84 results for “topic:early-warning-systems”
Introduction to OpenEEW, an open-source Earthquake Early-Warning toolkit
General Purpose Risk Modeling and Prediction Toolkit for Policy and Social Good Problems
ECDC Early warning tool using social media data.
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
A systems-thinking essay that explains why failure rarely happens suddenly. It shows how slow drift, accumulating pressure, and weakening buffers push systems toward collapse long before outcomes change, and why prediction-focused analytics miss the most important phase of failure.
Open Source Content Management System for National Meteorological and Hydrological Services
A systems-thinking essay that reframes failure as a gradual transition rather than a discrete outcome. It explains how pressure accumulation, weakening buffers, and hidden instability precede visible collapse, and why prediction-based models arrive too late to prevent failure in human-centered systems.
An interpretable battery health engine that detects hidden points of no return instead of just predicting health %. It models stress, buffer, and degradation intensity, discovers Stable/Drifting/Irreversible regimes via GMM, and learns simple Decision Tree thresholds, with a Streamlit app for diagnostics and what-if scenarios.
A systems-thinking essay arguing that most optimization quietly trades away buffers, slack, and resilience to make present metrics look better. It reframes efficiency as borrowing stability from the future, and shows how education, workforce, infrastructure, markets, and hardware all get optimized into fragility.
An early-warning system that models disasters as instability transitions rather than isolated events. It combines force-based instability modeling with an interpretable ML escalation-risk layer to detect when hazards become disasters due to exposure growth, response delays, and buffer collapse.
A long-form systems essay arguing that most metrics fail because they measure outcomes instead of accumulated pressure. It reframes collapse as a consequence of debt, buffer depletion, and delayed feedback, and explains why early warning depends on measuring pressure rather than predicting final events.
No description provided.
An interpretable early-warning engine that detects academic instability before grades collapse. Instead of predicting performance, it models pressure accumulation, buffer strength, and transition risk using attendance, engagement, and study load to explain fragility and identify high-leverage interventions.
A long-form systems essay arguing that machine learning fails when used as an automated decision-maker in unstable environments. It reframes ML as an early-warning instrument that exposes pressure, instability, and shrinking intervention windows, preserving human judgment instead of replacing it with late, brittle decisions.
A systems-level analysis engine that models sleep as a recovery debt process rather than a nightly outcome. Using physiological traits and ecological pressure signals, it estimates predicted sleep need, quantifies sleep debt, and visualizes how stress accumulates silently before visible fatigue or failure occurs.
Source code for NodeMCU seismometers for SeismoCloud project
CAP Alerts composer, communication and dissemination tool
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.
A configurable code modifier for typescript and friends. Can transform entire codebases to enforce better coding practices, eliminate tech debt in one fell swoop, and catch bad code before it is committed.
Early Warning System(EWS) for natural disasters
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
No description provided.
An early warning platform POC built during International Space Apps Challenge 2016
An integrated MATLAB–ML system for early fault detection in induction motors. Detects six faults broken rotor bars, stator short, ground fault, overloading, eccentricity, and voltage imbalance using KNN and Decision Tree models for accurate, unified, and reliable predictive maintenance.
Design e Sviluppo del sistema di End User Development in SeismoCloud - Laurea Triennale in Informatica Università Sapienza di Roma
Prediction of Dengue Outbreaks Based on Disease Surveillance and Meteorological Data
Codes for Beutel, List and von Schweinitz (JFS, 2019)
Rain gauge selection tool for rainfall threshold analysis
Methods for Advance Detection of COVID-19.