Cityware: Design and Evaluation of City-scale Pervasive Technologies

Tim Jay

t.jay@bath.ac.uk

Contents

Background and Rationale Methodology Example studies and findings

The context logger Perceptions of the environment: neighbourhood

and city Bluefish: A privacy probe

Discussion

Cityware

Research collaboration between the University of Bath, Imperial College, The Bartlett at University College London, Vodafone, Nokia and Hewlett-Packard (http://www.cityware.org.uk)

Aim: To increase our knowledge and understanding of people’s relationships with urban spaces and with pervasive technologies in order to enable the development of tools and techniques for the implementation of long-term, city-scale pervasive systems.

How do people understand the city? Lynch, 1960 – The Image of the City

Imagability/legibility Basic elements – paths, edges, districts, nodes

and landmarks Wayfinding and Navigation Landmarks Cognitive Maps Urban Semiotics

The relationship between pervasive technologies and urban environments

Urbantapestries.net, Urban-atmospheres.net, MobileBristol.co.uk (all worth having a look at)

Often cover relatively small physical areas Often run over short timescales Cityware aims to address the methodological

challenge of longitudinal, city-scale studies

Some issues with traditional mobile and pervasive evaluation Bias towards laboratory testing Sample bias – technologically literate

participants Relatively restricted in both time and space –

often out of context

The Cityware Cohort

30 participants, working with us for the 3-year duration of the project

Aged 14-80+ 20 male, 10 female Variety of occupations and levels of technological

ability/awareness All equipped with a Nokia Smartphone and

Vodafone SIM Attend regular workshops + complete other activities

Data Collected

Questionnaires, interviews & focus group work

Personality data Map sketching Moblogging

Example Studies

The context logger Perceptions of the environment –

neighbourhood and city Bluefish: A privacy probe

The context logger

Developed in the Computer Science department, Imperial College

Designed to inform the development of context-aware applications and services

Records a variety of data generated by a mobile phone

Data is automatically transmitted to a remote server using the 3G/GPRS network

Context logged

Time/date and sender/receiver of text messages Time/date and sender receiver of voice calls Camera images Applications in operation Location (using either Bluetooth GPS unit, or built-in

functionality) Bluetooth scans Cell ID in use Active profile Battery strength

Context logger evaluation

Iterative process Local group 3 cohort members (selection criteria) Full cohort

Refinement of the application at each stage Functionality Interaction with general use of phone Privacy and trust concerns

Context Logger: Discussion

Different issues arise at various points of iteration

There is an association between the demographic of the sample and the level of concern that arises

Some issues could only have been discovered through genuine use with genuine user group

Perceptions of the environment How do city residents and visitors perceive and use

the city? Some background

Space syntax methods used to predict pedestrian movements. These can be compared with:

Bluetooth gate counts used in order to analyse actual movements of Bluetooth device around the city (+ social network analysis)

These don’t give access to some important aspects that we are interested in – what meanings are derived from, or ascribed to, the city?

Methods

3 phases Neighbourhoods City ‘Real’ City

Long-term study with cohort Multiple methods

Methods

Moblogging tour Questionnaires

Landmarks City use

Map sketching Boundary marking

The Neighbourhood/City Moblogging Tour GPS trail Photos Video Text notes Audio notes Analysis focuses on:

Representations across formats Landmarks Effects of moblogging on perception

Differences in representation

Landmarks

Rural v. Urban Traditional v. Personal Traditional landmarks

Churches, schools, war memorials, parks, pubs etc.

Personal landmarks (and non-landmarks) Allotments down a back lane A derelict building

Effects of moblogging on perception Change in scale between 1st and 2nd sketch

maps

Next steps

Recently completed similar set of activities in the city centre

Day-to-day city use Expand dataset – including digital landmarks,

Bluetooth, Wifi

Bluefish

Designed as a ‘privacy probe’ Previous Cityware research has shown that many people

are not aware that they are broadcasting information about themselves via their Bluetooth devices

Consists of a network of Bluetooth scanners + 3-4 public display screens, in various locations across Bath

The screens represent Bluetooth activity that has been recorded by the network of scanners - Example

Research Questions

How do people respond to their data and history being made visible by the Bluefish system? How does behaviour change – e.g. Bluetooth

turned on/off, opting in/out of the system What are people’s perceptions of the data, and

what are the reasons for any behaviour change?

Methods

System logs can be used to analyse changes in behaviour but don’t give us the reasons

Interviews on location can tell us something about people’s perception of the system and any reasons for changes in behaviour But – some of the more interesting data will not be

accessible through interviews Initial work will be done with the cohort

Advantages of the cohort

Broad demographic Trust and investment in the project Gives us access to participants who may

have concerns over privacy/security/trust issues, or who are not engaged with the system

Summary

Sustained engagement of participants Helps address the problem of validity

Combinations of data Mixture of methods – lab + field, quantitative +

qualitative Engagement of a community

Participants have ownership of and commitment to the project