Information and Communication Technologies (ICT) are becoming increasingly pervasive in urban environments and providing the necessary basis for sustainability and resilience of the smart cities. ICT solutions are being applied in smart mobility, energy, urban planning, socio-economic, health and environment application domains. ICT as the prime enabler for smart cities help in transforming city governance processes by making effective use of application specific information and knowledge. This unique possibility of realisation of smart cities is being enabled by smarter ‘Internet of Things’ (IoT) i.e. smart phones, sensor nets, smart household appliances, open data, crowd sourcing, etc., and making efficient use of ever increasing Big city data. Smart cities and its stakeholders can benefit from Big, and often real-time cross-thematic, data collection, processing, integration, visualisation and sharing through inter-operable information services. This certainly require adoption of existing or new standards in dealing with smart city data and services.

In the above context, the real value of smart city data is gained by new knowledge generation and by performing context based data processing and analytics using various data mining, machine learning or deep learning methods. This new knowledge can be used in improving the efficiency of existing city governance processes and effective policy making. The smart city data analytics for knowledge generation becomes challenging when applied to large scale or real time data and hence requires appropriate technology infrastructure e.g. software defined networks, tools, and techniques to be applied to process and generate required information without compromising privacy or security of data providers.