The Repository @ St. Cloud State

Open Access Knowledge and Scholarship

Date of Award

5-2024

Culminating Project Type

Starred Paper

Styleguide

apa

Degree Name

Criminal Justice: M.S.

Department

Criminal Justice

College

School of Public Affairs

First Advisor

Gilbertson, Douglas L

Second Advisor

Thea Baker

Third Advisor

Dick andzenge

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Keywords and Subject Headings

artificial intelligence (AI), Artificial neural network (ANN), Machine learning (ML), Unmanned aerial vehicle (UAV), Support vector machine (SVM), Internet of Things (IoT), Geographic information system (GIS)

Abstract

Based on peer-reviewed research, Artificial Intelligence (A.I.) and cloud-based collaborative platforms gather data in disaster response to present specific plans according to the complexities of emergencies (Gupta et al., 2022). The (RF) algorithm finds the elements influencing household evacuation preparation time (Rahman et al., 2021). A.I. and the cloud-based platform through (Crowdsourcing) coordinate humanitarian needs (Gupta et al., 2022). A.I. and cloud-based systems present the necessary information to emergency responders; the method also effectively assigns resources to respond (Gupta et al., 2022). Geo-AI disaster response makes precise information accessible to disaster responders by presenting accurate mapping analysis (Demertzis et al., 2021). A state-of-the-art deep-learning approach detects changes in satellite images for efficient response (Sublime & Kalinicheva, 2019). AGRA (A.I.), an augmented geographic routing approach, improves routing problems (Chemodanov et al., 2019). Early warning facilitates affected people's evacuation in disasters by applying the AI SVM to analyze the available data to make decisions with either (flood or no flood) for monitoring rooms (Al Qundus et al., 2022). A flood forecasting method that combines artificial neural networks (ANNs) and an Internet (IoT), as well as an ANN based on AI/Machine Learning (ML), works for an early flood warning system. Protecting vulnerable people from flood disasters by the integrated systems of artificial intelligence (A.I.) and machine learning (ML), Geographic Information System (GIS) with unmanned aerial vehicle (UAV) methods, and path-planning techniques for finding the safest evacuation route during a disaster (Munawar et al., 2022). A.I. with UNOSATs for advanced analysis of maps of the areas affected by disasters for early warning (Fusing AI into Satellite, 2021). Based on an online survey, different factors influence public perception of applying A.I. in disasters. Guidelines are presented for A.I. system users to ensure the system's responsibility. (Yigitcanlar et al., 2021).

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