HazardAhead.ai

HazardAhead.ai

Inspiration

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.

What it does

This Project is about using 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 hazard is, it works in Mathematical Ways.

This project uses different technologies and real life data sources together, and show cases, how a Hazard can be predicted well in advance, so that preventive actions can be taken.

How we built it

Platform: TigerGraph, Oracle OCI, AWS, Google or Microsoft Azure data cloud. Data: Internet of things, vision, ocr, supply chain ERP systems Analytics: Jupyter NBs, Julia Lang, TigerGraph GSQL, Oracle Analytics Cloud Programming/Framework: Julia, FluxML, TigerGraph GSQL, TigerGraph ML

Challenges we ran into

Gathering, cleaning and wrangling data from reliable sources is the key to success to any project. We worked very hard in gathering, using quality data.

Accomplishments that we're proud of

This is one my dream projects, I can't believe, that It came this far and this is real project now. Predicting Hazards/Crime, can only be seen happening in movies or fiction novels. I am proud to take this first step in making this into a reality.

What we learned

Graph, Deep Learning, IOTs is the future.

What's next for HazardAhead.ai

I am very excited to take this project forward, I have already received tremendous interest from my 275+ followers in GitHub and Organizations, who are ready to contribute and take it forward.