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sensing_and_living_lab_outdoor_experimentation_made_easy
Journal article

Crowd Sensing and Living Lab Outdoor Experimentation Made Easy

BP2-STS

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  • 2021
Published in:
  • IEEE Pervasive Computing. - Institute of Electrical and Electronics Engineers (IEEE). - 2021, vol. 21, no. 1, p. 18-27
Data collection
Task analysis
Sensors
Smart phones
Load modeling
Crowdsensing
Open source software
Remote laboratories
Pervasive computing
Data privacy
Mobile computing
Public domain software
Smart phones
Statistical analysis
Ubiquitous computing
Higher realism
External validity
Socio-spatio-temporal observations
Privacy concerns
Ethical review boards
Remote moderation
High-quality data
Smart Agora
Novel open-source software platform
Rigorous systematic outdoor experimentation
Highly complex experimental scenarios
Sensor data
Crowd sensing
Lab outdoor experimentation
Pervasive computing
English Living lab outdoor experimentation using pervasive computing provides new opportunities: higher realism, external validity, and socio-spatio-temporal observations in large scale. However, experimentation “in the wild” is complex and costly. Noise, biases, privacy concerns, compliance with standards of ethical review boards, remote moderation, control of experimental conditions, and equipment perplex the collection of high-quality data for causal inference. This article introduces Smart Agora, a novel open-source software platform for rigorous systematic outdoor experimentation. Without writing a single line of code, highly complex experimental scenarios are visually designed and automatically deployed to smart phones. Novel geolocated survey and sensor data are collected subject of participants verifying desired experimental conditions, for instance, their localization at certain urban spots. This new approach drastically improves the quality and purposefulness of crowd sensing, tailored to conditions that confirm/reject hypotheses. The features that support this innovative functionality and the broad spectrum of its applicability are demonstrated.
Faculty
Faculté des sciences économiques et sociales et du management
Department
Département des sciences de la communication et des médias
Language
  • English
Classification
Information, communication and media sciences
License
Rights reserved
Open access status
hybrid
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/326104
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