Quantifying multi-dimensional attributes of human activities at various geographic scales based on smartphone tracking

Xiaolu Zhou · Dongying Li

13 citations0/0 files storedInternational Journal of Health Geographics

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Human Mobility and Location-Based Analysis Urban Transport and Accessibility Context-Aware Activity Recognition Systems

Abstract

BACKGROUND: Advancement in location-aware technologies, and information and communication technology in the past decades has furthered our knowledge of the interaction between human activities and the built environment. An increasing number of studies have collected data regarding individual activities to better understand how the environment shapes human behavior. Despite this growing interest, some challenges exist in collecting and processing individual's activity data, e.g., capturing people's precise environmental contexts and analyzing data at multiple spatial scales. METHODS: In this study, we propose and implement an innovative system that integrates smartphone-based step tracking with an app and the sequential tile scan techniques to collect and process activity data. We apply the OpenStreetMap tile system to aggregate positioning points at various scales. We also propose duration, step and probability surfaces to quantify the multi-dimensional attributes of activities. RESULTS: Results show that, by running the app in the background, smartphones can measure multi-dimensional attributes of human activities, including space, duration, step, and location uncertainty at various spatial scales. By coordinating Global Positioning System (GPS) sensor with accelerometer sensor, this app can save battery which otherwise would be drained by GPS sensor quickly. Based on a test dataset, we were able to detect the recreational center and sports center as the space where the user was most active, among other places visited. CONCLUSION: The methods provide techniques to address key issues in analyzing human activity data. The system can support future studies on behavioral and health consequences related to individual's environmental exposure.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 13 citations exist upstream.

References

2006Public Participation Geographic Information Systems: A Literature Review and Framework 2012Citizen Science and Volunteered Geographic Information: Overview and Typology of Participation 2009The built environment and obesity: A systematic review of the epidemiologic evidence 1996Methodologies for exploring the link between urban form and travel behavior 2011Activity space environment and dietary and physical activity behaviors: A pilot study 2001The influence of land use on travel behavior: specification and estimation strategies 2010The influence of geographic life environments on cardiometabolic risk factors: a systematic review, a methodological assessment and a research agenda 2007Toward the next generation of research into small area effects on health: a synthesis of multilevel investigations published since July 1998

Cited by

2019Activity space metrics not associated with sociodemographic variables, diet or health outcomes in the Seattle Obesity Study II

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.