A New Location Technique for the Active Office Andy Ward Alan Jones Andy Hopper Configuration of the computing and communications systems found at home and in the workplace is a complex task that currently requires the attention of the user Recently researchers have begun to examine computers that would autonomously change their functionality based on observations of who or what was around them By determining their context using input from sensor systems distributed throughout the environment computing devices could personalize themselves to their current user adapt their behaviour according to their location or react to their surroundings We present a novel sensor system suitable for large scale deployment in indoor environments which allows the locations of people and equipment to be accurately determined We also describe some of the context aware applications that might make use of this fine grain location information Introduction The modern home and office are equipped with sophisticated computing and communications devices many of which require significant effort or specialist knowledge to configure and use effectively Whilst the complexity of such devices will surely increase in the future it may be possible to make them more user friendly by transferring some of the configuration burden to the devices themselves These computers would be context aware changing their behaviour based on how and where they were being used A context aware computer or application must be able to determine the state of its surroundings One method of discovering context is to monitor the locations of objects in the environment In this paper we first present an overview of research into location aware computing and evaluate currently available location sensor technologies We then describe a new location sensor tailored to provide information for context sensitive computers which has been developed at the Olivetti and Oracle Research Laboratory ORL Finally we examine potential applications of this system in an Active Office 1 where location aware equipment will be commonplace Location aware Computing Much of the existing research into context aware computing has used location information provided by Active Badges 2 3 small computing devices worn by personnel Each badge has a globally unique code that is periodically broadcast through an infrared interface The infrared signals reflect off walls and furniture to flood the surrounding area and are picked up by a network of sensors placed around the building By determining which badges were seen by which sensors it is possible to deduce the location of a badge giving a hint to the location of the badge s owner Applications in which Active Badge information has been used include telephone call routing security and environmental control 4 University of Cambridge Computer Laboratory Pembroke Street Cambridge CB2 3QG UK Olivetti and Oracle Research Laboratory 24a Trumpington Street Cambridge CB2 1QA UK Active Badge is a registered trademark of Ing C Olivetti C S p A An extension to this system allows equipment to be tracked using a low power version of the Badge called an Equipment Tag 1 The developers describe a nearest printer service offered to users of portable computers Tags placed on the computer and printers report their positions and the computer is automatically configured to use the nearest available printer as it is moved around a building The ParcTab 5 is a Personal Digital Assistant PDA that uses an infrared based cellular network for communication The infrared transmissions from ParcTabs can be used to determine their locations in the same way as Active Badges are located Schilit et al describe the use of the ParcTab system to implement applications involving context triggered actions and automatic reconfiguration 6 The ParcTab has also been used to implement a memory prosthesis 7 in which information about the user s context is collected andorganized to form a biography that can be consulted at a later time Weiser has considered how the widespread deployment of location aware devices might change the way we interact with computers 8 He considers a vision of Ubiquitous Computing in which computing elements are integrated into the environment to such an extent that they become invisible to common awareness There will be a number of different types of device in this computing fabric ranging in size to support different tasks However devices will not be specialized to a particular task instead they will be capable of adapting their behaviour based upon what is happening around them Sensor Technologies Systems like the Active Badge and the ParcTab are robust relatively cheap and can be integrated into everyday working environments However they locate objects only to the granularity of rooms which act as natural containers for the infrared signals emitted by the devices This limits the extent to which applications can adapt based on information from the system It is therefore pertinent to consider other sensor technologies that might give finer grain location information about objects in the office and home Electromagnetic trackers 9 10 can determine object locations and orientations to a high accuracy and resolution around 1mm in position and 0 2 in orientation but are expensive and require tethers to control units Furthermore electromagnetic trackers have a short range generally only a few metres and are sensitive to the presence of metallic objects Optical trackers are very robust and can achieve levels of accuracy and resolution similar to those of electromagnetic tracking systems However they are most useful in well constrained environments and tend to be expensive and mechanically complex Examples of this class of positioning device are a head tracker for augmented reality systems 11 and a laser scanning system for tracking human body motion 12 Radio positioning systems such as GPS and LORAN 13 are very successful in the wide area but are ineffective in buildings because of the reflections of radio signals that occur frequently in indoor environments In building radio positioning systems do exist for example the work of Feuerstein and Pratt 14 but offer only modest location accuracies of around 50cm or more Location information can also be derived from analysis of data such as video images as in the MIT Smart Rooms project 15 Accurate object locations can be determined in this way using relatively cheap hardware but large amounts of