontologies available on the Internet. The proposed service aims at modeling a context ontology in users’ healthcare service environment and defining the inference rules, thereby accomplishing a satisfactory real-time healthcare service.     

Item recommendation based on context-aware model for personalized u-healthcare service

A personalized service in the ubiquitous environment is to provide services or items, which reflect personal tastes, attitudes, and contexts. It is impossible to reflect the context information generated in u-healthcare environments due to the existing recommendation system performing the recommendation using the information directly input by users and application usage record only. This study develops a context-aware model using the context information provided by the context information model. The study applies it to the extraction of the missing value in a collaborative filtering process. The context-aware model reflects the information that selects items by users according to the appropriate context using the C-HMM and provides it to users. The solution of the missing value in the preference significantly affects the recommendation accuracy in a preference based item supply method. Thus, this study developed a new collaborative filtering for ubiquitous environments by reflecting the missing preference value and reflecting it to the collaborative filtering using the context-aware model. Also, the validity of this method will be evaluated by applying it to menu services in u-healthcare services.     

Progress in context-aware recommender systems — An overview

Recommender Systems are the set of tools and techniques to provide useful recommendations and suggestions to the users to help them in the decision-making process for choosing the right products or services. The recommender systems tailored to leverage contextual information (such as location, time, companion or such) in the recommendation process are called context-aware recommender systems. This paper presents a review on the continual development of context-aware recommender systems by analyzing different kinds of contexts without limiting to any specific application domain. First, an in-depth analysis is conducted on different recommendation algorithms used in context-aware recommender systems. Then this information is used to find out that how these techniques deals with the curse of dimensionality, which is an inherent issue in such systems. Since contexts are primarily based on users’ activity patterns that leads to the development of personalized recommendation services for the users. Thus, this paper also presents a review on how this contextual information is represented (either explicitly or implicitly) in the recommendation process. We also presented a list of datasets and evaluation metrics used in the setting of CARS. We tried to highlight that how algorithmic approaches used in CARS differ from those of conventional RS. In that, we presented what modification or additions are being applied on the top of conventional recommendation approaches to produce context-aware recommendations. Finally, the outstanding challenges and research opportunities are presented in front of the research community for analysis     

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.     

COLLECT: COLLaborativE ConText-aware service oriented architecture for intelligent decision-making in the Internet of Things

Internet of Things (IoT) has radically transformed the world; currently, every device can be connected to the Internet and provide valuable information for decision-making. In spite of the fast evolution of technologies accompanying the grow of IoT, we are still faced with the challenge of providing a service oriented architecture, which facilitates the inclusion of data coming together from several IoT devices, data delivery among a system's agents, real-time data processing and service provision to users. Furthermore, context-aware data processing and architectures still pose a challenge, in spite of being key requirements in order to get stronger IoT architectures. To face this challenge, we propose a COLLaborative ConText Aware Service Oriented Architecture (COLLECT), which facilitates both the integration of IoT heterogeneous domain context data — through the use of a light message broker — and easy data delivery among several agents and collaborative participants in the system — making use of an enterprise service bus —. In addition, this architecture provides real-time data processing thanks to the use of a complex event processing engine as well as services and intelligent decision-making procedures to users according to the needs of the domain in question. As a result, COLLECT has a great impact on context-aware decentralized and collaborative reasoning for IoT, promoting context-aware intelligent decision making in such scope. Since context-awareness is key for a wide range of recommender and intelligent systems, the presented novel solution improves decision making in a large number of fields where such systems require to promptly process a variety of ubiquitous collaborative and context-aware data.     

Context-adaptive and energy-efficient mobile transaction management in pervasive environments

Pervasive computing is a user-centric, scalable, parallel, and distributed computing paradigm, allowing users to access to their preferred services even while moving around. Transaction management for pervasive environments has to provide mobile users with reliable and transparent services anytime anywhere. To make such a vision a reality, the communication of pervasive transaction processing should be context-aware for adapting to dynamically changing execution environments, and energy-efficient for prolonging the lifetime of battery-powered mobile devices. In this paper, we propose a context model and a context-aware transaction model for pervasive transactions, and present a c\underline{\mathrm{c}} ontext-adaptive and e\underline{\mathrm{e}} nergy-efficient t\underline{\mathrm{t}} ransaction m\underline{\mathrm{m}} anagement mechanism (CETM) that can dynamically adjust transaction execution behaviors in terms of current context information. Moreover, we model and verify the correctness of the CETM through Petri nets. The simulation results have demonstrated that our transaction management mechanism CETM can significantly reduce the failed probability of concurrent pervasive transactions.     

基于本体的NGN上下文感知业务设计与实现

为使NGN业务具有良好的适应性满足用户在灵活多变环境下的需要,提出基于本体的上下文感知业务生成框架,该框架对NGN中上下文业务系统的开发起到关键作用。分析NGN业务实现关键问题以及利用本体进行感知计算的方法,最后给出业务实现实例说明技术应用方法和该框架的可行性。     

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.     

Experiences in developing mobile applications using the Apricot Agent Platform

The trend of increasing mobile services has set a new challenge for service providers: how to develop more advanced and user-friendly, context-aware and personalized mobile services for the users. Apricot Agent Platform is an agent-based software platform designed for developing context-aware and personalized mobile services. Apricot Agent Platform supports the development of user-friendly mobile services by providing tools for combining various mobile and Internet-based services. Apricot agent architecture consists of an agent platform, agents and agent containers. For the developers of mobile services, it provides built-in functionality and communication mechanism. Furthermore, this paper describes four demonstrators that are built up on the Apricot Agent Platform to evaluate the usability and efficiency of the platform in the processes of building mobile services. The outcome of the evaluation indicates relatively promising results and the further target for development is revealed.     

User needs for location-aware mobile services

Mobile contexts of use vary a lot, and may even be continuously changing during use. The context is much more than location, but its other elements are still difficult to identify or measure. Location information is becoming an integral part of different mobile devices. Current mobile services can be enhanced with location-aware features, thus providing the user with a smooth transition towards context-aware services. Potential application fields can be found in areas such as travel information, shopping, entertainment, event information and different mobile professions. This paper studies location-aware mobile services from the user's point of view. The paper draws conclusions about key issues related to user needs, based on user interviews, laboratory and field evaluations with users, and expert evaluations of location-aware services. The user needs are presented under five main themes: topical and comprehensive contents, smooth user interaction, personal and user-generated contents, seamless service entities and privacy issues.     

基于上下文感知的普适服务框架

为了更好地适应用户的个性化需求和普适计算环境的特征,提出一种基于上下文感知的普适服务框架。该框架包括服务呈现层、服务管理层、服务提供层和上下文感知层。通过基于社区的服务管理方式来屏蔽普适计算环境中服务的异构性、分布性,动态地感知与当前计算环境和用户活动相关的上下文信息,采用基于上下文的服务推荐机制为用户提供个性化的服务,从而更好地适应人的意图和环境 因素。     

The security service rating design for IT convergence services

There has been damage to users due to security problems such as personal information leaks and spam etc. by IT convergence in various information communication industries. Since where the responsibility for this damage lies, compensation systems and damage estimation criteria have not been prepared yet, its compensation is solved by civil litigation between service providers and users. In addition, for security services provided, the standardized clauses of a contract with consumers are provider-oriented articles to be disadvantageous to service users, and detailed compensation criteria have not been prepared in reality. Therefore, it is time to need to prepare a damage compensation system and an estimation criterion for protecting users against technical and legal troubles that could arise when providing security services. In order to solve these problems, this paper developed a damage compensation index for sustainable security service. In detail, by analyzing damage compensation criteria and cases for general information communication services, a damage compensation index on security services was developed for a goal of VoIP services. It could offer voluntary improvement of service quality for service providers, and simplicity of damage compensation for users. Additionally, it could socially give benefits of increasing the number of companies to apply the security SLA and mitigating legal disputes.     

Context-aware multiagent system: Planning home care tasks

Context-aware systems are able to capture information from the context in which they are executed, assign a meaning to the gathered information, and change their behavior accordingly. As a result, the systems can offer services to users according to their individual situation within the context. This article analyzes the important aspects of context-aware computing such as capturing information for context attributes and determining the manner of interacting with users in the environment. Used in conjunction with mobile devices, context-aware systems are specifically used to improve the usability of applications and services. This article proposes the home care context-aware computing (HoCCAC) multiagent system that identifies and maintains a permanent fix on the location of patients in their home, and manages the infrastructure of services within their environment securely and reliably by processing and reasoning the data received. Based on the multiagent system, a prototype was developed to monitor patients in their home. The HoCCAC multiagent system uses a critical path method-based planning model that, in the present study, prepares the most optimal task-planning schedule for the patients in their home, is capable of reacting automatically when faced with dangerous or emergency situations, replanning any plans in progress and sending alert messages to the system. The results obtained with this prototype are presented in this article.     

Modeling the user state for context-aware spoken interaction in ambient assisted living

Ambient Assisted Living (AAL) systems must provide adapted services easily accessible by a wide variety of users. This can only be possible if the communication between the user and the system is carried out through an interface that is simple, rapid, effective, and robust. Natural language interfaces such as dialog systems fulfill these requisites, as they are based on a spoken conversation that resembles human communication. In this paper, we enhance systems interacting in AAL domains by means of incorporating context-aware conversational agents that consider the external context of the interaction and predict the user’s state. The user’s state is built on the basis of their emotional state and intention, and it is recognized by means of a module conceived as an intermediate phase between natural language understanding and dialog management in the architecture of the conversational agent. This prediction, carried out for each user turn in the dialog, makes it possible to adapt the system dynamically to the user’s needs. We have evaluated our proposal developing a context-aware system adapted to patients suffering from chronic pulmonary diseases, and provide a detailed discussion of the positive influence of our proposal in the success of the interaction, the information and services provided, as well as the perceived quality.     

Usability study of ME2.0

Mobile context-aware applications execute in the background of hosts mobile devices. The applications source process and aggregate hosts’ contextual and personal information. This information is disclosed to ubiquitously pervasive services that adapt their offerings to individual preferences. Unfortunately, many developers continue to ignore the user perspective in context-aware application designs as they complicate their overall task and generate exponential requirements. The additional incorporation of privacy mechanisms in context-aware applications to safeguard context and personal information disclosures also complicates users’ tasks resulting to misconfigured or completely abandoned applications. Misconfigured applications give end-users a false assurance of privacy exposing them to comprising services. We present a usability study on Mobile Electronic Personality Version 2 a privacy enhanced context-aware mobile application for personalising ubiquitous services and adapting pervasive smart-spaces. We draw conclusions on key issues related to user needs, based on user interviews, surveys, prototypes and field evaluations. Users’ needs are evaluated against five themes, learn-ability, efficiency, memorability, errors, satisfaction and privacy contention. In addition, design layout preferences, privacy manageability and consensus design comprehension are also evaluated. Clarity of priorities in context-aware mobile applications shaped by usability studies effectively increases the acceptance of levels of potential users.     

基于Parlay的状态感知通信业务技术及实现

提出了综合上下文感知技术和融合网络通信技术的下一代网络新业务——状态感知通信业务。讨论了基于遍布计算的网络层状态感知技术以及基于Parlay API的应用层状态感知技术,综合这两层状态感知技术提出了状态感知通信系统的结构和控制流程,并给出了应用示例。