Fahim Hasan Khan, Akila De Silva, Gregory Dusek, James Davis, Alex Pang
{"title":"SmartCS: Enabling the Creation of Machine Learning–Powered Computer Vision Mobile Apps for Citizen Science Applications without Coding","authors":"Fahim Hasan Khan, Akila De Silva, Gregory Dusek, James Davis, Alex Pang","doi":"10.5334/cstp.642","DOIUrl":null,"url":null,"abstract":"It is undeniable that citizen science contributes to the advancement of various fields of study. There are now software tools that facilitate the development of citizen science apps. However, apps developed with these tools rely on individual human skills to correctly collect useful data. Machine learning (ML)–aided apps provide on-field guidance to citizen scientists on data collection tasks. However, these apps rely on server-side ML support, and therefore need a reliable internet connection. Furthermore, the development of citizen science apps with ML support requires a significant investment of time and money. For some projects, this barrier may preclude the use of citizen science effectively. We present a platform that democratizes citizen science by making it accessible to a much broader audience of both researchers and participants. The SmartCS platform allows one to create citizen science apps with ML support quickly and without coding skills. Apps developed using SmartCS have client-side ML support, making them usable in the field, even when there is no internet connection. The client-side ML helps educate users to better recognize the subjects, thereby enabling high-quality data collection. We present several citizen science apps created using SmartCS, some of which were conceived and created by high school students.","PeriodicalId":514738,"journal":{"name":"Citizen Science: Theory and Practice","volume":"32 8","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Citizen Science: Theory and Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5334/cstp.642","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
It is undeniable that citizen science contributes to the advancement of various fields of study. There are now software tools that facilitate the development of citizen science apps. However, apps developed with these tools rely on individual human skills to correctly collect useful data. Machine learning (ML)–aided apps provide on-field guidance to citizen scientists on data collection tasks. However, these apps rely on server-side ML support, and therefore need a reliable internet connection. Furthermore, the development of citizen science apps with ML support requires a significant investment of time and money. For some projects, this barrier may preclude the use of citizen science effectively. We present a platform that democratizes citizen science by making it accessible to a much broader audience of both researchers and participants. The SmartCS platform allows one to create citizen science apps with ML support quickly and without coding skills. Apps developed using SmartCS have client-side ML support, making them usable in the field, even when there is no internet connection. The client-side ML helps educate users to better recognize the subjects, thereby enabling high-quality data collection. We present several citizen science apps created using SmartCS, some of which were conceived and created by high school students.
不可否认,公民科学有助于推动各个研究领域的发展。现在有一些软件工具可以促进公民科学应用程序的开发。不过,利用这些工具开发的应用程序要正确收集有用的数据,还得依靠个人的技能。机器学习(ML)辅助应用程序可为公民科学家的数据收集任务提供现场指导。不过,这些应用程序依赖服务器端的 ML 支持,因此需要可靠的互联网连接。此外,开发具有 ML 支持的公民科学应用程序需要投入大量的时间和金钱。对于某些项目来说,这一障碍可能会阻碍公民科学的有效使用。我们提出了一个使公民科学民主化的平台,让更多的研究人员和参与者都能使用该平台。通过 SmartCS 平台,无需编码技能,就能快速创建具有 ML 支持的公民科学应用程序。使用 SmartCS 开发的应用程序具有客户端 ML 支持,即使在没有互联网连接的情况下也能在现场使用。客户端 ML 可帮助教育用户更好地识别研究对象,从而实现高质量的数据收集。我们将介绍几款使用 SmartCS 创建的公民科学应用程序,其中一些是由高中生构思和创建的。