Divya Pullarkatt
Amrita Vishwa Vidyapeetham
9 Papers
19 Citations
Divya Pullarkatt is an academic researcher from Amrita Vishwa Vidyapeetham. The author has contributed to research in topics: Landslide & Computer science. The author has an hindex of 3, co-authored 8 publications.
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Papers
Towards establishing rainfall thresholds for a real-time landslide early warning system in Sikkim, India
TL;DR: In this article, the authors derived the rainfall thresholds for landslides based on the daily rainfall data available from India Meteorological Department (IMD) for six stations in Sikkim.
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Use of Social Media Data in Disaster Management: A Survey
Jedsada Phengsuwan,Tejal Shah,Nipun Balan Thekkummal,Zhenyu Wen,Rui Sun,Divya Pullarkatt,Hemalatha Thirugnanam,Maneesha Vinodini Ramesh,Graham Morgan,Philip James,Rajiv Ranjan +10 more
TL;DR: In this article, a survey of how social media data contribute to disaster management and the methodologies for social media management and analysis in disaster management is provided. But to the best of our knowledge, there is no published literature that identifies the research problems and provides a research taxonomy for the classification of the common research issues.
Wireless Sensor Networks for Early Warning of Landslides: Experiences from a Decade Long Deployment
Maneesha Vinodini Ramesh,Divya Pullarkatt,T. H. Geethu,P. Venkat Rangan +3 more
- 29 May 2017
TL;DR: The results from the experimentation shows this system has contributed in enhancing the reliability of landslide warning, reduced false alarm rate, and provides the capability to issue warnings in local, slope and regional levels.
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Machine Learning based Classification of Online News Data for Disaster Management
Lakshmi S. Gopal,Rekha Prabha,Divya Pullarkatt,Maneesha Vinodini Ramesh +3 more
- 29 Oct 2020
TL;DR: In this paper, a data scraping approach is proposed to gather hazard relevant news stories from the web by building a crawler software and incorporating machine learning approaches to filter out insightful information.
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Context-Based Knowledge Discovery and Querying for Social Media Data
Jedsada Phengsuwan,Nipun Balan Thekkummal,Teja Shah,Philip James,Dhavalkumar Thakker,Rui Sun,Divya Pullarkatt,T. Hemalatha,Maneesha Vinodini Ramesh,Rajiv Ranjan +9 more
- 01 Jul 2019
TL;DR: A data integration and analytics system which allows social media users to contribute to hazard monitoring and supports decision making for its prediction and prototype the system using landslides as an example hazard is prototype.
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