Authoring Platform for Mobile Citizen Science Apps with Client-side ML
- URL: http://arxiv.org/abs/2212.05411v1
- Date: Sun, 11 Dec 2022 05:10:23 GMT
- Title: Authoring Platform for Mobile Citizen Science Apps with Client-side ML
- Authors: Fahim Hasan Khan, Akila de Silva, Gregory Dusek, James Davis, Alex
Pang
- Abstract summary: A significant portion of citizen science projects depends on visual data, where photos or videos of different subjects are needed.
In this article, we introduce an authoring platform for easily creating mobile apps for citizen science projects.
The apps created with our platform can help participants recognize the correct data and increase the efficiency of the data collection process.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Data collection is an integral part of any citizen science project. Given the
wide variety of projects, some level of expertise or, alternatively, some
guidance for novice participants can greatly improve the quality of the
collected data. A significant portion of citizen science projects depends on
visual data, where photos or videos of different subjects are needed. Often
these visual data are collected from all over the world, including remote
locations. In this article, we introduce an authoring platform for easily
creating mobile apps for citizen science projects that are empowered with
client-side machine learning (ML) guidance. The apps created with our platform
can help participants recognize the correct data and increase the efficiency of
the data collection process. We demonstrate the application of our proposed
platform with two use cases: a rip current detection app for a planned pilot
study and a detection app for biodiversity-related projects.
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