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Beginning of article

1. Introduction

The research community has introduced a large volume of context-aware systems [4], which have adopted different definitions of the slippery notion of "context" [6]. The systems typically involves mechanisms for context acquisition, preprocessing, representation, management and utilization in an application. The raw context data is acquired from different types of sources or "sensors", where the term "sensor' has to be understood very broadly. The raw context data may be subjected to different forms of preprocessing, for example to deal with missing data or to elicit higher level abstractions such as logical relationships or activities. Different models have been developed for representing context data in formats understood by computers and users, ranging from simple key-value pairs to extensive ontologies [5]. Different types of centralized and distributed context management architectures have been proposed for storing and distributing context data to applications. They then utilize context for various purposes such as to adapting the user interface or to retrieving contextually relevant information.

When evaluating context-aware mobile systems, we have to make a distinction whether we evaluate the system architecture [12] or the user interface [7]. Evaluating the user interface or usability of mobile systems is difficult due to extra interaction and evaluation challenges in the mobile domain. The interaction challenges include the mobile context of use, rich device functionality, small device size, lack of direct manipulation, and lack of standardization in handset and software design.

The evaluation challenges relate to data collection (technical, social and legal constraints) and uncontrollable variables (e.g. weather, ambient noise and attention destructors). Important decisions to be made regarding evaluation include what is evaluated (interface metaphors, mental models or UI elements), how (empirical vs analytical) and where (lab vs field). While a lab experiment does not provide a proper simulation of the true mobile context and the real-word factors affecting behavior and performance are missing, a field experiment in turn is time consuming, expensive, and suspect to data collection difficulties and uncontrollable external variables.

The six case studies presented in this paper demonstrate the utilization of context data in different types of context-aware mobile multimedia services. Each service employs a simple key-value context model and centralized context management architecture for storing or retrieving contextually relevant information. First five case studies originate from the Rotuaari --Context-Aware Mobile Multimedia Services research project [19]. Each of them involved empirical evaluation in the field in form of a user evaluation with real users in true environment of use. It is a fundamental usability assessment method providing direct information about how the system is used and what are the exact problems [11]. The sixth case study, panOULU Luotsi, is a joint effort of the Wireless Cities project [21] and the panOULU network [15]. Some of the services are now in "production" use, either as a public service or as a commercial product.

2. SmartRotuaari

SmartRotuaari was an early demonstration of the new mobile multimedia services that emerging wireless broadband Internet would eventually facilitate. SmartRotuaari comprised of a wireless multi-access network, SmartWare architcture for deploying context-aware mobile multimedia services, a web-based CPI (Content Provider Interface) for content management and a collection of functional prototype services [13]. The design and implementation of the system started in 2002, leading to empirical evaluation in form of a large-scale field trial executed at downtown Oulu in fall 2003. SmartRotuaari was motivated by the needs of both companies (i.e. mobile service providers, technology providers, retailers etc.) and consumers as end users of mobile services. While companies have the most comprehensive knowledge about their business ("market pull"), some of them, especially smaller retailers, are not necessarily aware of the possibilities offered by the new technology ("technology push"). These aspects were studied in form of surveys, joint workshops and one-to-one discussions with local businesses.

The multi-access network comprised of a GPRS network and a WLAN (IEEE 802.11b). The WLAN emulated the emerging wireless broadband Internet access with much higher data transfer rate and lower latencies than GPRS. We built the WLAN ourselves, managing to install 11 WLAN access points around downtown Oulu by the start of the first field trial in late August 2003. Later the WLAN network was expanded, contributing to the founding of the panOULU network in October 2003 [15], which eventually proved to be the most valuable outcome of the project.

The SmartWare architecture included server components for service access, user positioning, instant messaging, real-time presence management and database access. The architecture facilitated using different context attributes represented as key-value pairs in service provisioning: time (e.g. time range when a service was active), location (absolute and relative locations of the user and/or a service provider, for example a service could be triggered if the user was within a specific distance of a service provider, location of the user could be provided by GPS, WLAN positioning or manual entry), weather (real-time weather observation, temperature and wind speed divided to non-overlapping ranges), user profile (e.g. age, marital status, education, occupation, income, personal interests entered upon registration) and user presence (availability and mood set to any of the seven predefined values).

The prototype services were implemented with a monolithic Java client for PDA's. They included a service directory, map-based guidance, personal communications, Time Machine Oulu (see Section 3), mobile ads (see Section 5), personalized news and mobile payment. The "desktop" shown in Fig. 1(a) provided access to individual services. Map-based guidance (Fig. 1(b)) provided visualization of the location of a place relative to the user's current location shown as red dot. A place could refer to any entry in the service directory, a 'buddy', or a location of personal interest specified earlier by the user. Personal communications was supported in form of peer-to-peer and group chat, which were implemented as simple text-based chat (Fig. 1(c)).

[FIGURE 1 OMITTED]

The user could maintain a list of 'buddies' and invite them to a chat. Further, the user could set his presence status ('mood') to any of the predefined alternatives. The user could choose whether his location and/or presence status were shown to his 'buddies' and other users. Personalized news feed was provided so that the user could designate whether (s)he found a particular article interesting or not. A personalization engine then updated the user's profile accordingly and provided first those of the incoming news that matched the user's interest profile. Mobile payment was implemented with an external micropayment server, which facilitated payments for on-line content with real money.

A subset of the prototype services, service directory, map-based guidance, mobile ads and TimeMachine Oulu, were included in the field trial running from late August 2003 till the end of September 2003. The field trial was coordinated from an office established in a small hut placed at the very heart of downtown Oulu (Fig. 2). The office was staffed with researchers, who persuaded passers-by to sign up as test users, helped test users in creating a user profile and in using the iPAQ and services, and …