Published April 27, 2026
| Version v1
Journal article
Open
Real Time Disaster Information Aggregation Software
Authors/Creators
- 1. Jayaraj Annapackiam CSI College of Engineering
- 2. Jayaraj Annapackiam CSI College of Engineering
Description
Natural disasters like earthquakes and floods require quick and accurate information for effective response. Traditional systems are reliable but often slow. Social media platforms such as Twitter and YouTube provide real-time updates, but filtering useful information is challenging. This system collects and analyzes disaster-related data using APIs, keyword filtering, and natural language processing, then sends verified alerts to users via SMS using the Twilio API.
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Additional details
References
- Research shows that social media can be effectively used for disaster detection and management, as highlighted by M. Atefeh and A. Imran. Studies such as J. P. Singh et al. (2019) and S. Goswami (2020) focus on event classification, location prediction, and NLP-based tweet analysis. Overall, works by S. Kumar et al. (2022) and A. Hernandez-Suarez et al. (2019) show that machine learning improves real-time disaster response.