Intelligent services for Big Data science

• Analysis of challenges and requirements for next-generation Big Data services.
• CAPIM is a platform to collect and aggregate context information on a large scale.
• Present the implementation of an Intelligent Transportation System on top of CAPIM.
• Context-Aware Framework is designed to handle efficient storage of context data.
• Such Big Data services show different mechanisms to cope with identified challenges.

Cities are areas where Big Data is having a real impact. Town planners and administration bodies just need the right tools at their fingertips to consume all the data points that a town or city generates and then be able to turn that into actions that improve peoples’ lives. In this case, Big Data is definitely a phenomenon that has a direct impact on the quality of life for those of us that choose to live in a town or city. Smart Cities of tomorrow will rely not only on sensors within the city infrastructure, but also on a large number of devices that will willingly sense and integrate their data into technological platforms used for introspection into the habits and situations of individuals and city-large communities. Predictions say that cities will generate over 4.1 terabytes per day per square kilometer of urbanized land area by 2016. Handling efficiently such amounts of data is already a challenge. In this paper we present our solutions designed to support next-generation Big Data applications. We first present CAPIM, a platform designed to automate the process of collecting and aggregating context information on a large scale. It integrates services designed to collect context data (location, user’s profile and characteristics, as well as the environment). Later on, we present a concrete implementation of an Intelligent Transportation System designed on top of CAPIM. The application is designed to assist users and city officials better understand traffic problems in large cities. Finally, we present a solution to handle efficient storage of context data on a large scale. The combination of these services provides support for intelligent Smart City applications, for actively and autonomously adaptation and smart provision of services and content, using the advantages of contextual information.