Big IoT and social networking data for smart cities: Algorithmic improvements on Big Data Analysis in the context of RADICAL city applications

In this paper we present a SOA (Service Oriented Architecture)-based, enabling the retrieval and analysis of big datasets stemming from networking (SN) sites and Internet of Things (IoT) devices, collected by city applications and socially-aware data aggregation services. A large of city applications in the areas of Participating Urbanism, Augmented and Sound-Mapping throughout participating cities is being applied, into produced sets of millions of user-generated events and online SN fed into the RADICAL platform. Moreover, we study the application of analytics such as sentiment analysis to the combined IoT and SN data saved an SQL database, further investigating algorithmic and configurations to delays in dataset processing and results retrieval.