There are 1 repository under early-warning-systems topic.
The spider crawls moneycontrol.com and economictimes.com to fetch news of input companies and also scores and classifies the companies to raise an early warning signal
Fraud Detection for VoIP. Use SentryPeer® HQ to help prevent VoIP cyberattacks and fraudulent VoIP phone calls (toll fraud) at https://sentrypeer.com
Source code for NodeMCU seismometers for SeismoCloud project
CAP (Common Alerting Protocol) XML alert format parsing, HTML parsing, inserting new alerts into database, OneSignal (possible Android and iOS push notifications), Twitter, Facebook, MailChimp (e-mail notifications) for project of open source solution for natural disasters early-warning.
Research on developing a new method for determining the warning time of Early Warning Signals. Also an attempt at removing window size uncertainty from EWS analysis
An early warning platform POC built during International Space Apps Challenge 2016
Design e Sviluppo del sistema di End User Development in SeismoCloud - Laurea Triennale in Informatica UniversitĂ Sapienza di Roma
Codes for Beutel, List and von Schweinitz (JFS, 2019)
Prediction of Dengue Outbreaks Based on Disease Surveillance and Meteorological Data
This is a repository that integrates XBeach with FEWS. It is still under active development
Methods for Advance Detection of COVID-19.
Rain gauge selection tool for rainfall threshold analysis
early warning system for fiscal stress
Locust Early Warning System(loews) project implementation(Locally)
Quake Safe Rings (QuaSaR) contains various tools to support Earthquake Early Warning (EEW) projects
Data and Code for replicating the World Development paper "A Data-Driven Approach Improves Food Insecurity Crisis Prediction"
VSPsnap is a collection of R and Python code for Gaussian Process regression in a kriging-like setting (i.e. two features (X,Y) and a target (Z)) - with a focus on SARS-CoV2 data (genomic/IR/FR).
Node programs
Python code implementation for the paper 'The Epidemic Forest: Unveiling the Spatial Dynamics of Acute Respiratory Infections Spread in Jakarta, Indonesia.'
These are files associated with the prediction of aflatoxin risk levels in maize using various ensemble and non-ensemble machine learning methods in east and southern Africa countries
This project was made as a part of the 'NASA Space apps challenge-2021' where the challenge my team and I chose was 'Measuring the value of Earth Observations'.
Disaster location mapping and warning system
Japan Meteorological Agency Earthquake API Client
This repository contains models trained for various purposes during my summer internship at Optical Networks and Technologies Lab.
Objective: This project is a Flood Prediction Model that leverages machine learning techniques to predict the likelihood of flood events in specific regions based on historical weather data. The model can be used by municipalities, researchers, or environmental agencies to assess flood risks and implement preventive measures.