Context awareness

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Context awareness is a property of mobile devices that is defined complementarily to location awareness. Whereas location may determine how certain processes in a device operate, context may be applied more flexibly with mobile users, especially with users of smart phones. Context awareness originated as a term from ubiquitous computing or as so-called pervasive computing which sought to deal with linking changes in the environment with computer systems, which are otherwise static. The term has also been applied to business theory in relation to Contextual application design and business process management issues.[1]

Qualities of context[edit]

It is common sense to understand that context awareness did not originate in computer science or the organizational learning literature (management literature). The word "context" stems from a study of human "text"; and the idea of "situated cognition," that context changes the interpretation of text, is an idea that goes back many thousand years. One of many examples of recorded ancient analysis of context and interpretation is the writings of the Legalist school of philosophers, who were influential between 500-60 B.C. in China. In Western philosophy, one could easily identify ideas about "context awareness" from Greek epistemology. A search for the words "situated learning" will show that the study of context awareness goes back at least as early as Charles Pierce and other American pragmatics. Linguistics have discussed context awareness as early as the formation of the discipline, as for Roman Jakobson one of the six functions of language was the "referential function" that emphasizes the role of context within which the communicative process takes place.

Context defines some rules of inter-relationship of features in processing any entities as a binding clause.

Various categorizations of context have been proposed in the past. Dey and Abowd (1999)[2] distinguish between the context types location, identity, activity and time. Kaltz et al. (2005)[3] identified the categories user&role, process&task, location, time and device to cover a broad variety of mobile and web scenarios. They emphasize yet for these classical modalities that any optimal categorization depends very much on the application domain and use case. Beyond more advanced modalities may apply when not only single entities are addressed, but also clusters of entities that work in a coherence of context, as e.g. teams at work or also single bearers with a multiplicity of appliances.

Some classical understanding of context in business processes is derived from the definition of AAA applications[4] with the following three categories:

  • Authentication, which means i.e. confirmation of stated identity
  • Authorisation, which means i.e. allowance to accrual or access to location, function, data
  • Accounting, which means i.e. the relation to order context and to accounts for applied labour, granted license, and delivered goods,

these three terms including additionally location and time as stated.

Computer science[edit]

In computer science context awareness refers to the idea that computers can both sense, and react based on their environment. Devices may have information about the circumstances under which they are able to operate and based on rules, or an intelligent stimulus, react accordingly. The term context-awareness in ubiquitous computing was introduced by Schilit (1994).[5][6] Context aware devices may also try to make assumptions about the user's current situation. Dey (2001) define context as "any information that can be used to characterize the situation of an entity." [7]

While the computer science community initially perceived the context as a matter of user location, as Dey discuss,[7] in the last few years this notion has been considered not simply as a state, but part of a process in which users are involved; thus, sophisticated and general context models have been proposed (see survey[8]), to support context-aware applications which use them to (a) adapt interfaces, (b) tailor the set of application-relevant data, (c) increase the precision of information retrieval, (d) discover services, (e) make the user interaction implicit, or (f) build smart environments. For example: a context aware mobile phone may know that it is currently in the meeting room, and that the user has sat down. The phone may conclude that the user is currently in a meeting and reject any unimportant calls.[9]

Context aware systems are concerned with the acquisition of context (e.g. using sensors to perceive a situation), the abstraction and understanding of context (e.g. matching a perceived sensory stimulus to a context), and application behaviour based on the recognized context (e.g. triggering actions based on context).[10] As the user's activity and location are crucial for many applications, context awareness has been focused more deeply in the research fields of location awareness and activity recognition.

Context awareness is regarded as an enabling technology for ubiquitous computing systems. Context awareness is used to design innovative user interfaces, and is often used as a part of ubiquitous and wearable computing. It is also beginning to be felt in the internet with the advent of hybrid search engines. Schmidt, Beigl & Gellersen[11] define human factors and physical environment as two important aspects relating to computer science. More recently, much work has also been done to ease the distribution of context information; Bellavista, Corradi, Fanelli & Foschini survey[12] the several middleware solutions that have been designed to transparently implement context management and provisioning in the mobile system. Perera, Zaslavsky, Christen, & Georgakopoulos[13] have performed a comprehensive survey on context-aware computing from Internet of Things perspective by reviewing over 50 leading projects in the field. Further, Perera has also surveyed a large number of industrial products in the existing IoT marketplace from context-aware computing perspective.[14] Their survey is intended to serve as a guideline and a conceptual framework for context-aware product development and research in the IoT paradigm. The evaluation has been done using the theoretical framework developed by Dey and Abowd (1999)[2] more than a decade ago.

Human factors related context is structured into three categories: information on the user (knowledge of habits, emotional state, biophysiological conditions), the user’s social environment (co-location of others, social interaction, group dynamics), and the user’s tasks (spontaneous activity, engaged tasks, general goals). Likewise, context related to physical environment is structured into three categories: location (absolute position, relative position, co-location), infrastructure (surrounding resources for computation, communication, task performance), and physical conditions (noise, light, pressure, air quality).

Application in health care[edit]

Context-aware mobile agents[15] are a best suited host implementing any context-aware applications. Modern integrated voice and data communications equips the hospital staff with smart phones to communicate vocally with each other, but preferably to look up the next task to be executed and to capture the next report to be noted.

However, all attempts to support staff with such approaches are hampered till failure of acceptance with the need to look up upon a new event for patient identities, order lists and work schedules. Hence a well suited solution has to get rid of such manual interaction with a tiny screen and therefore serves the user with

  • automated identifying actual patient and local environment upon approach,
  • automated recording the events with coming to and leaving off the actual patient,
  • automated presentation of the orders or service due on the current location and with
  • supported documenting the required information keying in a minimum of data into prepared form entries.

Basically such contextually well formed approach requires scheduled workflows, as all necessary preparation must refer to given orders and set schedules. Working free hand or ex tempore does not provide such qualities.[citation needed]

Additionally, none of the RFID, WLAN or RTLS locating solutions advertising for most precise locating serve the required quality, as determining a location in conventional attitude looking for absolute coordinates fails either technically or economically.

However, the coincidence of personnel with patient is easily detected and delivers all options of reliable automating at reasonable effort. An escape is fairly available with the method of unilateration or fuzzy locating, where no absolute coordinates are required, but just the radial distance between personnel smart phone and patient wrist band.[16] Such distance estimating is entirely sufficient to detect the context of servicing the patient, as no service is ever applied to patients only at larger distance. Even in nuclear medicine or with radiology diagnosis, the haptic contact of staff with patient comes before staff retreats while the patient gets exposed to isotopes or X-rays.

Applications in Pervasive Games[edit]

Pervasive gaming, a new genre in the field of entertainment, is leveraging the sensed human contexts to adapt game system behaviors. By blending of real and virtual elements and enabling users to physically interact with their surroundings during the play, people can become fully involved in pervasive games and attain better gaming experience. For example, a pervasive game that uses the contexts of human activity and location in smart homes is reported by [17]

See also[edit]



  1. ^ Rosemann, M., & Recker, J. (2006). "Context-aware process design: Exploring the extrinsic drivers for process flexibility". In T. Latour & M. Petit. 18th international conference on advanced information systems engineering. proceedings of workshops and doctoral consortium. Luxembourg: Namur University Press. pp. 149–158. 
  2. ^ a b Towards a Better Understanding of Context and Context-Awareness
  3. ^ Kaltz, J.W., Ziegler, J., Lohmann, S. (2005). "Context-aware Web Engineering: Modeling and Applications" (PDF). Revue d'Intelligence Artificielle 19 (3): 439–458. doi:10.3166/ria.19.439-458. 
  4. ^ CISCO AAA Overview
  5. ^ B. Schilit, N. Adams, and R. Want. (1994). "Context-aware computing applications". IEEE Workshop on Mobile Computing Systems and Applications (WMCSA'94), Santa Cruz, CA, US. pp. 89–101. CiteSeerX: 
  6. ^ Schilit, B.N. and Theimer, M.M. (1994). "Disseminating Active Map Information to Mobile Hosts". IEEE Network 8 (5): 22–32. doi:10.1109/65.313011. 
  7. ^ a b Dey, Anind K. (2001). "Understanding and Using Context". Personal Ubiquitous Computing 5 (1): 4–7. doi:10.1007/s007790170019. 
  8. ^ Cristiana Bolchini and Carlo A. Curino and Elisa Quintarelli and Fabio A. Schreiber and Letizia Tanca (2007). "A data-oriented survey of context models" (PDF). SIGMOD Rec. (New York, NY, USA: ACM) 36 (4): 19–26. doi:10.1145/1361348.1361353. ISSN 0163-5808. 
  9. ^ Schmidt, A.; Aidoo, K.A.; Takaluoma, A.; Tuomela, U.; Van Laerhoven, K; Van de Velde W. (1999). "Advanced Interaction in Context" (PDF). 1st International Symposium on Handheld and Ubiquitous Computing (HUC99), Springer LNCS, Vol. 1707. pp. 89–101. 
  10. ^ Schmidt, Albrecht (2002). "Ubiquitous Computing - Computing in Context". PhD dissertation, Lancaster University. 
  11. ^ Albrecht Schmidt, Michael Beigl and Hans-W. Gellersen (December 1999). "There is more to Context than Location" (PDF). Computers & Graphics (Elsevier) 23 (6): 893–902. doi:10.1016/s0097-8493(99)00120-x. 
  12. ^ Paolo Bellavista, Antonio Corradi, Mario Fanelli and Luca Foschini (August 2012). "A Survey of Context Data Distribution for Mobile Ubiquitous Systems". Computing Surveys, ACM 44 (4): 1–45. doi:10.1145/2333112.2333119. 
  13. ^ Charith Perera, Arkady Zaslavsky, Peter Christen, and Dimitrios Georgakopoulos (2013). "Context Aware Computing for The Internet of Things: A Survey". Communications Surveys Tutorials, IEEE. Early Access Articles (n/a): 1–44. doi:10.1109/SURV.2013.042313.00197. 
  14. ^ Perera, Charith; Liu, Harold; Jayawardena, Srimal; Chen, Min. "A Survey on Internet of Things From Industrial Market Perspective". Access, IEEE 2: 1660–1679. doi:10.1109/ACCESS.2015.2389854. Retrieved 1 February 2015. 
  15. ^ Burstein Context Aware Mobile Agents in Healthcare
  16. ^ Wireless authenticating & authorising system
  17. ^ B. Guo, R. Fujimura, D. Zhang, M. Imai.Design-in-Play: Improving the Variability of Indoor Pervasive Games. Multimedia Tools and Applications, 2011.

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