A Flash Flood Categorization System Using Scene-Text Recognition
A Flash Flood Categorization System Using Scene-Text Recognition
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DOI：
10.1109/smartcomp.2018.00085
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发表时间：
2018-06
期刊：
影响因子：
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通讯作者：
Bipendra Basnyat;Nirmalya Roy;A. Gangopadhyay
中科院分区：
文献类型：
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作者：
Bipendra Basnyat;Nirmalya Roy;A. Gangopadhyay
实时检测山洪暴发并采取快速行动对于挽救智慧城市中的人类生命、基础设施损失和个人财产至关重要。在本文中，我们开发了一个低成本低功耗的网络物理系统原型，使用树莓派相机来检测水位上升。我们将系统部署在真实的世界中，并在不同的环境条件下（清晨有雾，晴朗的下午，傍晚日落）收集数据。我们采用图像处理和文本识别技术来检测水位上升，并阐明了在真实的环境中部署这样一个系统的几个挑战。我们设想这种原型设计将为大规模部署山洪检测系统铺平道路，最大限度地减少人为干预。
Detecting flash floods in real-time and taking rapid actions are of utmost importance to save human lives, loss of infrastructures, and personal properties in a smart city. In this paper, we develop a low-cost low-power cyber-physical System prototype using a Raspberry Pi camera to detect the rising water level. We deployed the system in the real word and collected data in different environmental conditions (early morning in the presence of fog, sunny afternoon, late afternoon with sunsetting). We employ image processing and text recognition techniques to detect the rising water level and articulate several challenges in deploying such a system in the real environment. We envision this prototype design will pave the way for mass deployment of the flash flood detection system with minimal human intervention.