The synergy of linguistic summaries, fuzzy functional dependencies and land coverings for augmenting informativeness in smart cities

Searching for hidden information in data is a complex task. The two main aspects are asking questions and interpreting the results, preferably linguistically, as applicable in many fields, including smart cities. This work integrates linguistic summaries in aggregating the examined features of entities, classifying and calculating land coverings, and fuzzy functional dependencies in revealing dependencies between the summarized sentences and percentages of categories of objects in districts. The proposed approach is experimentally illustrated and explained.