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A service‐oriented middleware for building context‐aware services
Abstract
The advancement of wireless networks and mobile computing necessitates more advanced applications and services to be built with context-awareness enabled and adaptability to their changing contexts. Today, building context-aware services is a complex task due to the lack of an adequate infrastructure support in pervasive computing environments. In this article, we propose a Service-Oriented Context-Aware Middleware (SOCAM) architecture for the building and rapid prototyping of context-aware services. It provides efficient support for acquiring, discovering, interpreting and accessing various contexts to build context-aware services. We also propose a formal context model based on ontology using Web Ontology Language to address issues including semantic representation, context reasoning, context classification and dependency. We describe our context model and the middleware architecture, and present a performance study for our prototype in a smart home environment.
... 进一步地,给定一个 duration 的集合 D 及其两个元素: 1 给定一个实数集合 , R ⊂ 以及 R 中的任意一对实数 1 2 , , r r 我们称 1 2 , r r 在 R 中是互连的(r 1 connects_with r 2 ),当且仅当 1 = ⊗ = ⊕ = 定义 2(规范 Duration 集合(normal formed duration set,简称 NFDS)). 一个 duration 集合 D 被称为"规范 的(normal formed)"当且仅当(1) 其元素个数小于 2(即 2 D < );或(2) 当 2 D ≥ 时,其任意两个不同元素彼此互 不相连,即 ( ) [5,7]} 都是 NFDS,而 { [1,4], [5,9]}, {(2,6), [7,11]}, D D = = 则 ( ) , , , , , , , , , [8,10], [9,11] , , , , [9,10) . ce ce C ce C ∀ , ∈ ⇔ ∈ ; 1 ...
... 进一步地,给定一个 duration 的集合 D 及其两个元素: 1 给定一个实数集合 , R ⊂ 以及 R 中的任意一对实数 1 2 , , r r 我们称 1 2 , r r 在 R 中是互连的(r 1 connects_with r 2 ),当且仅当 1 = ⊗ = ⊕ = 定义 2(规范 Duration 集合(normal formed duration set,简称 NFDS)). 一个 duration 集合 D 被称为"规范 的(normal formed)"当且仅当(1) 其元素个数小于 2(即 2 D < );或(2) 当 2 D ≥ 时,其任意两个不同元素彼此互 不相连,即 ( ) [5,7]} 都是 NFDS,而 { [1,4], [5,9]}, {(2,6), [7,11]}, D D = = 则 ( ) , , , , , , , , , [8,10], [9,11] , , , , [9,10) . ce ce C ce C ∀ , ∈ ⇔ ∈ ; 1 ...
... 基于上一节给出的 NFDS 的定义,我们在此也给出一个规范上下文的定义如下: [8,11] , , , , [9,10) . 两个上下文的"并(union)"为它们的最小公共(规范)超上下文,即包括这两个上下文所有条目(entry)的上下 文的规范形式: 2 1 3 1 11 2 2 2 , , , , 1,10 , , , , 10,12 , ...
Context awareness is one of the key characteristics of ubiquitous and pervasive computing. Most current formalism works focus on two aspects: context representing and system modeling. However, how the temporal property of context can be modeled and how context can be manipulated are not well addressed. This paper proposes a formal way based on set theory for modeling and manipulating context, in which a context is defined as a set of context entries and operators are introduced to specify how to manipulate contexts in according to the needs of different applications. To show the usability of the proposed model, a demo implementation is also included in this paper.
... Contextual information models based on ontologies have been explored in several architectures that support context-aware services (e.g. [7,8]). These models allow the cooperation among objects and the discovering, acquisition, inference, and distribution of contextual information. ...
... These systems do not have an open context model because often the context is described in an object-oriented base and so the information is strongly coupled with the programming model. More recently several studies appeared to support context-aware composition of services, one more generic and others dedicated to mobile environments [7,[12][13][14]. In [12] the authors propose a framework for dynamic composition of context-aware mobile services. ...
... However the study does not specifies which approach is used to compose new services. The SOCAM [7] presents a middleware architecture for building rapid context-aware services. It provides support for discovering, acquiring, interpreting and accessing context information. ...
Besides services traditionally available in wireless networks, new ones may be offered that transparently adjust and adapt to the user context. The user would have more choice and flexibility if not only could he use platform and third-party services, but also compose his own services in an ad-hoc way, making it available to other users, involving them collaboratively in the construction of a wide set of services. Moreover, collaboration among users can be fostered by the availability of awareness services in mobile environments that enable them to execute joint tasks and activities. This paper presents iCas, an architecture to create context-aware services on the fly, and discusses its main modules. Also a collaborative application scenario is briefly described.
... All work in this emerged domain research of contextawareness system are based on this definition. This definition resumes the other previous definitions of context given by Schilit and Theimer [4], Brown et al. [14], Ryan and Pascoe [25]. A context is any information that can be used to characterize the situation of an entity. ...
... -Change detection service responsible for the detection of service change and therefore the context change -Security responsible for the verification and control of contextual information. D. Service-Oriented Context Aware Middleware SOCAM [14] SOCAM is a framework of a service oriented context-aware middleware to build context-aware mobile services in an intelligent car. The SOCAM architecture is composed of the following components (see figure 3): ...
... It enables users or applications to locate these services. Figure 4: The SOCAM architecture (extract from [14]). ...
the big needs of disabled and normal users who want to receive the needed information using computational system at anytime and everywhere is now a necessity. The need for services architectures that is aware of the context that to build content adaptation applications that maximize the user satisfaction. The development of context-aware applications should be supported by adequate context information modeling and reasoning techniques. In this paper, we present how to design a conceptually layered framework that supports context aware application to explain the different elements common to most context-aware architectures, but also how a context can be modeled and shared. In this paper we focus on existing work in this research issue in order to determine the different elements common to most context-aware architectures and determine different approaches of modeling context in ubiquitous computing.
... All work in this emerged domain research of contextawareness system are based on this definition. This definition resumes the other previous definitions of context given by Schilit and Theimer [4], Brown et al. [14], Ryan and Pascoe [25]. A context is any information that can be used to characterize the situation of an entity. ...
... -Change detection service responsible for the detection of service change and therefore the context change -Security responsible for the verification and control of contextual information. D. Service-Oriented Context Aware Middleware SOCAM [14] SOCAM is a framework of a service oriented context-aware middleware to build context-aware mobile services in an intelligent car. The SOCAM architecture is composed of the following components (see figure 3): ...
... It enables users or applications to locate these services. Figure 4: The SOCAM architecture (extract from [14]). ...
the big needs of disabled and normal users who want to receive the needed information using computational system at anytime and everywhere is now a necessity. The need for services architectures that is aware of the context that to build content adaptation applications that maximize the user satisfaction. The development of context-aware applications should be supported by adequate context information modeling and reasoning techniques. In this paper, we present how to design a conceptually layered framework that supports context aware application to explain the different elements common to most context-aware architectures, but also how a context can be modeled and shared. In this paper we focus on existing work in this research issue in order to determine the different elements common to most context-aware architectures and determine different approaches of modeling context in ubiquitous computing.
... Bayesian Networks (BN) and Gene Expression Programming (GEP) are two models for time series forecasting. The BN is based on probabilities, and the estimation of probabilistic relationships is based on Bayes' theorem in this model (Gu et al., 2005), and GEP is based on the Genetic Algorithm and Mathematical Equations (Ferreira 2006). The BN model is appropriate in determination of the conditional probabilities between cause and effect relationships in the absence of enough observed data (Pearl, 1988). ...
... In this algorithm, the estimation of probabilistic relationships is based on the Bayes' theorem introduced by Thomas Bayes (Gu et al., 2005) as in Eq. (1): ...
Forecasting Urban Water Consumption (UWC) has a significant impress in efficient urban water management in rapidly growing cities in arid regions. Enhancing forecasting accuracy of UWC using novel models is a crucial requirement in order to the management of smart cities. In this study, Bayesian Networks (BN) is developed as a probabilistic model and compared to Gene Expression Programming (GEP) model as an evolutionary algorithm for forecasting UWC. The amount of current water consumption predicts future water consumption. The scenario with sunshine hours was added to the parameter set as the best scenario in both BN and GEP models based on comparison of Root Mean Square Error (0.11, 0.16), Mean Absolute Relative Error (0.02, 0.05), Max Root Error (0.26, 0.26), and Coefficient of determination (0.8, 0.7), respectively. The outcomes indicate that the BN model provided a more desirable efficiency compared to the GEP model. Furthermore, it can be concluded that the sunshine hour has a considerable influence on UWC, and the ability of the BN model is greatly enhanced by adding this predictor to forecast UWC in a city in an arid region with rapid population growth.
... Next, the author discusses a different approach to the implementation of context-aware applications. The first application to use semantic language and ontology was developed by Gu et al. [32]. This work focused on tracking activity context through software sensors. ...
... Next came the invention of software sensors [32], [33] and applications based on semantic language and ontologies [34]- [37] which made sure that activity context was sensed. These systems were able to attach knowledge and interpretation to the sensed data. ...
The hunt to categorize context-aware applications has been a prevalent issue to developers of context-aware applications. The previous categorizations were based on the functions of the applications. These mechanisms yielded limited results since many applications could not be categorized. This paper categorizes applications into four generations based on developmental trends through a literature survey. The first generation applications focused on data acquisition and used hardware sensors. The second generation applications focused on knowledge acquisition and used software sensors, semantic language and ontology-based modelling languages. The third generation applications focused on intelligent reasoning and used mechanisms to handle information uncertainty. The fourth generation applications deprecate cumbersome ruleset implementations and focus on artificial intelligence whilst taking into consideration the effect of the dynamics of users’ background and preference on contextual information. The study demonstrated that when applications, methods or technologies can be categorized over some time, it is better to classify them into generations.
... Satyanarayanan et al. [28] introduced the emergence of edge computing. Gu et al. [29] proposed a Service-Oriented Context-Aware Middleware (SOCAM) architecture, aiming to solve the context-aware problems of wireless network and mobile computing. Abbs et al. [30] provided the definition of mobile edge computing, its advantages, architecture, application areas, and future directions. ...
... When downloading data from the WoS Core Collection database, the time range was set from 2000 to 2020. However, the first EC-IoT literature retrieved was in 2005 [29]. erefore, the data we used were from 2005 to 2020. ...
In recent years, with the emergence of many Internet of Things applications such as smart homes, smart city, and connected vehicles, the amount of network edge data increases rapidly. Now, edge computing for Internet of Things has attracted the research interest of many researchers. Then, a thorough analysis of the current body of knowledge in edge computing for Internet of Things is conducive to a comprehensive understanding of the research status and future trends in this field. In this paper, a bibliometric analysis of edge computing for Internet of Things was performed using the Web of Science (WoS) Core Collection dataset. The relevant literature studies published in this field were quantitatively analyzed based on a bibliometric analysis method combined with VOSviewer software, and the development history, research hotspots, and future directions of this field were studied. The research results show that the number of literature studies published in the field of edge computing for Internet of Things is on the rise over time, especially after 2017, and the growth rate is accelerating. China and USA take the lead position in the number of literature studies published. Zhang is the most productive author, and Satyanarayanan is the most influential author. IEEE Access and IEEE Internet of Things Journal are the main journals in this field. Beijing University of Posts Telecommunications has published most literature studies. Research hotspots of edge computing for Internet of Things mainly include specific problem research such as resource management, architecture research, application research, and fusion research of this field with some other fields such as artificial intelligence and 5G.
... There are also approaches to extend existing standards by adding/using context, such as KNX ISO [13]. The need to go beyond context representation to context reasoning, classification and dependency is also recognized [14]. Defining the context (model), that is required for achieving context sensitivity can be difficult as indicated in [5], [3]. ...
... Automatic update of the context model based on the observed changes in environment is a subject of the further research. Another problem under study 14 is how to assure better automatic evaluation and validation of the results to make learning process more autonomous. ...
Highly flexible manufacturing systems require continuous run-time (self-) optimization of processes with respect to various parameters, e.g. efficiency, availability, energy consumption etc. A promising approach for achieving (self-) optimization in manufacturing systems is the usage of the context sensitivity approach. Thereby the Cyber-Physical Systems play an important role as sources of information to achieve context sensitivity. In this paper it is demonstrated how context sensitivity can be used to realize a holistic solution for (self-) optimization of discrete flexible manufacturing systems, by making use of Cyber-Physical System integrated in manufacturing systems/processes. A generic approach for context sensitivity, based on self-learning algorithms, is proposed aiming at a various manufacturing systems. The new solution is propos encompassing run-time context extractor and optimizer. Based on the self-learning module both context extraction and optimizer are continuously learning and improving their performance. The solution is following Service Oriented Architecture principles. The generic solution is developed and then applied to two very different manufacturing processes. This paper proposes a holistic solution to achieve context sensitivity for Flexible Manufacturing Systems, whereby the knowledge created by applying the context sensitivity approach can be used for (self-) optimization of manufacturing processes.
... What is desirable behavior for a mobile phone in a classroom or supermarket differs considerably [44], and a smart office [34] has different information provisioning requirements from a smart hospital [33]. The de-facto stan-dard that emerged were ontology-based approaches [72,151,178] connecting the previous more network-centered notion of context awareness to the established formalisms of the knowledge representation area, in particular, to the description language formalisms [12] in the KL-ONE tradition [19] that constitute the de-facto standard in web ontologies through the web ontology language OWL [85,131]. The advantages of this standardization process are particularly in interoperability: ontologies about a certain domain can be used in any application in the domain [105,137]. ...
... However, representing and reasoning about knowledge within the main areas of context, in particular time and space, is not a focus of standard OWL [203]. Consequently, ontology-based context modeling approaches often additionally leverage logical languages more expressive than OWL [72,151,178], e.g., for representing rules [34] or space and time [151]. Research in the qualitative reasoning area, however, demonstrated that temporal and spatial knowledge can be represented and reasoned about in a tractable manner [155]. ...
With the CoViD-19 pandemic, location awareness technologies have seen renewed interests due to the numerous contact tracking mobile application variants developed, deployed, and discussed. For some, location-aware applications are primarily a producer of geospatial Big Data required for vital geospatial analysis and visualization of the spread of the disease in a state of emergency. For others, comprehensive tracking of citizens constitutes a dangerous violation of fundamental rights. Commercial web-based location-aware applications both collect data and-through spatial analysis and connection to services-provide value to users. This value is what motivates users to share increasingly private and comprehensive data. The willingness of users to share data in return for services has been a key concern with web-based variants of the technology since the beginning. With a focus on two privacy preserving CoViD-19 contact tracking applications, this survey walks through the key steps of developing a privacy preserving context-aware application: from types of applications and business models, through architectures and privacy strategies, to representations.
... In addition, the paper proposes a formal context model based on Web Ontology Language and ontology to address issues such as semantic representation, context reasoning, context classification, and dependency. The context model and middleware architecture are described, as well as the prototype's performance in a smart home environment [27]. ...
... Several techniques in this regard have been presented in the scientific literature. Gu et al. use Web Ontology Language, and knowledge of context [19]. Specifically, their suggested methodology uses Ontology to capture contextual information. ...
The advent of the Internet of Things (IoT) paradigm has led to the construction of technological environments based on device communication. In this scenario, solutions have been developed for the intelligent management of various services, such as those related to Smart Cities. In such a scenario, widespread use is that of Smart Homes, environments that can provide management help and intelligent and tailored services to users. This paper aims to present an Internet of Things-based approach to Smart Home management. The proposed approach, which leverages graph approaches, enables the extraction and processing of contextual data, collected from sensors, and probabilistic approaches able to provide valuable information and autonomous actions. The system training phase is performed using graph approaches, which could represent an increase in Context and Situation Awareness. In the experimental phase, a prototype is used to test the proposed method’s energysaving and ventilation management capabilities, which shows encouraging findings.
... In this manuscript, both the pertinent concepts of context and context awareness are utilized to manage the collected data at the fog node level in an effective manner. Both context and context awareness has been excessively used by several researchers in [21], [22] and [23]. The concept learned from context generation and context processing is utilized as a context instance, and context instances are generated at fog nodes from raw data collected from either vehicles or roadside units. ...
Transportation is considered the fundamental pillarof economic growth in any society. Still, inherent issues likeaccidents, higher fuel consumption, and pollution have pavedthe way for the rise of the intelligent transportation system(ITS), which enables safety and improvement in the existingtransportation system. ITS helps the massive collection of datafrom multiple sources, and this big data needs immediate processing for ascertaining the events. However, prediction accuracycontinues to be low because of the trade-off of accuracy with theimmediate detection of an event, and this limits the performanceof ITS. This paper addresses this issue by proposing a novel IoT-enabled distributed context-aware Fog-cloud architecture, whichimproves the prediction accuracy by utilizing a hybrid CNN(Convolutional Neural Network) deep learning (DL) approach.Each vehicle in the system only has a track of the local knowledge.The nearby fog nodes are enabled to know the global eventsthrough incremental federated learning, which gets updatedcontinuously back and forth with fog and cloud. Experimentsdemonstrated in the paper clearly show that the modified versionof VGGNet for the CNN model outperforms RGB images,delivering an accuracy of more than 95%, which is 3% moreaccurate than the LeNet while using RGB images as input
... It presents a formal model of context that can be shared, reused, extended and combined. As an example; SOCAM [14] (Service Oriented Context-Aware Middleware), COBRA [15] (Context Broken Architecture) are context-aware middleware's that provide specifications and requirements to develop a context-aware system but all offer a weak support of general adaptation service. The advantage of ontologies resides in the semantic description of context information and reasoning technics engines. ...
With the rapid progress of mobile computing technology and network connections, mobile learning has gained significant potential in the field of e-learning and the new teaching approaches[1],Learners are in the center of the learning process and they are provided with adaptive learning experience related to their personal characteristics and educational objectives. In general, adaptation can be done based on the learner profile, learning content, in this paper, we explore anadaptation approach that can be done on the learning environment. In order to provide adapted services for the learner, applications and services should be aware of their contexts and automatically adapt to their changing context-known as context awareness. Context is any information that can be used to characterize the situation of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a learner and an application, including location, time, activities, and the preferences of each entity.
... This paradigm has allowed systems to be enriched with information through sensors in indoor environments that can dynamically control multiple information, aspects, and variables. If filtered and managed appropriately, this information can lead to the further enrichment of knowledge for the management of environments [6], [16]. Among the paradigms for the representation of environments and the management of information effectively are those related to Context-Awareness and Situation Awareness. ...
... SOCAM [33,34] is a service-oriented context-aware middleware for a multipledomain environment. It gathers and converts various domains from which contexts are produced into a single semantic space. ...
Current Internet of Things (IoT) systems concentrate on one domain, such as smart home, university, office, etc., while many entities such as humans and mobile phones are mobile entities, roaming between different IoT domains. Most of the research on context-aware middleware for IoT addresses a specific domain and limited kinds of applications. Realizing the ultimate intelligence and automation in IoT will need a multiple-domain system. The architectural design of a multiple-domain context-aware middleware for IoT and pervasive computing envisages serious challenges, including extensibility of the environment, need for distribution, resource limitation of mobile devices, mobility, and need for unique name allocation, which have not been fully addressed by related studies. This paper proposes the architectural design of a multiple-domain context-aware middleware (CAMID), which uses a distributed two-layer architecture to handle the above issues. CAMID has been developed in Java in two layers, including H-CAMID and L-CAMID. Scenario-based Architecture Analysis Method (SAAM) shows that CAMID satisfies the target quality attributes and outperforms previous multiple-domain solutions. Finally, an experimental evaluation of CAMID shows acceptable response time in a critical scenario.
... Online adaptive learning is widely required in the era of mobile and wearable computing (Song et al. 2014), in which a classifier, generally trained offline, needs to adapt to the personalized features after being delivered to end users. The goal is to serve the end users precisely and smartly (Gu, Pung, and Zhang 2005). ...
Online multi-kernel learning is promising in the era of mobile computing, in which a combined classifier with multiple kernels are offline trained, and online adapts to personalized features for serving the end user precisely and smartly. The online adaptation is mainly carried out at the end-devices, which requires the adaptation algorithms to be light, efficient and accurate. Previous results focused mainly on efficiency. This paper proposes an novel online model adaptation framework for not only efficiency but also optimal online adaptation. At first, an online optimal incremental simplex tableau (IST)algorithm is proposed, which approaches the model adaption by linear programming and produces the optimized model update in each step when a personalized training data is collected.But keeping online optimal in each step is expensive and may cause over-fitting especially when the online data is noisy. A Fast-IST approach is therefore proposed, which measures the deviation between the training data and the current model. It schedules updating only when enough deviation is detected. The efficiency of each update is further enhanced by running IST only limited iterations, which bounds the computation complexity. Theoretical analysis and extensive evaluations show that Fast-IST saves computation cost greatly, while achieving speedy and accurate model adaptation.It provides better model adaptation speed and accuracy while using even lower computing cost than the state-of-the art.
... Gu et al. [24] take advantage of context awareness and Web Ontology Language. In particular, the model that they propose acquires contextual information through Ontology. ...
... • Implicitly: A different approach to represent context is through collecting the relevant data to describe the surrounding environment of the user, such as GPS location or the time of the day [PTG08, GPZ05,HSK09]. This data will then be used directly as the contextual information provided to the recommender. ...
The exponential growth of online services and user data changed how we interact with various services, and how we explore and select new products. Hence, there is a growing need for methods to recommend the appropriate items for each user. In the case of music, it is more important to recommend the right items at the right moment. It has been well documented that the context, i.e. the listening situation of the users, strongly influences their listening preferences. Hence, there has been an increasing attention towards developing recommendation systems. State-of-the-art approaches are sequence-based models aiming at predicting the tracks in the next session using available contextual information. However, these approaches lack interpretability and serve as a hit-or-miss with no room for user involvement. Additionally, few previous approaches focused on studying how the audio content relates to these situational influences, and even to a less extent making use of the audio content in providing contextual recommendations. Hence, these approaches suffer from both lack of interpretability.In this dissertation, we study the potential of using the audio content primarily to disambiguate the listening situations, providing a pathway for interpretable recommendations based on the situation.First, we study the potential listening situations that influence/change the listening preferences of the users. We developed a semi-automated approach to link between the listened tracks and the listening situation using playlist titles as a proxy. Through this approach, we were able to collect datasets of music tracks labelled with their situational use. We proceeded with studying the use of music auto-taggers to identify potential listening situations using the audio content. These studies led to the conclusion that the situational use of a track is highly user-dependent. Hence, we proceeded with extending the music-autotaggers to a user-aware model to make personalized predictions. Our studies showed that including the user in the loop significantly improves the performance of predicting the situations. This user-aware music auto-tagger enabled us to tag a given track through the audio content with potential situational use, according to a given user by leveraging their listening history.Finally, to successfully employ this approach for a recommendation task, we needed a different method to predict the potential current situations of a given user. To this end, we developed a model to predict the situation given the data transmitted from the user's device to the service, and the demographic information of the given user. Our evaluations show that the models can successfully learn to discriminate the potential situations and rank them accordingly. By combining the two model; the auto-tagger and situation predictor, we developed a framework to generate situational sessions in real-time and propose them to the user. This framework provides an alternative pathway to recommending situational sessions, aside from the primary sequential recommendation system deployed by the service, which is both interpretable and addressing the cold-start problem in terms of recommending tracks based on their content.
... However, tasks for context gathering, context handling and reaction to context changes should not be tangled with application business logic because this approach tends to be repetitive and error-prone. Instead, a more promising approach is to delegate those tasks to a contextprovision middleware [29,11,15,17,20,33,22,30] that should support most of the tasks involved in the gathering and manipulation of context information in those heterogeneous, dynamic and distributed environments, unburdening applications of handling contextual information. ...
In this paper, we present OpenCOPI (Open COntext Platform Integration), a Service-Oriented Architecture-based middleware platform that supports the integration of services provided by distinct sources, ranging from services offered by simple systems to more complex services provided by context-provision middleware. OpenCOPI offers selection and composition mechanisms to, respectively, select and compose services provided by different sources, considering applications of both Quality of Service and Quality of Context requirements. It also offers an adaptation mechanism that enables to adapt the application execution due to service failures, service quality fluctuation and user mobility. OpenCOPI allows the definition of applications in a higher abstraction level by the specification of a semantic workflow that contains abstract activities. This paper illustrates the use of OpenCOPI in an application from the Gas & Oil Industry and it also shows the evaluation of the main mechanisms of OpenCOPI: the service selection, composition, adaptation and workflow execution.
... Context awareness technology should be able to complete realtime information collection integrating clear knowledge representation and semantics operation. Through information fusion technology, lowlevel scenario information is combined to generate highlevel information that can be identified by the application, and services are provided actively based on the information retrieved [3][4][5]. ...
Background:
With the continuous expansion of urban scale and the increasing concentration of population, public health crisis has become an important part of urban residents' health management. The outbreak of the COVID-19 pandemic in Wuhan in 2020 has sounded the alarm.
Objective:
With the government at all levels to carry out the construction of urban Internet of things and information internet, the Internet backbone network has been built, deployed a large number of sensors, and collected a large number of urban situation data.
Methods:
In this paper, situational awareness technology is introduced into public health emergency services.
Results:
By constructing ontology, situational data and residents' health data are integrated. Through key technologies such as situational data collection, data fusion and data mining, real-time perception of environmental conditions of public health emergency scene is realized, and situational data fusion and situational information reasoning model are constructed.
Conclusions:
The model is applied to the public health crisis emergency simulation system to verify the effectiveness of the model.
... Yet, they do not provide a system architecture top operationalize this information. Gu et al. (2005) use an ontologybased approach with the help of OWL (Web Ontology Language) to model context. None of the above has been designed for or applied to BPM. ...
Changes in workflow relevant data of business processes at run-time can hinder their completion or impact their profitability as they have been instantiated under different circumstances. The purpose of this paper is to propose a context engine to enhance a business process management (BPM) system's context-awareness. The generic architecture provides the flexibility to configure processes during initialization as well as to adapt running instances at decision gates or during execution due to significant context change. The paper discusses context-awareness as the conceptual background. The technological capabilities of business rules and complex event processing (CEP) are outlined in an architecture design. A reference process is proposed and discussed in an exemplary application. The results provide an improvement over the current situation of static variable instantiation of business processes with local information. The proposed architecture extends the well-known combination of business rules and BPM systems with a context engine based on CEP. The resulting architecture for a BPM system using a context engine is generic in nature and, hence, requires to be contextualized for situated implementations. Implementation success is dependent on the availability of context information and process compensation options. Practitioners receive advice on a reference architecture and technology choices for implementing systems, which can provide and monitor context information for business processes as well as intervene and adapt the execution. Currently, there is no multi-purpose non-proprietary context engine based on CEP or any other technology available for BPM, which facilitates the adaptation of processes at run-time due to changes in context variables. This paper will stimulate a debate between research and practice on suitable design and technology.
... O SOCAM (Service Context-Aware Middleware) [13] é uma infra-estrutura para aplicações dependentes de contexto focada no uso de ontologias para modelar informações de contexto. Quanto à notificação, as aplicações dependentes de contexto são notificadas através de um método de callback. ...
... Henricksen [33] distinguishes context according to source and mutability in (i) sensed context, i.e., data directly collected from sensors, (ii) static context, i.e., immutable data, (iii) profiled context, i.e., data that change infrequently and (iv) derived context, i.e., computed information. Direct and indirect context types are used by [34]. Mei and Easterbrook [35] propose a distinction between objective and cognitive context. ...
The proliferation of smart things and the subsequent emergence of the Internet of Things has motivated the deployment of intelligent spaces that provide automated services to users. Context-awareness refers to the ability of the system to be aware of the virtual and physical environment, allowing more efficient personalization. Context modeling and reasoning are two important aspects of context-aware computing, since they enable the representation of contextual data and inference of high-level, meaningful information. Context-awareness middleware systems integrate context modeling and reasoning, providing abstraction and supporting heterogeneous context streams. In this work, such a context-awareness middleware system is presented, which integrates a proposed context model based on the adaptation and combination of the most prominent context categorization schemata. A hybrid reasoning procedure, which combines multiple techniques, is also proposed and integrated. The proposed system was evaluated in a real-case-scenario cultural space, which supports preventive conservation. The evaluation showed that the proposed system efficiently addressed both conceptual aspects, through means of representation and reasoning, and implementation aspects, through means of performance.
... Context-awareness is a key feature in modern approaches and computer paradigms, such as Pervasive Computing, Smart Cities and the Internet of Things. This feature implies that services and applications must be aware of their changing contexts to automatically adapt their functionality in order to improve the quality of experience (QoE) of its users [16]. Context-awareness requires several components and processes working together with the aim to accomplish the context life cycle, which embraces context acquisition, modelling, reasoning and dissemination [19]. ...
Modern services and applications need to react to changes in their context (e.g. location, memory consumption, number of users) to improve the user’s experience. To obtain this context, a monitoring infrastructure with adequate functionality and quality levels is required. But this monitoring infrastructure needs to react to the context as well, raising the need for context-aware monitoring tools. Provide a generic solution for context-aware monitoring able to effectively react to contextual changes. We have designed CAMA, a service-oriented Context-Aware Monitoring Architecture that can be easily configured, adapted and evolved according to contextual changes. CAMA implements a decoupled architecture and manages a context domain ontology for modelling the inputs, outputs and capabilities of monitoring tools. CAMA has been demonstrated in three real use cases. We have also conducted different evaluations, including an empirical study. The results of the evaluations show that (1) the overhead introduced by the architecture does not degrade the behavior of the system, except in extreme conditions; (2) the use of ontologies is not an impediment for practitioners, even when they have little knowledge about this concept; and (3) the reasoning capabilities of CAMA enable context-aware adaptations. CAMA is a solution useful for both researchers and practitioners. Researchers can use this architecture as a baseline for providing different extensions or implementing new approaches on top of CAMA that require context-aware monitoring. Practitioners may also use CAMA in their projects in order to manage contextual changes in an effective way.
... AmbieAgents [21] • An agent-based infrastructure for delivering context-based information to mobile users in AmbieSense. [22] • A context-aware middleware that adopts service-oriented, and ontology-based approach to enable the rapid prototyping of context-aware mobile services in an intelligent vehicle environment. ...
The Internet of Things is envisioned to provide connectivity and communication between various devices all over the world. Based on the devices and applications involved, the nature of the network formed differs. Thus, an intelligent and holistic ecosystem needs to be created wherein clients, data sources, smart objects, and services can all co-exist and interact with each other. We present Adaptive Ubiquitous Middleware for context-aware IoT ecosystems, which considers the situational context of the applications, devices, or people and the contexts of the network formed and accordingly adapts the behavior of the ecosystem. Adaptive Ubiquitous Middleware is a multi-agent, multi-communication protocol-facilitated middleware that acts as an integration point for applications to access relevant context, share it with other applications, and have relevant services made available via a multi-communication protocol bridge. We also present an optimal service allocation model for a single service class that utilizes available computing resources and achieves a minimum average response time. The system implementation has been evaluated with two use cases to demonstrate its applicability, effectiveness, and generality. The evaluation of optimal service allocation demonstrates the service response is much faster in the proposed model.
... We now describe the components of the SOCAM architecture provided by [14]. The SOCAM architecture consists of the following components: ...
Currently few efficient context aware systems that dynamically adapt business processes to context information exist. This calls for the study of context data that affect business processes at runtime, and also a research on adaptive systems that will dynamically reconfigure a business process at runtime to soot the current context. Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context data and adapting systems behavior accordingly, especially in combination with mobile devices these mechanisms are of high value and are used to increase usability tremendously. Our goal is to develop efficient architectural frameworks for context aware systems for business processes that will respond to changing context by adapting itself to a new context. We propose a hybrid architecture which combines both middleware technologies and web services.
... We now describe the components of the SOCAM architecture provided by [14]. The SOCAM architecture consists of the following components: ...
Currently few efficient context aware systems that dynamically adapt business processes to context information exist. This calls for the study of context data that affect business processes at runtime, and also a research on adaptive systems that will dynamically reconfigure a business process at runtime to soot the current context. Context-aware systems offer entirely new opportunities for application developers and for end users by gathering context data and adapting systems behavior accordingly, especially in combination with mobile devices these mechanisms are of high value and are used to increase usability tremendously. Our goal is to develop efficient architectural frameworks for context aware systems for business processes that will respond to changing context by adapting itself to a new context. We propose a hybrid architecture which combines both middleware technologies and web services.
... A first order logic model is introduced in [27] to express complex rules with context. Several Bayesian approaches [18,25] have also been proposed to model the decision making process. A combined approach is adopted in [5], which employs ontologies and logic rules for representation and makes decisions with Markov Logic Networks. ...
Argumentation-based approaches to decision making have gained considerable research interest, due to their ability to select and justify decisions. In order to make better decisions, context is a key piece of information that needs to be considered. However, most existing argumentation-based models and frameworks have not modelled or reasoned with context explicitly. In this paper, we present a new argumentation-based approach for making context-based and explainable decisions. We propose a graphical representation for modelling decision problems involving varying contexts, Decision Graphs with Context (DGC), and a reasoning mechanism for making context-based decisions which relies on the Assumption-based Argumentation formalism. Based on these constructs, we introduce two types of explanations, argument explanation and context explanation , identifying the reasons for the decisions made from an argument-view and a context-view respectively.
... Firstly, GAIA (Context Infrastructure) [16] is a context-aware service structure that allows a provider to obtain various context information and reason over it. The context provider in the structure of Gaia that collects context and provides the context to applications. ...
Context-aware services are attracting attention of world as the use of web services are rapidly growing. We designed an architecture of context-aware semantic web which provides on demand flexibility and scalability in extracting and mining the research papers from well-known digital libraries i.e. ACM, IEEE and SpringerLink. This paper proposes a context-aware administrations system, which supports programmed revelation and incorporation of setting dependent on Semantic Web administrations. This work has been done using the python programming language with a dedicated library for the semantic web analysis named as "Cubic-Web" on any defined dataset, in our case as we have used a dataset for extracting and studying several publications to measure the impact of context aware semantic web application on the results. We have found the average recall and averge accuracy for all the context aware research journals in our research work. Moreover, as this study is limited journal documents, other future studies can be approached by examining different types of publications using this advance research. An efficient system has been designed considering the parameters of research article meta-data to find out the papers from the web using semantic web technology. Parameters like year of publication, type of publication, number of contributors, evaluation methods and analysis method used in publication. All this data has been extracted using the designed context-aware semantic web technology.
Cloud computing has achieved great commercial success to date, but its associated risks may impede firms from adopting it more effectively. This paper addresses the issue from the perspective of firms that use cloud computing and argues that the modularization of firms’ internal IT systems play an important role in enabling their adoption of cloud services. We performed detailed empirical analyses employing a dataset containing 457 firms classified as small and medium-sized enterprises (SMEs) as well as large enterprises. Our empirical results mainly suggest that internal IT modularity aimed for organization-wide, top-down strategic business transformation can help firms better adopt application-level cloud services regardless of their firm size. Bottom-up non-strategic internal IT modularity siloed in individual projects can foster the use of server-level cloud services for SMEs, but not for large enterprises. Our findings reveal support for the general prior understanding of (a) the negative effect of internal IT expenditure and cloud-based software’s quality and risk concerns on application-level cloud adoption, and (b) the positive effect of perceived benefits of cloud-based software on application-level cloud adoption for both SMEs and large enterprises. Finally, when SMEs develop more custom Web services in house, they tend to adopt fewer server-level cloud services externally. The theoretical development and empirical analysis of the effect of IT modularity and firm size on cloud adoption contribute to our understanding of how firms can be more internally ready to use cloud computing effectively.
The rapid development of information and communication technology (ICT)-based solutions in the field of smart city applications becomes essential to cope with the ever-increasing urbanization requirements globally. These ever-increasing demands pose a great challenge to city infrastructure, particularly smart cities, and thus a sustainable approach is needed for the future smart cities. The ever-increasing service demand of the smart city archetype is prone to monitoring and managing such constrained smart city infrastructures in an effective way and to maintain the QoS (smart applications like transportation, healthcare, road traffic, and other utility services). In this work, the authors envisioned improving the QoS of smart transportation while employing a context-aware computing approach that helps to alleviate fog node data transfer, and a distributed smart transport service (DSTS) model is proposed that manages intelligent vehicles and road traffic of the traditional vehicles in an effective way to improve the QoS of the smart city.
Technological advancements such as information and communication technologies (ICTs), artificial intelligence (AI), internet-of-things (IoT), and the increasing popularity of the smart city and smart living movements during the last couple of decades boosted the developments in the smart home domain. Although the number of smart home related research has been expanding rapidly, there is still a lack of systematic analysis of the evolution of this research domain. This study helps to generate an understanding of the historical vicissitude, state-of-the-art and emerging trends, and the existing smart home research clusters. The study applies a scientometric method to analyse the published scholarly research (n = 17,153) over the last two decades, from 2000 to 2021. The scientometric analysis findings reveal that: Smart home literature has experienced steady growth during the last two decades; Smart home research has mainly clustered around ICT for home automation, home information management, AI for home automation, domestic energy management, IoT for home automation, and home-based healthcare areas; IoT is seen as the most popular technology to realise fully functioning smart homes; Limited evidence exists on the urban perspective and social issues of smart home technology; Smart homes are seen potentially as a strong driver of the smart city agenda.
The advancement of the Internet of Things, big data, and mobile computing leads to the need for smart services that enable the context awareness and the adaptability to their changing contexts. Today, designing a smart service system is a complex task due to the lack of an adequate model support in awareness and pervasive environment. In this paper, we present the concept of a context-aware smart service system and propose a knowledge model for context-aware smart service systems. The proposed model organizes the domain and context-aware knowledge into knowledge components based on the three levels of services: Services, Service system, and Network of service systems. The knowledge model for context-aware smart service systems integrates all the information and knowledge related to smart services, knowledge components, and context awareness that can play a key role for any framework, infrastructure, or applications deploying smart services. In order to demonstrate the approach, two case studies about chatbot as context-aware smart services for customer support are presented.
This article describes the Learning Activities Editor Tool, developed by Escola do Futuro (School of the Future) of the University of São Paulo, in the scope of TidiaAe Project. This design time engine, based in IMS-Learning Design specification, has been developed to conform a set with the player tool, in order to support either teachers which desire a simple planning tool to organize their learning contents or activities for local and delimited applications, or more advanced users which need integrated solutions that can be spread in large scale. The article highlights the multifaceted solution developed to take care of to the variety of detected needs, analyzes the limitations of the IMS-LD specification and points the contributions of this work for the Tidia-Ae Project specifically and to the community of developers of open source e-learning tools.
óThis article describes the integration of an IMS compliant GPL Learning Design engine into the Tidia-Ae Learning Management System. This was done by developing an intermediary component ñ the Course Manager. We conclude that the concept of the intermediary component can be used to allow integration of other tools into Tidia-Ae. Because IMS-LD is a relatively new specification, more work has to be done to
test - and possibly improve - the requisites of IMS-LD based tools.
This paper aims at improving supply chain resilience by applying a model- and event-driven architecture from the crisis management field: the AIC information system which Acquires, Interprets and Contextualizes events. It begins with a literature review on information systems able to process events in order to improve situational awareness within supply chains. It concludes that supply chain managers still lack a decision support system able to access new information in near real time. The paper describes the components of the AIC information system, and the implications for a supply chain use case. By testing the architecture on a pharmaceutical supply chain, we assess the accuracy, cost and speed of the detection of new risks. These works are made possible by the use of several data streams aggregated into a single decision-making platform. This supports the claim for a more connected supply chain. Our contributions make crisis management knowledge available to supply chain management and help improving resilient decision-making in a fast changing context.
As the core layer of the Internet of Things (IoT), middleware bridges the gap between applications and devices to resolve many common IoT issues and enhancing application development. Consequently, developing suitable middleware is the main challenge that covers functionality and required quality to combine heterogeneous hardware and software as the integrated system in the IoT. This survey discusses IoT middleware requirements and challenges, and presents the current state of research in this domain. A technical taxonomy is presented for the IoT middleware according to the abstract and processing approach of data. We focus on discovering similarities and differences by making comparisons and appropriateness studies. Besides, this survey discusses three enabling techniques in detail to present analytically the current research trends on the IoT middleware. In the end, we summarize open issues in IoT middleware. This survey aims to provide guidance for the development and research of middleware in the IoT paradigm.
The advancement of the Internet of things, big data, and mobile computing leads to the need for smart services that enable the context awareness and the adaptability to their changing contexts. Today, designing a smart service system is a complex task due to the lack of an adequate model support in awareness and pervasive environment. In this paper, we present a context-aware knowledge model for smart service systems that organizes the domain and context-aware knowledge into knowledge components based on the three levels of services: Services, Service system and Network of service systems. The context-aware knowledge model for smart service systems integrates all the information and knowledge related to smart services, knowledge components and context awareness that can play a key role for any framework, infrastructure, or applications deploying smart services. To demonstrate the approach, a case study about a chatbot as a smart service for customer support is presented.
Technology can be used to assist people with disabilities in their daily activities. Especially when the users have communication deficiencies, suitable technology and tools can assuage such needs. We envision that context awareness is a potential method suitable to provide services and solutions in the area of Assistive and Augmentative Communication (AAC). In this chapter, the authors give an introduction to context awareness and the state of the art. This is followed with the elaboration on how context awareness can be used in AAC. The Context Aware Remote Monitoring Assistant (CARMA) is presented as an application designed for a care assistant and his patient. A demonstration of a context aware component implemented in the CARMA application is shown in this chapter. An experiment that investigates movement recognition using an accelerometer in a smartphone and the obtained results are presented. This chapter ends with a discussion on challenges, future work and the conclusion.
In health service environments, support to mobility is an important issue, given that the mobility of the medical professionals is inherent to the organizational structure of healthcare entities, such as hospitals and medical centers. The concept of the “Ubiquitous Doctor” refers to a doctor that works anytime, anywhere and uses any computer device. For doing this, the doctor needs support to migrate a work session started on a device to another one, either for convenience (more comfort) or forced (e.g. low battery). This so called ‘session migration’ presents some challenges like preventing from disruption and performing quickly, so the Ubiquitous Doctor’s productivity can be improved. This chapter presents the design and implementation of a context-aware system (middleware services and application) to support the Ubiquitous Doctor, as well as experiments that show that the average migration time represents a low impact on the transition time between medical activities, and an assessment carried out with a group of doctors confirmed the importance of supporting the migration process in order to make it fast and reliable. The doctors also agreed on the importance of using the most convenient device based on context variables like user status and location.
Context-awareness is considered to be the cornerstone technique for developing pervasive computing applications that are flexible, adaptable, and capable of acting autonomously on behalf of the user. However, context-awareness introduces various software engineering challenges. The separation of concerns is a promising approach in the design of the context-aware adaptive processes (CAAPs) where the core logic is designed and implemented separately from the context handling and adaptation logics. In this respect, this chapter presents a conceptual framework for developing CAAPs and software infrastructure for efficient context management that together address the known software engineering challenges and facilitate the design and implementation tasks associated with such context-aware applications.
Context aware services have the ability to utilize information about the user’s context and adapt services to a user’s current situation and needs. In this article the authors consider users’ perceptions of the added value of location awareness and presence information in mobile services. The authors use an experimental design, where stimuli comprising specific bundles of mobile services were presented to groups of respondents. The stimuli showed increasing, manipulated, levels of context-awareness, including location of the user and location and availability of buddies as distinct levels. Their results indicate that simply adding context aware features to mobile services does not necessarily provide added value to users, rather the contrary. The potential added value of insight in buddies’ location and availability is offset by people’s reluctance to share location information with others. Although the average perceived value overall is rather low there exists a substantial minority that does appreciate the added context aware features. High scores on constructs like product involvement, social influence and self-expressiveness characterize this group. The results also show that context aware service bundles with utilitarian elements have a higher perceived value than bundles with hedonic elements. On the basis of the different results some guidelines for designing context aware mobile services are formulated.
Contextual information and Identity Management (IM) is of paramount importance in the growing use of portable mobile devices for sharing information and communication between emergency services in pervasive ad-hoc environments. Mobile Ad-hoc Networks (MANets) play a vital role within such a context. The concept of ubiquitous/pervasive computing is intrinsically tied to wireless communications. Apart from many remote services, proximity services (context-awareness) are also widely available, and people rely on numerous identities to access these services. The inconvenience of these identities creates significant security vulnerability as well as user discomfort, especially from the network and device point of view in MANet environments. The need of displaying only relevant contextual information (CI) with explicit user control arises in energy constraint devices and in dynamic situations. We propose an approach that allows users to define policies dynamically and a ContextRank Algorithm which will detect the usability of CI. The proposed approach is not only efficient in computation but also gives users total control and makes policy specification more expressive. In this Chapter, the authors address the issue of dynamic policy specification, usage of contextual information to facilitate IM and present a User-centered and Context-aware Identity Management (UCIM) framework for MANets.
Context awareness is a key issue for applications within heterogeneous and networked environments. In terms of efficiency and reusability, such applications need to be separated from the problems of context gathering and modeling, but should instead profit from and contribute to cross-application context information. For this purpose, an ontology-based, cross-application context modeling and management service is required to provide appropriate support for the variety of conceivable application scenarios. Although there have been numerous approaches dealing with application-independent context management, none of them sufficiently supports the vision of cross-application context handling. Therefore, this paper presents CroCo, an ontology-based context management service that allows for cross-application context gathering, modeling, and provision. The authors successfully verified and tested the application independency and practicability of this novel concept within three different projects with disparate application scenarios.
Advances in wireless, sensor, mobile and wearable technologies present new challenges for data mining research on providing mobile applications with intelligence. Autonomy and adaptability requirements are the two most important challenges for data mining in this new environment. In this chapter, in order to encourage the researchers on this area, we analyzed the challenges of designing ubiquitous data mining services by examining the issues and problems while paying special attention to context and resource awareness. We focused on the autonomous execution of a data mining algorithm and analyzed the situational factors that influence the quality of the result. Already existing solutions in this area and future directions of research are also covered in this chapter.
Ubiquitous Computing advocates the construction of massively dis- tributed systems that help transform physical spaces into computationally active and intelligent environments. The design of systems and applications in these environments needs to take account of heterogeneous devices, mobile users and rapidly changing contexts. Most importantly, agents in ubiquitous and mobile environments need to be context-aware so that they can adapt themselves to dif- ferent situations. In this paper, we argue that ubiquitous computing environ- ments must provide middleware support for context-awareness. We also pro- pose a middleware that facilitates the development of context-aware agents. The middleware allows agents to acquire contextual information easily, reason about it using different logics and then adapt themselves to changing contexts. An- other key issue in these environments is allowing autonomous, heterogeneous agents to have a common semantic understanding of contextual information. Our middleware tackles this problem by using ontologies to define different types of contextual information. This middleware is part of Gaia, our infrastruc- ture for enabling Smart Spaces.
As mobile and embedded computing devices become more pervasive, it is becoming obvious that the nature of interactions between users and computers must evolve. Applications need to become increasingly autonomous and invisible, by placing greater reliance on knowledge of context and reducing interactions with users. Moreover, applications must cope with highly dynamic environments in which resources, such as network connectivity and software services, frequently vary over time. This paper presents our vision of pervasive computing and enumerates the software engineering challenges involved in realizing this vision. It also evaluates the current state of research and presents an agenda for future investigations in pervasive computing.
sent out by a central facility that addresses a particular receiver unit (beeper) and produces an audible signal. In addition, it may display a number to which the called-party should phone back (some systems allow a vocal message to be conveyed about the call-back number). It is then up to the recipient to use the conventional telephone system to call-back confirming the signal and determine the required action. Although useful in practice there are still circumstances where it is not ideal. For instance, if the called party does not reply the controller has no idea if they: 1) are in an area where the signal does not penetrate 2) have been completely out of the area for some time 3) have been too busy to reply or 4) have misheard or misread the call-back number. Moreover, in the case where there are a number of people who could respond to a crisis situation, it is not known which one is the nearest to the crisis and therefore the most suitable to contact. A `tagging system' does not
The use of context is important in interactive applications. It is par- ticularly important for applications where the user's context is changing rap- idly, such as in both handheld and ubiquitous computing. In order to better un- derstand how we can use context and facilitate the building of context-aware applications, we need to more fully understand what constitutes a context- aware application and what context is. Towards this goal, we have surveyed existing work in context-aware computing. In this paper, we provide an over- view of the results of this survey and, in particular, definitions and categories of context and context-aware. We conclude with recommendations for how this better understanding of context inform a framework for the development of context-aware applications.
This paper proposes a novel method for detecting foreground objects in nonstationary complex environments containing moving background objects. We derive a Bayes decision rule for classification of background and foreground changes based on inter-frame color co-occurrence statistics. An approach to store and fast retrieve color co-occurrence statistics is also established In the proposed method, foreground objects are detected in two steps. First, both foreground and background changes are extracted using background subtraction and temporal differencing. The frequent background changes are then recognized using the Bayes decision rule based on the learned color co-occurrence statistics. Both short-term and longterm strategies to learn the frequent background changes are proposed Experiments have shown promising results in detecting foreground objects from video containing wavering tree branches and flickering screens/water surface. The proposed method has shown better performance as compared with two existing methods.
Computing devices and applications are now used beyond the desktop, in diverse environments, and this trend toward ubiquitous computing is accelerating. One challenge that remains in this emerging research field is the ability to enhance the behavior of any application by informing it of the context of its use. By context, we refer to any information that characterizes a situation related to the interaction between humans, applications and the surrounding environment. Context-aware applications promise richer and easier interaction, but the current state of research in this field is still far removed from that vision. This is due to three main problems: (1) the notion of context is still ill defined; (2) there is a lack of conceptual models and methods to help drive the design of context-aware applications; and (3) no tools are available to jump-start the development of context-aware applications. In this paper, we address these three problems in turn. We first define context, identify categories of contextual information, and characterize context-aware application behavior. Though the full impact of context-aware computing requires understanding very subtle and high-level notions of context, we are focusing our efforts on the pieces of context that can be inferred automatically from sensors in a physical environment. We then present a conceptual framework that separates the acquisition and representation of context from the delivery and reaction to context by a contextaware application. We have built a toolkit, the Context Toolkit, that instantiates this conceptual framework and supports the rapid development of a rich space of context-aware applications. We illustrate the usefulness of the conceptual framework by describing a number of contextaware applications that h...
We present the Cyberguide project, in which we are building prototypes of a mobile context-aware tour guide that provide information to a tourist based on knowledge of position and orientation. We describe features of existing Cyberguide prototypes and discuss research issues that have emerged in our context-aware applications development in a mobile environment. Keywords: Mobile computing applications, contextawareness, location-dependent applications, hand-held devices 1 Introduction The project we report on in this paper, Cyberguide, has as its main focus the rapid prototyping of handheld mobile applications in order to assess the utility of context-awareness in mobile devices. The challenge we are addressing in Cyberguide is how to build mobile applications that make use of the context of the user. Initially, we are concerned with only a small part of the user's context, specifically location and orientation. The application which drives the development of Cyberguide is a that of ...
Ontologies are a key component for building open and dynamic distributed pervasive computing systems in which agents and devices share contextual information. We describe our use of the Web Ontology Language OWL and other tools for building the foundation ontology for the Context Broker Architecture (CoBrA), a new context-aware pervasive computing framework. The current version of the CoBrA ontology models the basic concepts of people, agents, places, and presentation events in an intelligent meeting room environment. It provides a vocabulary of terms for classes and properties suitable for building practical systems that model context in pervasive computing environments. We also describe our ongoing research in developing an OWL inference engine using Flora-2 and in extending the present CoBrA ontology to use the DAML spatial and temporal ontologies.
The Context Toolkit (Dey, Abowd, and Salber, 2001 [this special issue]) is only one of many possible architectures for supporting context-aware applications. In this essay, we look at the tradeoffs involved with a service infrastructure approach to context-aware computing. We describe the advantages that a service infrastructure for context awareness has over other approaches, outline some of the core technical challenges that must be addressed before such an infrastructure can be built, and point out promising research directions for overcoming these challenges.
CoolTown offers a Web model for supporting nomadic users, based on the convergence of Web technology, wireless networks and portable devices. This paper describes how CoolTown ties Web resources to physical objects and places, and how users interact with resources using the information appliances they carry, from laptops to smart watches. Enabling the automatic discovery of URLs from our physical surroundings, and using localized Web servers for directories, we create location-aware but ubiquitous systems. On top of this infrastructure we leverage device connectivity to support communication services.
The Rete Match Algorithm is an efficient method for comparing a large collection of patterns to a large collection of objects. It finds all the objects that match each pattern. The algorithm was developed for use in production system interpreters, and it has been used for systems containing from a few hundred to more than a thousand patterns and objects. This article presents the algorithm in detail. It explains the basic concepts of the algorithm, it describes pattern and object representations that are appropriate for the algorithm, and it describes the operations performed by the pattern matcher.
Service discovery has been drawing much attention from researchers and practitioners. The existing service discovery systems, like SLP, Jini, UPnP and Salutation, provide basic infrastructures where services can announce their presence and users can locate these services across the network. However there are several key issues which are partially solved or have not been well addressed - such as scalability, availability, dynamics and support for multiple matching mechanisms. In this paper, we propose a design for a service locating manager (SLM) system which addresses some of these issues. The SLM system adopts a dynamic hierarchical tree structure and service aggregation for scalability, availability and dynamics, and introduces multiple matching mechanisms which contain an attribute-based and a semantic matching engine. It provides a scalable, distributed, dynamic and robust solution to establish a flexible service discovery architecture. We describe our concepts, architecture and implementation, and present a performance study for our prototype.
Building of context-aware applications in pervasive computing environments faces the difficult problem of dealing with uncertain context information. In this paper, we propose a probability extension to our ontology-based model for representing uncertain contexts; and use Bayesian networks to reason about uncertainty. In addition, the supports of probabilistic markups and Bayesian networks have been incorporated into our contextaware middleware system to enable the building of context-aware services by using various uncertain contexts. We also present our experiences and discussions.
Computing becomes increasingly mobile and pervasive today; these changes imply that applications and services must be aware of and adapt to their changing contexts in highly dynamic environments. Today, building context-aware systems is a complex task due to lack of an appropriate infrastructure support in intelligent environments. A context-aware infrastructure requires an appropriate context model to represent, manipulate and access context information. In this paper, we propose a formal context model based on ontology using OWL to address issues including semantic context representation, context reasoning and knowledge sharing, context classification, context dependency and quality of context. The main benefit of this model is the ability to reason about various contexts. Based on our context model, we also present a Service-Oriented Context-Aware Middleware (SOCAM) architecture for building of context-aware services.
Service discovery has been drawing much attention from researchers and practitioners. The existing service discovery systems, like SLP, Jini, UPnP and Salutation, provide basic infrastructures where services can announce their presence and users can locate these services across the network. However there are several key issues which are partially solved or have not been well addressed - such as scalability, availability, dynamics and support for multiple matching mechanisms. In this paper, we propose a design for a Service Locating Manager (SLM) system which addresses some of these issues. The SLM system adopts a dynamic hierarchical tree structure and service aggregation for scalability, availability and dynamics, and introduces multiple matching mechanisms which contain an attribute-based and a semantic matching engine. It provides a scalable, distributed, dynamic and robust solution to establish a flexible service discovery architecture. We describe our concepts, architecture and implementation, and present a performance study for our prototype.
As mobile and embedded computing devices become more pervasive, it is becoming obvious that the nature of interactions between users and computers must evolve. Applications need to become increasingly autonomous and invisible, by placing greater reliance on knowledge of context and reducing interactions with users. Moreover, applications must cope with highly dynamic environments in which resources, such as network connectivity and software services, frequently vary over time. This paper presents our vision of pervasive computing and enumerates the software engineering challenges involved in realizing this vision. It also evaluates the current state of research and presents an agenda for future investigations in pervasive computing.
Ontologies are set to play a key role in the "Semantic Web", extending syntactic interoperability to semantic interoperability by providing a source of shared and precisely defined terms. DAML+OIL is an ontology language specifically designed for use on the Web; it exploits existing Web standards (XML and RDF), adding the familiar ontological primitives of object oriented and frame based systems, and the formal rigor of a very expressive description logic. The logical basis of the language means that reasoning services can be provided, both to support ontology design and to make DAML+OIL described Web resources more accessible to automated processes.
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 re...
The Context Toolkit (Dey, Salber, and Abowd 2001 [this special issue]) is only one of many possible architectures for supporting context-aware applications. In this essay, we look at the trade-offs involved with a service infrastructure approach to context-aware computing. We describe the advantages that a service infrastructure for contextawareness has over other approaches, outline some of the core technical challenges that must be addressed before such an infrastructure can be built, and point out promising research directions for overcoming these challenges. CONTENTS 1. INTRODUCTION 2. LIBRARIES, FRAMEWORKS, TOOLKITS, AND INFRASTRUCTURES 3. ADVANTAGES TO AN INFRASTRUCTURE APPROACH 3.1. Independence from Hardware, Operating System, and Programming Language 3.2. Improved Capabilities for Maintenance and Evolution 3.3. Sharing of Sensors, Processing Power, Data, and Services 4. CHALLENGES TO BUILDING A CONTEXT-AWARE INFRASTRUCTURE 4.1. Defining Standard Data Formats and Protocols 4...
A middleware for context-aware agents in ubiquitous computing environments Shilit BN. A context-aware system architecture for mobile distributed computing The active badge location system
- Ranganathan A Rh Campbell
- A Hopper
- V Falcao
- Gibbons
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