This survey and taxonomy of location systems for mobile-computing applications describes...

Emerging mobile computing applications often need to know where things are physically located. To meet this need, many dierent location systems and technologies have been developed. In this paper we present a the basic techniques used for location-sensing, describe a taxonomy of location system properties, present a survey of research and commercial location systems that de ne the eld, show how the taxonomy can be used to evaluate location-sensing systems, and oer suggestions for future research. It is our hope that this paper is a useful reference for researchers and location-aware application builders alike for understanding and evaluating the many options in this domain.

Location information can be used to enhance interaction with mobile devices. While many location systems require instrumentation of the environment, we present a system that allows devices to measure their spatial relations in a true peerto -peer fashion. The system is based on custom sensor hardware implemented as USB dongle, and computes spatial relations in real-time. In extension of this system we propose a set of spatialized widgets for incorporation of spatial relations in the user interface. The use of these widgets is illustrated in a number of applications, showing how spatial relations can be employed to support and streamline interaction with mobile devices.

Augmented Reality (AR) provides a natural interface to the "calm" pervasive technology anticipated in large-scale Ubiquitous Computing environments. However, the range of classic AR applications has been limited by the scope, range and cost of sensors used for tracking. Hybrid tracking approaches can go some way to extending this range. We propose an approach, called Ubiquitous Tracking, in which data from widespread and diverse heterogeneous tracking sensors is automatically and dynamically fused, and then transparently provided to applications. A formal model represents spatial relationships between objects as a graph attributed with quality-of-service parameters. This paper presents a software implementation, in which a dynamic data flow network of distributed software components is thereby constructed in response to queries and optimisation criteria specified by applications. This implementation is demonstrated using a small laboratory example, and larger setups modelled in a simulation environment.

Abstract. Location is a primary cue in many context-aware computing systems, and is often represented as a global coordinate, room number, or a set of Euclidean distances to various landmarks. A user’s concept of location, however, is often defined in terms of regions in which similar activities occur. We discuss the concept of such regions, which we call activity zones, and suggest that such zones can be used to trigger application actions, retrieve information based on previous context, and present information to users. We show how to semi-automatically partition a space into activity zones based on patterns of observed user location and motion. We describe our system and two implemented example applications whose behavior is controlled by users ’ entry, exit, and presence in the zones. 1

Load sensing is a mature and robust technology widely applied in process control. In this paper we consider the use of load sensing in everyday environments as an approach to acquisition of contextual information in ubiquitous computing applications. Since weight is an intrinsic property of all physical objects, load sensing is an intriguing concept on the physical-virtual boundary, enabling the inclusive use of arbitrary objects in ubiquitous applications. In this paper we aim to demonstrate that load sensing is a versatile source of contextual information. Using a series of illustrative experiments we show that using load sensing techniques we can obtain not just weight information, but object position and interaction events on a given surface. We describe the incorporation of load-sensing in the furniture and the floor of a living laboratory environment, and report on a number of applications that use context information derived from load sensing.

In this paper, we propose an ontology-based approach for analyzing social interaction patterns in a nursing home from video. Social interaction patterns are broken into individual activities and behavior events using a multi-level context hierarchy ontology framework. To take advantage of an ontology in representing how social interactions evolve, we design and refine the ontology based on knowledge gained from 80 hours of video recorded in the public spaces of a nursing home. The ontology is implemented using a dynamic Bayesian network to statistically model the multi-level concepts defined in the ontology. We have developed a prototype system to illustrate the proposed concept. Experiment results have demonstrated feasibility of the proposed approach. The objective of this research is to automatically create concise and comprehensive reports of activities and behaviors of patients to support physicians and caregivers in a nursing facility.

In the past decade, there have been numerous efforts in ubiquitous computing, making computational resources or communication more widely available. We believe that it is time to move to a global-scale ubiquitous computing system that is securable, administered by multiple independent administrators and integrates off-the-shelf hardware and software. We are developing such a system based on the Session Initiation Protocol (SIP), with Bluetooth devices for location sensing and Service Location Protocol (SLP) for service discovery. We also introduce context-aware location information to augment device discovery and user communication. The system builds on our CINEMA infrastructure and can support a range of activities, from home-based settings to collaboration between distant sites.

Location-based context is important for many applications. Previous systems offered only coarse room-level features or used manually specified room regions to determine fine-scale features. We propose a location context mechanism based on activity maps, which define regions of similar context based on observations of 3-D patterns of location and motion in an environment. We describe an algorithm for obtaining activity maps using the spatio-temporal clustering of visual tracking data. We show how the recovered maps correspond to regions for common tasks in the environment and describe their use in some applications.

No matter which technologies or techniques a ubiquitous location system uses, its measurements will have some amount of quantifiable error.