System Software for Ubiquitous Computing

By Tim Kindberg, A. Fox. IEEE pervasive computing, 2002

441 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/924825a8a2e79ec43c6e60486293243412a82bbf

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In Computer Networks and Communications

In Computer Vision and Pattern Recognition

In Human-Computer Interaction

Citations in the corpus

A context-aware ubiquitous learning environment for conducting complex science experiments (2009, background): “…and products concerning ubiquitous computing have been developed in recent years, such as sensors and actuators, RFID (Radio Frequency Identification) tags and readers, wireless communication, mobile phones, PDAs, and wearable computers (Feeney, Ahgre, & Westerlund, 2001; Kindberg & Fox, 2002).”
Context-Aware Computing, Learning, and Big Data in Internet of Things: A Survey (2018, background): “For instance, a smart meeting room that senses the existence of people in the room, records their actions and voices, obtains the writing from the whiteboard, and fuses the data of all sensors to extract meaningful knowledge [73].”
The Interactive Workspaces Project: Experiences with Ubiquitous Computing Rooms (2002, background): “In designing it we have kept in mind the boundary principle [10] which states that ubiquitous computing infrastructure needs to allow interaction between devices only within the bounds of the local physical space, in our case an interactive workspace.”
Accurate GSM Indoor Localization (2005, background): “The accurate localization of objects and people in indoor environments has long been considered an important building block for ubiquitous computing applications [7,8].”
Criteria, Strategies and Research Issues of Context-Aware Ubiquitous Learning (2008, background): “A component interoperates spontaneously if it interacts with a set of communicating components that can change both identity and functionality over time as its circumstances change ( Kindberg & Fox, 2002 ).”
Moving on from Weiser's Vision of Calm Computing: Engaging UbiComp Experiences (2006, background): “As pointed out by Greenfield [20] “we simply don’t do ‘smart’ very well yet” because it involves solving very hard artificial intelligence problems that in many ways are more challenging than creating an artificial human [26].”