The continued urbanization is an unstoppable trend, which drives existing cities to enlarge themself and become bigger, increasing simultaneously their scalability problems. In this extension trend, we need to find a way to manage this novel complexity to increase efficiency and to reduce expenses of a smart and sustainable city, to improve the quality of life of its citizens. Since our cities are becoming bigger and bigger, they need to become even smarter. Smarter, in a city context, means to be able to monitor, analyse, and foresee city behaviours by interpreting information and consequentially, to provide better services and an easier and safer life to citizens. This new concept of city starts from the assumption that everything is usable to provide information: citizen mobiles, traffic sensors, monitoring stations, public transportation, and so on; all those can be integrated to provide complete description of city environments, to foresee new tendencies and even influence future behaviours.
Our goal is to provide a way to merge all these real-time heterogeneous information together, for better and more complete services, to transform our cities into smarter ones. To tackle these problems, we have focused on a novel prototype to ease real-time decision-making processes for the City of Dublin with three main original technical aspects:
DubExtensions language an extension of SPARQL to support efficient querying of heterogeneous streams;
query execution framework and runtime environment based on IBM InfoSphere Streams, a high-performance, industrial strength, stream processing engine;
hybrid RDFS reasoner optimized for our stream processing execution framework.
This work have been realised in collaboration with IBM Research Dublin and it is part of a larger project of research on Smarter Cities.