Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> The article describes an active map service (AMS) that supports context-aware computing by providing clients with information about located-objects and how those objects change over time. The authors focus on the communication issues of disseminating information from an active map server to its clients, and in particular, address how to deal with various overload situations that can occur. Simple unicast callbacks to interested clients work well enough if only a few located-objects are moving at any given time and only a few clients wish to know about any given move. However, if many people are moving about in the same region and many clients are interested in their motion, then the AMS may experience overload due to the quadratic nature of the communications involved. This overload affects both the server as well as any slow communications links being used. Mobile distributed computing enables users to interact with many different mobile and stationary computers over the course of the day. Navigating a mobile environment can be aided by active maps that describe the location and characteristics of objects within some region as they change over time. > <s> BIB001 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> Current hardware developments are making mobile computing increasingly attractive. An important class of mobile applications are context-aware applications: applications that change their behaviour according to the user's present context-their location, who they are with, what the time of day is, and so on. This article is about software design for context-aware applications. Currently most such applications have been crafted by experts in research laboratories. Our aim is to factor out a simple class of context-aware applications and make the creation of these as easy as, say, creating Web pages. <s> BIB002 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> The last five years has seen a shift in the nature of mobile computers. The development of increasingly powerful laptop computer systems has been mirrored by the production of a range of small computational devices. The increased prominence of these devices outlined a number of distinct research challenges. These challenges have tended to focus on extending the utility of these devices using new forms of interaction; techniques to overcome display limitations or improvements in the general ergonomics of these devices. The merging of these devices with existing telecommunication services and the production of devices that offer connections to other systems presents yet another set of research challenges in terms of the development of cooperative multi-user applications. <s> BIB003 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> As computing technology continues to become increasingly pervasive and ubiquitous, we envision the development of environments that can sense what we are doing and support our daily activities. In this article, we outline our efforts toward building such environments and discuss the importance of a sensing and signal-understanding infrastructure that leads to awareness of what is happening in an environment and how it can best be supported. Such an infrastructure supports both high- and low-end data transmission and processing, while allowing for detailed interpretation, modeling and recognition from sensed information. We are currently prototyping several aware environments to aid in the development and study of such sensing and computation in real-world settings. <s> BIB004 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> Context-aware computing is a mobile computing paradigm in which applications can discover and take advantage of contextual information (such as user location, time of day, nearby people and devices, and user activity). Since it was proposed about a decade ago, many researchers have studied this topic and built several context-aware applications to demonstrate the usefulness of this new technology. Context-aware applications (or the system infrastructure to support them), however, have never been widely available to everyday users. In this survey of research on context-aware systems and applications, we looked in depth at the types of context used and models of context information, at systems that support collecting and disseminating context, and at applications that adapt to the changing context. Through this survey, it is clear that context-aware research is an old but rich area for research. The difficulties and possible solutions we outline serve as guidance for researchers hoping to make context-aware computing a reality. <s> BIB005 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> A device for detaching a sheet-shaped copy support from a moving photoconductive layer by fluid pressure. The device includes a nozzle arrangement which directs pressurized fluid, such as compressed air, toward a sheet of copy paper or other copy support. The action of the fluid on the copy support creates a suction pressure which draws the copy support toward the nozzle arrangement to detach the copy support from the photoconductive layer. When the copy support has moved into close proximity and generally overlying relationship with respect to the nozzle arrangement, the fluid is passed off generally tangentially with respect to the copy support to maintain a constant suction and to avoid undesirable oscillations of the copy support. This, in turn, eliminates the undesirable noise associated with such oscillations. <s> BIB006 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> Context and context-awareness provides computing environments with the ability to usefully adapt the services or information they provide. It is the ability to implicitly sense and automatically derive the user needs that separates context-aware applications from traditionally designed applications, and this makes them more attentive, responsive, and aware of their user's identity, and their user's environment. This paper argues that context-aware applications capable of supporting complex, cognitive activities can be built from a model of context called Activity-Centric context. A conceptual model of Activity-Centric context is presented. The model is illustrated via a detailed example. <s> BIB007 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> As computing becomes more pervasive, the nature of applications must change accordingly. In particular, applications must become more flexible in order to respond to highly dynamic computing environments, and more autonomous, to reflect the growing ratio of applications to users and the corresponding decline in the attention a user can devote ::: to each. That is, applications must become more context-aware. To facilitate the programming of such applications, infrastructure is required to gather, manage, and disseminate context information to applications. This paper is concerned with the development of appropriate context modeling concepts for pervasive computing, which can form the basis for such a context management infrastructure. This model overcomes prob- ::: lems associated with previous context models, including their lack of formality and generality, and also tackles issues such as wide variations in information quality, the existence of complex relationships amongst context information and temporal aspects of context. <s> BIB008 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context data and adapting systems behaviour accordingly. Especially in combination with mobile devices, these mechanisms are of high value and are used to increase usability tremendously. In this paper, we present common architecture principles of context-aware systems and derive a layered conceptual design framework to explain the different elements common to most context-aware architectures. Based on these design principles, we introduce various existing context-aware systems focusing on context-aware middleware and frameworks, which ease the development of context-aware applications. We discuss various approaches and analyse important aspects in context-aware computing on the basis of the presented systems. <s> BIB009 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> Improving the quality of healthcare and the prospects of "aging in place" using wireless sensor technology requires solving difficult problems in scale, energy management, data access, security, and privacy. We present AlarmNet, a novel system for assisted living and residential monitoring that uses a two-way flow of data and analysis between the front- and back-ends to enable context-aware protocols that are tailored to residents' individual patterns of living. AlarmNet integrates environmental, physiological, and activity sensors in a scalable heterogeneous architecture. The SenQ query protocol provides real-time access to data and lightweight in-network processing. Circadian activity rhythm analysis learns resident activity patterns and feeds them back into the network to aid context-aware power management and dynamic privacy policies. <s> BIB010 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> Today's mobile phones represent a rich and powerful computing platform, given their sensing, processing and communication capabilities. Phones are also part of the everyday life of billions of people, and therefore represent an exceptionally suitable tool for conducting social and psychological experiments in an unobtrusive way. de the ability of sensing individual emotions as well as activities, verbal and proximity interactions among members of social groups. Moreover, the system is programmable by means of a declarative language that can be used to express adaptive rules to improve power saving. We evaluate a system prototype on Nokia Symbian phones by means of several small-scale experiments aimed at testing performance in terms of accuracy and power consumption. Finally, we present the results of real deployment where we study participants emotions and interactions. We cross-validate our measurements with the results obtained through questionnaires filled by the users, and the results presented in social psychological studies using traditional methods. In particular, we show how speakers and participants' emotions can be automatically detected by means of classifiers running locally on off-the-shelf mobile phones, and how speaking and interactions can be correlated with activity and location measures. <s> BIB011 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> This paper addresses the Internet of Things. Main enabling factor of this promising paradigm is the integration of several technologies and communications solutions. Identification and tracking technologies, wired and wireless sensor and actuator networks, enhanced communication protocols (shared with the Next Generation Internet), and distributed intelligence for smart objects are just the most relevant. As one can easily imagine, any serious contribution to the advance of the Internet of Things must necessarily be the result of synergetic activities conducted in different fields of knowledge, such as telecommunications, informatics, electronics and social science. In such a complex scenario, this survey is directed to those who want to approach this complex discipline and contribute to its development. Different visions of this Internet of Things paradigm are reported and enabling technologies reviewed. What emerges is that still major issues shall be faced by the research community. The most relevant among them are addressed in details. <s> BIB012 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> Many applications in vehicular networks are context-aware in that the observations of sensing nodes, potentially vehicles, at a target location should be made available to the requesting node possibly at a different location. In order to provision such applications, two phases of packet routing between the requesting node and the target location and packet dissemination within the target location need to be implemented. In this paper, we focus on the second phase and propose an efficient reliable packet dissemination mechanism, Request-adaptive Packet Dissemination Mechanism (RPDM), in target location. RPDM allows for different applications to generate request packets based on their exclusive observation needs and delay requirements and adapts the dissemination mechanism in target location to specific needs of the request packet received. Besides, RPDM also takes the intrinsic characteristics of vehicular environments into account to make sure roadmap and connectivity constraints are considered and broadcast storm is prevented. Finally, RPDM is compared with a best-known state-of-the-art data dissemination mechanism, COR, and the results show that RPDM outperforms COR in terms of both resolution time and packet overhead traffic. <s> BIB013 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> Recommender systems have been researched extensively by the Technology Enhanced Learning (TEL) community during the last decade. By identifying suitable resources from a potentially overwhelming variety of choices, such systems offer a promising approach to facilitate both learning and teaching tasks. As learning is taking place in extremely diverse and rich environments, the incorporation of contextual information about the user in the recommendation process has attracted major interest. Such contextualization is researched as a paradigm for building intelligent systems that can better predict and anticipate the needs of users, and act more efficiently in response to their behavior. In this paper, we try to assess the degree to which current work in TEL recommender systems has achieved this, as well as outline areas in which further work is needed. First, we present a context framework that identifies relevant context dimensions for TEL applications. Then, we present an analysis of existing TEL recommender systems along these dimensions. Finally, based on our survey results, we outline topics on which further research is needed. <s> BIB014 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT. <s> BIB015 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> During the last years, a continuous convergence and fusion of computing and networking systems is stressed in the ICT research community. Context awareness appears to be a major research "glue-point" of such kind of heterogeneous environments' integration. In this survey paper, we aim to assemble all the "puzzle-pieces" of the emerging research area of Context Aware Mobile and Wireless Networking (CAMoWiN) in order to provide the reader a holistic representation of the work having been done in the past emphasizing in recent research efforts. A precise definition of abstract Context Aware (CA) functionalities together with a clear classification of related state-of-the-art proposals are provided in the form of a proposed taxonomy scheme per CA functionality. Each taxonomy scheme can also serve as a sufficiently general framework permitting the easy classification of novel CAMoWiN solutions emerging in the near future. Therefore, our study not only defines all the possible components of a CAMoWiN architecture and clearly points out the similarities and differences of all research efforts in the field but also evaluates future research trends and paves the way for the researchers to work beyond the concepts investigated in this work. Finally, apart from identifying the open challenges, which arise when applying traditional concepts of pervasive computing to mobile and wireless networks, we further map them to the Mobile Cloud Computing paradigm, whose concepts appear to be very promising regarding next generation networking and computing environments' integration. <s> BIB016 </s> Context-Awareness for Mobile Sensing: A Survey and Future Directions <s> I. INTRODUCTION <s> The Internet of Things and the advent of cloud computing promotes a global scale Machine-to-Machine (M2M) communication. Dissemination of information and advertising services to the targeted nodes is an important aspect in the performance of the future large scale network systems. With the contextual information inferred from available information, delivery of services can be performed in a more efficient way. Context-awareness is a key ingredient in any ubiquitous and pervasive system and provides intelligence to the system, allowing computing devices make appropriate and timely decisions on behalf of users. Semantic support for M2M communication can be enhanced if it leverages the available information and contextual data. In this paper we present a methodology for a context-aware publish-subscribe based approach to dissemination of information and services and a service selection method which is based on the idea of utilizing network information as services that is delivered via application programming interfaces. We propose a fuzzy MADM method and a context similarity measure. The proposed method of information dissemination is based on mining the value of a node based on information inferred from the contextual information of the node and contextually similar nodes. We take into account the quality of contextual information in aggregating contextual information from different sources. <s> BIB017
T HE continual development of sensor designs and deployment together with ever-increasing computing technologies in mobile device based embedded systems platforms have enabled to pervasively recognize the individual and social context that device users touch with. Hence, the inference of daily Ö. Yürür was with the Department of Electrical Engineering, University of South Florida, Tampa, FL 33620-5399 USA. He is now with RF Micro Devices, Greensboro, NC 27409 USA (e-mail: oyurur@mail.usf.edu). C. H. Liu is with the School of Software, Beijing Institute of Technology, Beijing 100181, China (e-mail: chiliu@bit.edu.cn). Z. Sheng is with the School of Engineering and Informatics, University of Sussex, Brighton BN1 9RH, U.K. (e-mail: z.sheng@ieee.org). V. C. M. Leung is with the Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada (e-mail: vleung@ece.ubc.ca). W. Moreno is with the Department of Electrical Engineering, University of South Florida, Tampa, FL 33620-5399 USA (e-mail: wmoreno@usf.edu). K. K. Leung is with the Department of Electrical and Electronic Engineering, Imperial College, London SW7 2BT, U.K. (e-mail: kin.leung@imperial.ac.uk). Digital Object Identifier 10.1109/COMST.2014.2381246 occurring human-centric actions, activities and interactions by a set of mobile device based sensors has drawn much interest in the research area of ubiquitous sensing community. BIB010 It is believed that introducing intelligence and situational awareness into recognition process of human-centric event patterns could give a better understanding of human behaviors, and it also could give a chance for proactively assisting individuals to enhance the quality of lives BIB010 , BIB011 . Ubiquitous sensing was firstly envisioned by Weiser  as in providing the right information to the right person at the right time through an effective kind of technology via physical environment, yet making the relevant computing elements and inter-communication invisible to the user. Then, the term of context-awareness firstly used in BIB001 where the ability of a mobile user's applications to discover and react to changes in the environment they are situated in. Also, the definition of context or context-awareness were simplified and generalized first by  , and later by BIB006 as in any information that can be used to characterize the situation of an entity, where an entity can be a person, place, or physical or computational object. In the latter, the complexity of context-awareness were linked with individual user activities by BIB007 , and also were modeled in BIB008 . In addition, use of context-awareness within mobile sensing, and within the concept of smart spaces was introduced in BIB003 - BIB004 respectively. Earlier attempts of context-aware applications were also presented in BIB002 . Since then, the envisioned interaction between smart devices and users has become possible today and inevitable for future technologies. Therefore, the ubiquitous sensing has led to increase the demand for novel applications and services to provide any interested context at anytime and from anywhere. The integration of sensing and advanced computing capability in network enabled mobile devices will produce sensory data and exchange information among local or system-wide resources by feeding the Internet at a social scale BIB017 , BIB013 . This situation will emerge the concept of the Internet-of-Things (IoT, BIB012 ,  ) to shift into a collection of autonomous, ambient intelligent and self-operated network nodes (e.g., independently acting smartphones) which are well aware of surrounding context, circumstances and environments. With these capabilities, the new network architecture would enhance data credibility, quality, privacy and share-ability by encouraging participation at personal, social and urban scales. It would also lead to discover the knowledge about human lives and behaviors, and environment interactions/social connections by leveraging the deployment capacity of smart things (e.g., smartphones, tablets) in order to collect and analyze the digital traces left by users. It is well known that recognition of a human behavior highly depends on perception, context, environment and prior knowledge of most recent event patterns. In other words, the understanding of human activity is based on the discovery of an activity pattern and accurate recognition of the activity itself. Therefore, researchers have focused on implementing computationally pervasive systems in order to create high-level conceptual models to infer activities, and low-level sensory models to extract context from unknown activity patterns. At this point, the creation of a generic model to represent the true nature of human behavior stands as a major challenge. In this aspect, the construction of a framework by distinct middleware technologies have been put forward to provide the required model for recognition of daily occurring human activities via observations acquired by various sensors built-in smartphones. These activities are inferred as outcomes of a wide range of sensory applications utilized in such diverse implementation areas ranging from environmental surveillance, assisting technologies for medical diagnosis/treatments, to the creation of smart spaces for individual behavior modeling. The key challenges that are faced in this concept is to infer relevant activities in such a system that takes raw sensor readings initially and processes them until obtaining a semantic outcome under some constrictions. These constrictions mostly stem from the difficulty of shaping exact topological structure, and also stem from modeling uncertainties in the observed data due to saving the energy wasted during physical sensor operations and process of sensory data. Today's mobile devices have been becoming increasingly sophisticated, and the latest versions are now equipped with a rich set of powerful small size built-in sensors such as accelerometers, ambient light sensors, GPS, 2 magnetic compass, and Wi-Fi. BIB011 These sensors can measure various information belonging to physical world surrounding the mobile device; thereby, ubiquitously use of mobile devices in the society creates a new exciting research area for sensory data mining context-aware applications. Specifically, smartphones could provide a large number of applications within the defined research area. Since human beings are involved in a vast variety of activities within very diverse contexts along with the usage of mobile phones are getting more integrated into human lives throughout the day, a specific context, whose relevant data is acquired through built-in sensors can be extracted by a smartphone application. Eventually, a desired information within the context is inferred by successful computing implementations. Context-aware sensing applications can be classified under two different categories: personal/human-centric and urban including participatory/community/group or opportunistic.  In personal sensing applications, device user is the point of interest. For instance, monitoring and recognition of user related posture and movement patterns for personal fitness log or for health care reasons is an active research topic in this field. On the other hand, participatory sensing relies on multiple deployment of mobile devices to interactively and intentionally share, gather and analyze of each local knowledge that is not solely based on a human activity, but also based on surrounding environment. Hence, participatory sensing requires the active participation of each user into collecting of sensory data in order to result in a large-scale phenomena, which cannot be easily measured by a single participation. For example, delivering an intelligent traffic congestion report in case where many users provide their speed and location information while being in a transportation is a great example of implementation in participatory sensing. On the other hand, unlike participatory sensing, opportunistic sensing accepts sensory data collection in a fully autonomous way without active user interaction. This type of applications runs in background mode without any user intervention in actual sensing, such as continuous location notification or ambient sound recognition. In summary, the generic idea of all possible sensing applications is to orchestrate the increasing capabilities of mobile devices (e.g., computing, communication and networking, and sensing) through a running software on an existing hardware platform at a right time and place in order to enable services to infer meaningful information for the benefit of individual and community use. Besides the exciting development of context-aware applications, middleware systems/services in smart devices, however, only have very limited resources in terms of power, memory and bandwidth as compared to the capabilities of PCs and servers. Especially, energy efficiency is a major restriction imposed on context-aware application developments since the extraction and inference of user relevant sensory data requires continuous sensor operations. This requirement unfortunately shortens the device battery lifetime due to high energy consumption required by both sensor and processor operations. One solution is to take precautions on sensory operations while putting them into more sleeping mode to reduce power consumption. However, it turns into an accuracy problem that middleware services may produce while providing information to applications. This situation triggers the research topic of finding optimal solutions to balance a trade-off existing between power consumption and sensory data accuracy. Hence, the key goal lies under discovering the best characteristics of the target complex spatial phenomenon being sensed, meeting the demands of application, and satisfying the constraints on sensor usage. Toward this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-todate research and future research directions. There are some successful surveys in the literature that take the phenomena of context-awareness in different perspectives. These works mostly consider the high-level (abstract) contextual information as a basis, and builds up the survey around it by introducing modeling schemes, types of applications, and their relations to different research areas. Accordingly,  surveys sensor utilization in mobile sensing, and types of context-aware application based on their sensing scales, such as within individual or large groups. It also gives information about mobile phone sensing architecture, and use of it as an sensing instrumentation. Finally, it discusses challenges faced in system architecture while sensing, learning and distributing high-level context. BIB009 presents a detailed explanation of context, context types along with sensor types. Then, it continues with context modeling. Also, it covers architectural design principles and models to implement context-aware systems, and conceptual framework design for context processing. BIB005 looks in depth at the types and modeling of context. It also browses applications and architectural models that adapt to changing context.  examines a category of applications implemented for crowdsensing by explaining their unique characteristics and challenges faced in design process.  discusses requirements set by context modeling and reasoning techniques. Also, it shows a variety of context information types with a comparison analysis, and high-level context abstractions in the existence of uncertainty. BIB015 highlights context-awareness from an IoT perspective, and presents the background of IoT paradigm, context-aware essentials and their relations to sensor networks. The work also points out the principles of context-aware management design by surveying a broad range of techniques, methods, models, functionalities, and applications related to abstract layer based context-awareness and IoT. BIB014 ,  survey context-awareness for recommender systems to build such intelligent systems that can better predict and anticipate the needs of users, and act more efficiently in response to their behaviors. The surveys explore contexts, context types and context modeling in the recommender systems, and defines future challenges to be faced in this research area. BIB016 takes context-awareness in a scope of mobile and wireless networking. It surveys traditional contextaware computing areas, and makes a connection between them with mobile and wireless networking notions. It defines the functionality of context-awareness in this term, and puts them in a precise taxonomy scheme. This paper differs from other studies since it surveys contextawareness in mobile platforms by pointing out and proposing solutions to the challenges in terms of recognition process of both low and high level context. More specifically, the paper aims at enlightening possible solutions to enhance the existing tradeoffs in mobile sensing, especially between accuracy and power consumption, while context is being inferred under the intrinsic constraints of mobile devices and around the emerging concepts in context-aware middleware framework. In addition, the paper provides an overview of context-awareness in ubiquitous/mobile sensing, and a comprehensive introduction to the definition, representation and inference of context. However, unlike other surveys, this paper does not extensively cover basic definitions and essentials in context-awareness. Also, this paper not only intends to summarize and itemize some important works done under a specific research branch of context-awareness, but also it gives a detailed view and current trends in this branch by evaluating works and investigating further evolvement. In this sense, it categorizes and gives an inside-out look into context-aware applications depending on the interested context under the limitation of mobile sensing, and then identifies opportunities in the covered research areas. Moreover, the paper exposes the key elements that modern context-aware middleware and framework designs must have, and their connections to mobile computing. Apart from clearly pointing out the similarities and differences of all research efforts, and identifying the open challenges, it also evaluates future research trends and paves the way for the researchers to see emerging concepts in the defined research area. Finally, the content and the flow of the paper always intend to seek for motivation, identification of drawbacks and road-map to possible solutions of the covered topics, eventually summarize and present findings by projecting the future. The remainder of this paper is organized as follows. Section II introduces the definition of context, context presentation and stages to context inference problem along with context modeling. This section also exposes the context-aware middleware and framework designs, and their key properties. Section III summarizes significant context-aware application domains, and categorizes them under the interested context. Section VIII puts emphasis on the challenges that are faced in context-awareness and system integration around this research topic, and evaluates possible solutions. Finally, conclusion is given in Section V.