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2024 | OriginalPaper | Buchkapitel

A Wireless Emergency Alerts System for Warning Disasters by Using Distributed Databases, GPS and Machine Learning Enabled API Services

verfasst von : Md. Abdullah Al Mamun, Md. Tanvir Miah Shagar, Meher Durdana Khan Raisa, Md. Jubayer Hossain, Utsa Chandra Sutradhar, S. Rayhan Kabir, Anupam Hayath Chowdhury, Mohammad Kamrul Hasan

Erschienen in: Computing, Internet of Things and Data Analytics

Verlag: Springer Nature Switzerland

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Abstract

As most disasters are weather-related, location tracking is crucial during any event, and early warning systems can save lives. This article outlines the design and execution of a wireless emergency alerts model for catastrophic alerting based on data from distributed databases by using machine learning enabled Application Programming Interface (API) services. Using machine learning-based historical and current data from the NASA Open API and OpenWeatherMap API, this program is intended to forecast natural catastrophes and aid in their management. To forecast future disasters, the application analyses data from previous natural disasters, including floods, wildfires, tornadoes, cyclones, and hurricanes. Additionally, it gives users access to GPS (Global Positioning System) based evacuation routes and emergency shelter information. The purpose of this article is to assist individuals in the lead-up, during, and aftermath of a disaster by providing access to important resources and information. The software serves as a daily catastrophe management tool, notifying users of the most recent disasters and letting them know whether an incident is happening right now using machine learning-based data. This application can be an important tool to help individuals from disaster.

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Titel: A Wireless Emergency Alerts System for Warning Disasters by Using Distributed Databases, GPS and Machine Learning Enabled API Services
verfasst von: Md. Abdullah Al Mamun
Md. Tanvir Miah Shagar
Meher Durdana Khan Raisa
Md. Jubayer Hossain
Utsa Chandra Sutradhar
S. Rayhan Kabir
Anupam Hayath Chowdhury
Mohammad Kamrul Hasan
Verlag: Springer Nature Switzerland
Buch: Computing, Internet of Things and Data Analytics
Print ISBN: 978-3-031-53716-5

Electronic ISBN: 978-3-031-53717-2

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-3-031-53717-2_22

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