The Analysis of Resilientnet-Realtime Disaster Response System

Supriya, Kamoji and Heenakausar, Pendhari and Kris, Corriea and Mathew, Lobo and Hisbaan, Sayed and Omkar, Satupe (2024) The Analysis of Resilientnet-Realtime Disaster Response System. Journal of Data Science, 2024 (43). pp. 1-16. ISSN 2805-5160

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Abstract

Responding to India's urgent need for effective disaster management, proposed framework ResilientNet, an innovative system leveraging real-time big data processing and advanced AI technologies. ResilientNet gathers diverse multimedia content from a wide range of social media services, including Twitter, Instagram, Facebook, etc., and utilises the GEMINI API, enabling comprehensive analysis and verification. Data is stored in the NEO4J database and visually represented on a user-friendly website dashboard for easy accessibility and insights. This research explores the efficacy of crowdsourced fact- checking, contributing to a novel disaster-focused tweet verification system. ResilientNet's amalgamation of crowdsourcing and AI creates a comprehensive graph of critical metrics and trends, enabling authorities to counter misinformation and direct disaster response efforts efficiently.

Item Type:	Article
Uncontrolled Keywords:	BERT, Disaster Management, Knowledge Graph, NEO4J Database, Tweet Classification and Verification
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > TD Environmental technology. Sanitary engineering
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	08 Nov 2024 04:14
Last Modified:	08 Nov 2024 04:14
URI:	http://eprints.intimal.edu.my/id/eprint/2025

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