Instrumenting the City: Developing Methods for Observing and Understanding the Digital Cityscape

Abstract

Abstract. We approach the design of ubiquitous computing systems in the urban environment as integral to urban design. To understand the city as a system encompassing physical and digital forms and their relationships with people's behaviours, we are developing, applying and refining methods of observing, recording, modelling and analysing the city, physically, digitally and socially. We draw on established methods used in the space syntax approach to urban design. Here we describe how we have combined scanning for discoverable Bluetooth devices with two such methods, gatecounts and static snapshots. We report our experiences in developing, field testing and refining these augmented methods. We present initial findings on the Bluetooth landscape in a city in terms of patterns of Bluetooth presence and Bluetooth naming practices.

Leveraging explicitly disclosed location information to understand tourist dynamics: a case study

“…A third approach relies on the deployment of Bluetooth enabled systems. Recent studies have been able to establish the flow of people at strategic locations (O'Neill et al, 2006) as well as to recognize daily user activities and to identify socially significant locations (Eagle and Pentland, 2006). However, there are several key issues when using technologies to collect travel behaviours.…”

New Tools for Studying Visitor Behaviours in Museums: A Case Study at the Louvre

“…The recent wide spread of mobile devices implies that many people have their Bluetooth switched on passively, thus providing an important source of useful data. A variety of projects have exploited Bluetooth data for measuring the social network relationships between people (Eagle & Pentland, 2005, Paulos & Goodman, 2004, Nicolai, Yoneki, Behrens, & Kenn, 2006, mobility of vehicles (Yalowitz & Bronnenkant, 2009, Barceló, Montero, Marqués, & Carmona, 2010 and mobility of pedestrians and their relationships (O'Neill et al, 2006, Kostakos et al, 2010. However these investigations have not considered a specific analysis of pedestrians and their use of space.…”

Human interaction discovery in smartphone proximity networks

“…As two examples, Terry et al [36] investigated the use of pairwise proximity patterns over time to identify interests shared by individuals. In an urban context, O'Neill et al proposed to use the number of detected BT devices in an environment as an indicator of the associated human density [31]. More recently, other related work has appeared, often under the umbrella term of reality mining [11].…”