Engineering Democratization in Internet of Things Data Analytics

The pervasiveness of Internet of Things devices in techno-socio-economic domains such as Smart Cities and Smart Grids results in a massive scale of data about our society. Decision-making by system operators or policy-makers requires a sophisticated understanding of these data with real-time data analytics methods. However, common data analytics methods often serve exclusively corporate and commercial interests and result in privacy-intrusion, surveillance, profiling and discriminatory actions. This paper illustrates an alternative data analytics approach that relies on participatory citizens to contribute Internet of Things data and crowdsourced computational resources in order to compute aggregation functions in a collective fashion. This democratization calls for a fully decentralized and privacy-preserving system design with which a local data management mechanism implemented in smart phones can guarantee highly accurate computations under highly dynamic data streams. Experimental evaluation with real-world Smart Grid data illustrates the performance trade-offs and shows how they can be managed in an automated and empirical way using decision trees.