Location-aware computing involves the automatic tailoring of information and services based on the current location of the user. We have designed and implemented Rover, a system that enables location-based services, as well as the traditional time-aware, user-aware and device-aware services. To achieve system scalability to very large client sets, Rover servers are implemented in an action-based concurrent software architecture that enables fine-grained application-specific scheduling of tasks. We have demonstrated feasibility through implementations for both outdoor and indoor environments on multiple platforms.
A user is shopping in a mall. On entering a store, he pulls out a PDA and browses through detailed information about the products on display. Satisfied with the information, through the PDA, he makes an online purchase of the items of interest that will be subsequently shipped to his home directly. As he walks on to the next store, which happens to be a video rental store, information on newly-released movies in his favorite categories are downloaded automatically into his PDA, along with their availability information. He chooses a couple of these movies and indicates that he will pick them up at the storefront.
LOCATION AWARE COMPUTING COMES OF AGE
At the core of invisible computing is context awareness, the concept of sensing and reacting to dynamic environments and activities. Location is a crucial component of context, and much research in the past decade has focused on location-sensing technologies, location-aware application support, and location-based applications. With numerous factors driving deployment of sensing technologies, location-aware computing may soon become a part of everyday life.
A central problem in location-aware computing is the determination of physical location. Researchers in academia and industry have created numerous location-sensing systems that differ with respect to accuracy, coverage, frequency of location updates, and cost of installation and maintenance.