The challenge before Smart City planners is to find ways to analyse the massive data that would be gathered through Internet of Things with the need to process   billions or more data points each second.

By deploying sensors and network connectivity to everyday physical objects like cars, refrigerators, television and buildings, it is possible to remotely connect, manage and engage with these entities in ways that are not possible today, analysts say.

The prospects for IoT in government will provide a great deal of benefits to citizens, for example smart traffic management. Internet-enabled devices can monitor traffic movements and can smartly administer lanes to ease congestion.

When IoT becomes mainstream, there should be sufficient infrastructure to deal with Big Data. Both IoT and Big Data are essentially two sides of the same coin – like Big Data, the solution to a successful IoT implementation lies in storing, processing and extracting value from the data received.

What is needed is smart infrastructure that can process data in transit as well as optimise resources through prescriptive platform analytics and active copy analytics.

Such an infrastructure could use machine learning algorithms to dynamically allocate the resources required to back up job processes, monitor services and produce output for the user.