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A Privacy Preserving Framework for Smart Cities utilising IoT, Smart Buildings and Big Data

There are many possibilities for a smart city that is enabled with smart buildings and well provisioned and managed internet of things (IoT) frameworks. The benefits of such frameworks can be felt in multiple domains. On planning an integrated city, data captured from the infrastructures within a city can be analyzed and utilized for effective resource and services provisions within the city. In urban mobility, automated planning and demand responsive to public transportation integrated with self-driven vehicles. On safety, security and health of cities and their citizens, real-time surveillance and analytics can lead to better provision of emergency services, weather planning, early warnings on floods, tornadoes, man-made disasters and pandemics. To facilitate such services requires frameworks that can be effective at acquisition, processing and analysis of large volumes of data from vast systems as well as citizens within a city while preserving the security and privacy of data sources.In this paper, (a) a brief overview on the current landscape on smart cities is provided, the architectures and frameworks proposed to support data management, (b) highlights research opportunities that are still open, (c) proposes a privacy preserving computation framework that can be explored for a robust smart city ecosystem (d) and outlines the benefits possible with such a proposed framework.