Camera-First Form Filling: Reducing the Friction in Climate Hazard Reporting
Camera-First Form Filling: Reducing the Friction in Climate Hazard Reporting
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相机优先的表格填写：减少气候灾害报告中的摩擦
DOI：
10.1145/3597465.3605218
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Nandi, Arnab
中科院分区：
文献类型：
--
作者：
Wolf, Kristina;Winecki, Dominik;Nandi, Arnab
有效报告诸如山洪暴发、飓风和地震等气候灾害是至关重要的。为了快速、正确地评估情况和部署资源，应急服务往往依赖于必须及时、全面和准确的公民报告。智能手机摄像头的普及和使用使公民能够近乎实时地传输动态事件信息。虽然高质量的报告是有益的，但生成这样的报告可能会给已经遭受与气候有关的灾难压力的公民带来额外的负担。此外，由于报告方法的长度和复杂性，报告方法的使用往往具有挑战性。在这篇文章中，我们探索通过自动化表格填写过程的部分来减少气候灾害报告的摩擦。通过建立现有的计算机视觉和自然语言模型，我们演示了从一张照片自动生成完整形式的危险影响评估报告。我们建议的数据管道可以与现有系统集成，并与地理空间数据解决方案(如洪水风险地图)一起使用。
The effective reporting of climate hazards, such as flash floods, hurricanes, and earthquakes, is critical. To quickly and correctly assess the situation and deploy resou rces, emergency services often rely on citizen reports that must be timely, comprehensive, and accurate. The pervasive availability and use of smartphone cameras allow the transmission of dynamic incident information from citizens in near-real-time. While high-quality reporting is beneficial, generating such reports can place an additional burden on citizens who are already suffering from the stress of a climate-related disaster. Furthermore, reporting methods are often challenging to use, due to their length and complexity. In this paper, we explore reducing the friction of climate hazard reporting by automating parts of the form-filling process. By building on existing computer vision and natural language models, we demonstrate the automated generation of a full-form hazard impact assessment report from a single photograph. Our proposed data pipeline can be integrated with existing systems and used with geospatial data solutions, such as flood hazard maps.
Transformer：一种数据库驱动的方法，用于生成约束交互的表单
DOI：
10.1145/3301275.3302269
发表时间：
2019
期刊：
Proceedings of the 24th International Conference on Intelligent User Interfaces
影响因子：
--
作者：
Protiva Rahman;Arnab Nandi
通讯作者：
Arnab Nandi
人工智能支持公民科学监测加利福尼亚州纽波特海滩的涨潮洪水
DOI：
--
发表时间：
2020
期刊：
ARIC@SIGSPATIAL
影响因子：
--
作者：
Behzad Golparvar;Ruoqian Wang
通讯作者：
Ruoqian Wang