In its simplest, raw form, the data can be used directly to control whether street lights are turned on/off or to monitor. Display the position of a vehicle with a GPS locator. However, the use of analytical tools and knowledge management systems can convert this raw data into information and knowledge that can then be acted upon, traffic information systems are good examples of this. This can be further enhanced with workflow management and bespoke algorithms to make autonomous or semi-autonomous decisions. An example would be a traffic management system that dynamically controls the traffic flow based on data received from sensors monitoring traffic flow, speeds, road conditions, video etc. and uses this to modify traffic light sequencing, speed limits, lane allocation and route alternatives. This could be further enhanced by adding intelligent systems able to learn from previous experiences, allowing lane sequencing on a smart highway (ie. How lanes in each direction at a given time of day).
As we move from information and control-based systems to knowledge and learning-based systems, will see distinct systems sharing knowledge and understanding with each other. The smart city is a great example of this and we already see projects around Smart Tourism and use of integrated public/private transport and parking to attract consumers to shops in town centres.

Why Is Smart so Popular and Relevant in Strategic Industries?
SCADA systems (supervisory control and data acquisition) are and have been used by strategic industries for over 50 years now. SCADA is used to gather data in real-time from remote locations and then feed this data back to a control system which then uses this data to control equipment and conditions.

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