Journal article
An intelligent system on knowledge generation and communication about flooding
Environmental modelling & software : with environment data news, Vol.108, pp.51-60
10/2018
DOI: 10.1016/j.envsoft.2018.06.003
Abstract
Communities are at risk from extreme events and natural disasters that can lead to dangerous situations for residents. Improving resilience by helping people learn how to better prepare for, recover from, and adapt to disasters is critical to reduce the impacts of these extreme events. This project presents an intelligent system, Flood AI, designed to improve societal preparedness for flooding by providing a knowledge engine that uses voice recognition, artificial intelligence, and natural language processing based on a generalized ontology for disasters with a primary focus on flooding. The knowledge engine uses flood ontology to connect user input to relevant knowledge discovery channels on flooding by developing a data acquisition and processing framework using environmental observations, forecast models, and knowledge bases. The framework’s communication channels include web-based systems, agent-based chatbots, smartphone applications, automated web workflows, and smart home devices, opening the knowledge discovery for flooding to many unique use cases.
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•Development of an artificial intelligence system for flood-related natural language questions.•Use of custom ontologies to integrate domain knowledge.•Development of a knowledge engine as a software-as-a-service application.•Integration of many communication channels for the use of the knowledge engine.
Details
- Title: Subtitle
- An intelligent system on knowledge generation and communication about flooding
- Creators
- Yusuf Sermet - University of IowaIbrahim Demir - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Environmental modelling & software : with environment data news, Vol.108, pp.51-60
- DOI
- 10.1016/j.envsoft.2018.06.003
- ISSN
- 1364-8152
- eISSN
- 1873-6726
- Publisher
- Elsevier Ltd
- Grant note
- DOI: 10.13039/100008893, name: University of Iowa
- Language
- English
- Date published
- 10/2018
- Academic Unit
- Electrical and Computer Engineering; Civil and Environmental Engineering; IIHR--Hydroscience and Engineering; Injury Prevention Research Center
- Record Identifier
- 9984197293002771
Metrics
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