Open Access

Aadesh Misra

• The topic for the thesis originated from the CAP4ACCESS project run by the European Commission and its partners, which deals towards the sensiti-zation of people and development of tools for awareness about people with movement disabilities. The explorative analysis is never ending and to explore and find interest-ing patterns and the results is a tedious task. Therefore, a scientific approach was very important. To start with, familiarizing the domain and the data sources were done. Thereafter, selection of methodology for data analysis was done which resulted in the use of CRISP-DM methodology. The data sources are the source of blood to the analysis methodology, and as there were two sources of data that is MICROM and OSM Wheelchair History(OWH), it was important to integrate them together to extract relevant datasets. Therefore a functional and technically impure data warehouse was created, from which the datasets are extracted and analysed.The next task was to select appropriate tools for analysis. This task was very important as the data set although was not big data but con-tained a large number of rows. After careful analysis, Apache spark and its machine learning library were utilized for building and testing supervised models. DataFrame API for Python, Pandas, the machine learning library Sci-kit learn provided unsupervised algorithms for analysis, the association rule analysis was performed using WEKA. Tableau[21] and Matplotlib[24] provide attractive visualizations for representation and analysis.