This document deals with the creation of descriptive models from the GES3 aforementioned data sources, in order to understand the dynamics of traffic and transportation public services in Brazilian cities. Furthermore, it describes the elaboration of a toolbox containing descriptive models, their implementation, deployment and application on the smart cities context
Models applies a specific set of data mining and machine learning unsupervised techniques clustering, association rules, feature extraction and common used summarization and aggregation of data. Results from Task 7.3 are the first ones using the GES3 data and computation intensive algorithms. Thus, implemented code has been used as a proof-of-concept in differents WPs to, for example, evaluate infrastructure, expressiveness of programming abstractions, identification of security and privacy concerns and in the realization of the use cases. Next steps include integration (indirectly) with resource allocation and evaluation of workload and improvements in the implementation. Together with Task 7.4, Task 7.3 will provide the toolbox needed to implement the complex analytics scenarios of Routes for People Use Case (Task 7.5).