The active badge location system
ACM Transactions on Information Systems (TOIS)
Audio augmented reality: a prototype automated tour guide
CHI '95 Conference Companion on Human Factors in Computing Systems
Cyberguide: a mobile context-aware tour guide
Wireless Networks - Special issue: mobile computing and networking: selected papers from MobiCom '96
Understanding and Using Context
Personal and Ubiquitous Computing
A zero-input interface for leveraging group experience in web browsing
Proceedings of the 8th international conference on Intelligent user interfaces
Location-Aware Information Delivery with ComMotion
HUC '00 Proceedings of the 2nd international symposium on Handheld and Ubiquitous Computing
Mr.Web: an automated interactive webmaster
CHI '03 Extended Abstracts on Human Factors in Computing Systems
A survey of research on context-aware homes
ACSW Frontiers '03 Proceedings of the Australasian information security workshop conference on ACSW frontiers 2003 - Volume 21
An Indoor Wireless System for Personalized Shopping Assistance
WMCSA '94 Proceedings of the 1994 First Workshop on Mobile Computing Systems and Applications
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Context and information awareness is generally driven by the choice of available data acquisition mechanisms. In context aware system design, sensors are the primary means for data acquisition. To make such systems effective, sensors need to provide data that is accurate and reflects real time situations and events. Such data is not always readily available and may require a considerable number of in-field experiments with prototypes to gather it. In the absence of good sensor data, the situation aware models and functionality become largely ineffective. This paper proposes the use of qualitative and quantitative information gathered from logs and user research to directly generate artificial sensor data and models or complement existing sensor acquisition techniques. Data obtained via a human perspective based approach is accurate in terms of scenario requirements and user preferences, and complements sensor based data very well. This approach is similar to end-user tailoring, and preference elicitation methodologies. Furthermore, this approach allows designers to generate models that can be evaluated first before narrowing down the selection of sensors, attributes, and implementation infrastructure, thus keeping the design cost low. We present this approach with the help of a case study that involves the design of interruption aware cell phone simulations. We also propose the need for using similar human perspective based approaches in scenarios where sensor data acquisition is not accurate or feasible.