Studies in Small Scale Data: Three Case Studies on Describing Individuals’ Spatial Behaviour in Cities

Widder, Lynnette and Braden, Jessie and Ko, Joy and Steinfeld, Kyle (2017) Studies in Small Scale Data: Three Case Studies on Describing Individuals’ Spatial Behaviour in Cities. EAI Endorsed Transactions on Internet of Things, 3 (10): 1. ISSN 2414-1399

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Abstract

Big Data has been effectively mined to understand behavioural patterns in cities and to map large-scale trends predicated upon the repeated actions of many aggregated individuals. While acknowledging the vital role that this work has played in harnessing the Urban Internet of Things as a means to ensure efficient and sustainable urban systems, our work seeks to recover a scale of behavioural research associated with earlier, empirical studies on urban networks. UrbanIOT data expands the depth and precision of intimate behavioural analysis; small-scale analysis lends insight into important anomalies not explained by large-scale trends. The three case studies at stake here combined empirical journaling with data from mobile devices, tracking both automatically and through user reporting. Each produced diverse information and visualizations for describing the interaction of individual citizens, resources and urban systems. These are: a description of behaviours relative to food stores and shopping habits in New York City, US; a description of the correlation between mobility and food waste likelihood in Providence, RI, US; and a study of mobility patterns and personal choices in Copenhagen, DK.

Item Type: Article
Uncontrolled Keywords: Resource Flows, Transportation, Human Factors, Visualization, Design Thinking, Apps, GIS, GPS.
Subjects: Q Science > QA Mathematics > QA76 Computer software
Depositing User: EAI Editor III.
Date Deposited: 22 Sep 2020 13:46
Last Modified: 22 Sep 2020 13:46
URI: https://eprints.eudl.eu/id/eprint/541

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