reex2014 – a Rule Engine EXercise for 2014

I’m a Computer Science Engineer and I do believe there is a whole new range of unexplored applications for Expert Systems (AI) in Big Data scenarios, also within the Corporate business. You can read more about me on my LinkedIn profile.

I’ve found interest in Rule Engine applications while studying at University, and since, this has grown as a kind of NERD interest also on a personal perspective.

This is the reason every year I attempt an hobby-project where I can find an interesting application.

The theme I’ve chosen for this year 2014, is to solve a very practical problem: monitor data sources and social media for potential public transport issues, which I use for commuting. From a technological perspective, I’ve also wanted to seize a chance to experiment integrating several technologies.

In summary


  • Monitor data sources and social media for potential public transport issues
  • Use Expert Systems (AI) – Rule Engine (Drools)
  • Experiment for integration of other technologies with Java EE: like PaaS (OpenShift), Camel, Android


  • This is not an exercise of Sentiment analysis nor of Natural language processing
  • This is not an exercise to imitate other more complex systems for public transport information communications

Analyze RSS feed

Detect strike warning alerts from RSS stream, and others.


Analyze Twitter feed

Detect alerts for:

  • Several tweets for a specific of the different metro lines
  • Metro delays
  • Service interruptions

and others.


Android widgets

Distinct widgets for:

  • List display all Alerts
  • Display summary of inferred knowledge

with Settings page.


Source Code

The source code of this project is on github


This reex2014 project is NOT affiliated with, endorsed, or sponsored by any of the source of information which is connected to. This work has, instead, been created for demonstration of technological integration.

All trademarks of their respective owners.