There is more to context than location

TLDR: A working model for context is introduced, mechanisms to acquire context beyond location, and application of context-awareness in ultra-mobile computing are discussed and fusion of sensors for acquisition of information on more sophisticated contexts are explored.

About: This article is published in Computers & Graphics.The article was published on 1999-12-01 and is currently open access. It has received 1222 citations till now. The article focuses on the topics: Context awareness & Context (language use).

Figures

Fig. 4: Light sensor data

Figure 1: Context feature space.

Figure 2: Using the orientation-aware device in different modes.

Fig. 3: Schematic of the Awareness Device

Frequently asked questions

Q1. What are the contributions in this paper?

The authors propose that ultra-mobile computing, characterized by devices that are operational and operated while on the move ( e. g. PDAs, mobile phones, wearable computers ), can significantly benefit from a wider notion of context. To structure the field the authors introduce a working model for context, discuss mechanisms to acquire context beyond location, and application of context-awareness in ultra-mobile computing. The authors investigate the utility of sensors for context-awareness and present two prototypical implementations a light sensitive display and an orientation aware PDA interface. Further the authors explore fusion of sensors for acquisition of information on more sophisticated contexts. 

Q2. What are the future works in this paper?

A further research topic the authors are working on is cooperative context discovery. 

Q3. What is the effect of artificial neural networks?

Also when deploying automatic mappings, such as artificial neural networks, the introduced abstraction reduces the input dimension and eases the construction process. 

Q4. What is the meaning of context in ultra-mobile computing?

Situations and environments are generally characterized by a large degree of continuity over time, so that context history itself becomes an important feature for approximation of a given situation or environment. 

Q5. What is the purpose of this paper?

In this paper the authors showed that context-awareness can enhance ultra-mobile devices, especially towards providing an improved interface between the user and the device. 

Q6. What are the main developments in this area?

Relevant developments in this area are the embedding of sensors in handheld computers, the development of sensor devices as independent components, and the integration of sensors in wearable computing systems. 

Q7. What can be used to extract cues from light sensor readings?

Simple statistical functions can be applied to extract cues such as “artificial light” and “brightness” from the light sensor readings. 

Q8. What is the use of light sensors in the PDA?

Collaboration over PDAs: in face-to-face settings, users can take turns in interacting with the same PDA by simple handing it over with out having to turn it; a user can show the display to another by simply tilting it toward them. 

Q9. What is the second approach to acquiring context related to the physical environment?

The second approach is to embed sensors in ultra-mobile devices to acquire context related to the physical environment with the obvious advantage of not having to rely on infrastructure, and to be applicable in any environment. 

Q10. What is the first hardware platform for the sensor?

The first hardware platform simply samples sensor data and packages it into a digital signal that can be transferred to a standard portable computer for further processing. 

Q11. What is the definition of a context in ultra-mobile devices?

An example for explicit context acquisition in ultra-mobile devices is the specification of current location as required by personal digital assistants (e.g. PSION) to adapt standard location-dependent applications such as clock, tone dialing, and “world”. 

Q12. What is the main problem with the discussion of context-awareness?

Discussion of context-awareness suffers from the generality of the concept and the lack of models suited for comparison of approaches. 

Q13. What are the three applications that can benefit from context-awareness?

Beyond these general considerations, the authors have identified three application domains in ultra-mobile computing which the authors believe can considerably benefit from context-awareness: • Adaptive user interfaces: the utility of interaction styles and display modes depends largely on thesurrounding environment; context-awareness can facilitate adaptation to surrounding conditions.• 

Q14. How can you determine the level of noise and loudness of the background noise?

With little effort (i.e. cheap microphone and some electronics) loudness, type of background noise, and base frequency can be determined. 

Q15. What is the meaning of context in mobile computing?

In mobile computing, application usage is set in different environments at different times, constituting changing contexts that lie outside the human-computer-system in the environment. 

Q16. How is context acquired in computer applications?

In computer applications, context is acquired either explicitly by requiring the user to specify it, or implicitly by monitoring user and computer-based activity. 

Q17. What is the purpose of this article?

In the previous section the authors have reported work demonstrating the utility of enhancing ultra-mobile devices with simple and affordable sensor technology. 

Q18. What is the purpose of the Newton MessagePad?

The Newton MessagePad and also other PDAs actually offer operating system support for rotation of the user interface but experience shows that this feature is hardly used, if at all. 

Q19. What is the first approach to acquiring context?

The first is based on smart environments that provide an infrastructure for obtaining context and for providing context to mobile applications.