A Graph AI which predicts Hazards ahead.

Who should read this: IT developers, Healthcare, law enforcement agencies, Event management authorities

start here:-> https://amitxshukla.github.io/HazardAhead.ai

Complete source code/example notebooks are executed & included in documentation published under GitHub gh-pages branch.

Frontend: Julia, Flutter, Olive AI
Backend: Tiger Graph DB
Rest API: Julia, TGCloud RESTAPI
AI: TigerGraph ML, Julia, Fluxml.ai, H2O.ai, Oracle AutoML

Predicting danger, crime, distractions, hazards before it happens. Ability to predict danger, hazards and distractions in advance before they do any damage is no longer a distant fantasy. Subject of surveillance has shown world new ways of predicting hazards ahead.

This book is about Data Science, Graph Analysis to understand data pattern in crowd gatherings, making use of climate, supply chain, behavior archives of criminological data to understand what causes hazards. HazardAhead.ai demonstrates how to construct predictive algorithms to aid in the search for hazardous, danger, distractions and criminal activity.

One great aspect of hazards is, it Work in Mathematical Ways.

This notebook is dedicated to show examples, that using different technologies together, how a Hazard can be predicted well in advance, so that preventive actions can be taken.

Problem Statement Hazards are everywhere, and often completely unpredictable. But recent advancements in AI, ML Models, Scientific Neural network deep learning methods and advance use of mathematics like calculus enabled us to use these technologies learn design and data pattern which can be used to analyze, visualize, and further train machine learning models to predict certain events.

When I think about Impact using Graph technologies, I'm sure, these technologies will be able to make meaningful predictions which are useful to crowd/event management and is very helpful to the places and people who want to use Graph technologies in event management.

I have seen researcher using Graph technologies to predict supply chain in retail industry. Graph technologies are certainly useful, where events depends entity and their relationship, like Power Industries or healthcare industry. However, I have not seen much applications of using Graph in Law n Order, Hazard, Crowd/Event management area.

HazardAhead.ai uses extremely complex graph and data algorithms. This is lot of work to first identify, design solution pattern, gathering meaningful data. Cleaning and Wrangling huge amount of variety of data formats from different data sources. HazardAhead.ai needs powerful GPU clusters to train on Petabytes of data.

https://raw.githubusercontent.com/AmitXShukla/HazardAhead.ai/main/LICENSE

https://raw.githubusercontent.com/AmitXShukla/HazardAhead.ai/main/LICENSE