This project deals with moving source control from GIT server to VMs using ansible. Moving assets in case we have intruder in our internal network(or subnet).
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Updated
Dec 5, 2019
This project deals with moving source control from GIT server to VMs using ansible. Moving assets in case we have intruder in our internal network(or subnet).
UnderGraduate Project based on the management of resources in the flood hit areas of Assam.
The Rescuer App is a crucial element of the FORUS (Focused Operational Research and Unified Systems) aimed at enhancing disaster response and management. This Flutter application ensures seamless communication between the public and rescuers during disasters, utilizing SMS for data transmission.
By developing this Disaster Response Classifier, the project aims to improve the efficiency and effectiveness of disaster response efforts by enabling quick and accurate identification of relevant messages, thereby facilitating targeted assistance and support to those in need during times of crisis.
Earthquake Magnitude Forecasting and Spatial Analysis uses machine learning approaches to forecast earthquake magnitudes based on past seismic data. It seeks to detect probable earthquake-prone regions by analysing numerous factors, including geographic coordinates, depth, and other pertinent data.
Sentinel-1 based TU Wien flood mapping workflow written using the openEO API and prepared for local processing.
The project aims to create a decentralized system for tracking donations based on blockchain technology built using ReactJS and WEB 3.0. This blockchain-based system facilitates the operations of donors, nonprofit organizations, and recipients by offering a transparent and safe platform.
Bibtex from the paper 'A Survey on Unmanned Surface Vehicles for Disaster Robotics: Main Challenges and Directions'
Official Source code for Unity simulation DROPEX (Disaster Rescue Operation and Probing using EXpert Drones).
Research is fun!
The idea for codefundo++, this project deals with locating trapped survivors during calamities using remote tracking devices
This is a model that I developed for the Master of Science course "Environmental modelling". I gave the course for 4 sessions at the Humboldt-Universität Berlin.
NASA space app challenge 2018 HACKATHON project
Machine learning model used to predict whether a tweet is about a real disaster or not.
Awarded "The Most Ground Breaking Solution" @ UNESCO Water Resilience Challenge 2024
Disaster location mapping and warning system
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