Spelling suggestions: "subject:"locationaware computing"" "subject:"locationsare computing""
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A Privacy Conscious Bluetooth Infrastructure for Location Aware ComputingHuang, Albert, Rudolph, Larry 01 1900 (has links)
We present a low cost and easily deployed infrastructure for location aware computing that is built using standard Bluetooth® technologies and personal computers. Mobile devices are able to determine their location to room-level granularity with existing bluetooth technology, and to even greater resolution with the use of the recently adopted bluetooth 1.2 specification, all while maintaining complete anonymity. Various techniques for improving the speed and resolution of the system are described, along with their tradeoffs in privacy. The system is trivial to implement on a large scale – our network covering 5,000 square meters was deployed by a single student over the course of a few days at a cost of less than US$1,000. / Singapore-MIT Alliance (SMA)
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High Level VHDL Modeling of a Low-Power ASIC for a Tour GuideKailasam, Umadevi 29 March 2004 (has links)
We present the high level (VHDL) modeling and high level synthesis of an ASIC (TOUR NAVIGATOR) for a portable hand held device - a tour guide. The tour guide is based on location-aware mobile computing, which gives the information of the current location to the user. The TOUR NAVIGATOR designed in this work is interfaced with off-the-shelf components to realise the tour guide system. The current location is given by an on-board GPS receiver chip. The TOUR NAVIGATOR is a search and play module which interfaces with the flash memory, GPS receiver and the audio codec.
The functionality of the TOUR NAVIGATOR is to search the flash memory for audio data corresponding to the current GPS co-ordinate, which is an input to the TOUR NAVIGATOR. The look-up table containing the GPS coordinates and the corresponding audio files are loaded into the flash memory, where in each GPS entry in the table is indexed by the co-ordinates, and an audio file that contains information about the locations is associated with it. When there is a match, the audio file is streamed to the codec. The functionality of the interface of the TOUR NAVIGATOR with the memory module is verified at the RTL using Cadence-NCLaunch. The layout implementation of the TOUR NAVIGATOR is done using an automatic place and route tool (Silicon Ensemble), which uses standard cells for the entire design. Leakage power reduction is done by introducing sleep transistors in the standard cells. The TOUR NAVIGATOR is put into a "sleep" mode when there is no operation of the tour guide, thus giving significant power savings.
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A Constructive Memory Architecture for Context AwarenessDaruwala, Yohann January 2008 (has links)
Master of Philosophy (Architecture) / Context-aware computing is a mobile computing paradigm in which applications can discover, use, and take advantage of contextual information, such as the location, tasks and preferences of the user, in order to adapt their behaviour in response to changing operating environments and user requirements. A problem that arises is the inability to respond to contextual information that cannot be classified into any known context. Many context-aware applications require all discovered contextual information to exactly match a type of context, otherwise the application will not react responsively. The ability to learn and recall contexts based on the contextual information discovered has not been very well addressed by previous context-aware applications and research. The aim of this thesis is to develop a component middleware technology for mobile computing devices for the discovery and capture of contextual information, using the situated reasoning concept of constructive memory. The research contribution of this thesis lies in developing a modified architecture for context-aware systems, using a constructive memory model as a way to learn and recall contexts from previous experiences and application interactions. Using a constructive memory model, previous experiences can be induced to construct potential contexts, given a small amount of learning and interaction. The learning process is able to map the many variations of contextual information currently discovered by the user with a predicted type of context based on what the application has stored and seen previously. It only requires a small amount of contextual information to predict a context, something common context-aware systems lack, as they require all information before a type of context is assigned. Additionally, some mechanism to reason about the contextual information being discovered from past application interactions will be beneficial to induce contexts for future experiences.
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A Constructive Memory Architecture for Context AwarenessDaruwala, Yohann January 2008 (has links)
Master of Philosophy (Architecture) / Context-aware computing is a mobile computing paradigm in which applications can discover, use, and take advantage of contextual information, such as the location, tasks and preferences of the user, in order to adapt their behaviour in response to changing operating environments and user requirements. A problem that arises is the inability to respond to contextual information that cannot be classified into any known context. Many context-aware applications require all discovered contextual information to exactly match a type of context, otherwise the application will not react responsively. The ability to learn and recall contexts based on the contextual information discovered has not been very well addressed by previous context-aware applications and research. The aim of this thesis is to develop a component middleware technology for mobile computing devices for the discovery and capture of contextual information, using the situated reasoning concept of constructive memory. The research contribution of this thesis lies in developing a modified architecture for context-aware systems, using a constructive memory model as a way to learn and recall contexts from previous experiences and application interactions. Using a constructive memory model, previous experiences can be induced to construct potential contexts, given a small amount of learning and interaction. The learning process is able to map the many variations of contextual information currently discovered by the user with a predicted type of context based on what the application has stored and seen previously. It only requires a small amount of contextual information to predict a context, something common context-aware systems lack, as they require all information before a type of context is assigned. Additionally, some mechanism to reason about the contextual information being discovered from past application interactions will be beneficial to induce contexts for future experiences.
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