Speeding up children reunification in disaster scenarios via serverless computing
Speeding up children reunification in disaster scenarios via serverless computing
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通过无服务器计算加速灾难场景中儿童的团聚
DOI：
10.1145/3154847.3154851
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Charney, Rachel
中科院分区：
文献类型：
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作者：
Coleman, Kyle;Esposito, Flavio;Charney, Rachel
儿童是弱势群体，需要特别考虑，以便在灾害期间为他们提供适当的照顾。在卡特里娜飓风等灾难发生后，必须迅速查明和保护失散儿童，并使他们与法定监护人团聚，以最大限度地减少二次伤害(即身体和性虐待、忽视和绑架)。在路易斯安那州因卡特里娜飓风而流离失所的俄克拉何马州收容所格鲁伯营地，70%的儿童在2周后与法定监护人团聚，而最后一个孩子在6个月后团聚。在这个项目中，我们使用无服务器计算来扩展和最小化数据库查询响应时间，并加快机器学习任务的速度，以实现快速团聚，以支持联合的第一响应人员集。特别是，我们正在使用一个基于FlaskWeb的系统，该系统利用ApacheOpenWhisk在后端运行(人脸和文本)配置文件识别软件。
Children constitute a vulnerable population and special considerations are necessary in order to provide proper care for them during disasters. After disasters such as Hurricane Katrina, the rapid identification and protection of separated children and their reunification with legal guardians is necessary to minimize secondary injuries (i.e., physical and sexual abuse, neglect and abduction). At Camp Gruber, an Oklahoma shelter for Louisianan's displaced by Hurricane Katrina, 70% of the children were with their legal guardian after 2 weeks while the last child was reunified after 6 months.In this project, we are using serverless computing to scale and minimize database querie response time as well as to speed up machine learning tasks for rapid reunifying time, in support of a federated set of first-responders. In particular, we are using a Flask-based web system that leverages Apache OpenWhisk to run both (face and text) profile recognition software at the back-end.