The Analysis of Resilientnet-Realtime Disaster Response System
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.
Authors
- Supriya Kamoji
- Heenakausar Pendhari
- Mathew Lobo
- Kris Corriea
- Hisbaan Sayed
- Omkar Satupe
Publication Details
- Journal
- INTI JOURNAL.
- Published
- 2024-11-01
- DOI
- https://doi.org/10.61453/jods.v2024no43
- Primary Topic
- Infrastructure Resilience and Vulnerability Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00