Work

Conceptual Framework of an Intelligent Decision Support System for Smart City Disaster Management

Year: 2020

Type: article

Abstract: In order to protect human lives and infrastructure, as well as to minimize the risk of damage, it is important to predict and respond to natural disasters in advance. However, currently, the standardized disaster response system in South Korea still needs further advancement, and the response phase systems need to be improved to ensure that they are properly equipped to cope with natural disasters. Existing studies on intelligent disaster management systems (IDSSs) in South Korea have focused only on storms, floods, and earthquakes, and they have not used past data. This research proposes a new conceptual framework of an IDSS for disaster management, with particular attention paid to wildfires and cold/heat waves. The IDSS uses big data collected from open application programming interface (API) and artificial intelligence (AI) algorithms to help decision-makers make faster and more accurate decisions. In addition, a simple example of the use of a convolutional neural network (CNN) to detect fire in surveillance video has been developed, which can be used for automatic fire detection and provide an appropriate response. The system will also consider connecting to open source intelligence (OSINT) to identify vulnerabilities, mitigate risks, and develop more robust security policies than those currently in place to prevent cyber-attacks.

Source: Applied Sciences

DOI: 10.3390/app10020666

Authors: Daekyo Jung, Vu Tran Tuan, Dai Quoc Tran, Minsoo Park, Seunghee Park

Institution: Sungkyunkwan University

Language: English

Topic: Energy and Environmental Systems

Subfield: Transportation

Field: Social Sciences

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities, Climate action

Open Access status: gold

Estimated APC paid: $1,901