Data flows generated by people, using smart devices and ubiquitous connectivity, and machines are the next step towards establishing truly smart cities. The City of Johannesburg has several of the components necessary to establish smart city systems and machine systems are the next step, says information and communication technology firm T-Systems South Africa Intervate head Lionel Moyal.

The city has several citizen engagement and reporting tools that help it to identify traffic and road problems – such as potholes, toppled poles or trees and nonfunctioning traffic lights – and is also aiming to make its electricity grid systems and components smart. Similar location-based reporting pilot programmes are in progress in the areas of waste management and community security forums.

“These examples are something of a portent. If step one is all about human-generated data, then step two will involve integrating machine-generated data – such as from connected sensors, meters, cameras and devices – with the human-generated data flows,” says Moyal.

In step two, sophisticated algorithms interpret these various data sources – from sensors, came- ras or any other kind of connected device – and produce useful insights for citizens. For example, an Internet Protocol camera can record the density of people waiting at a bus terminal and translate the information into likely waiting time for people heading to the terminal.

These information flows generated by analytics engines can then be used to provide a rich variety of applications for citizens and businesses and capabilities for the city.

“With rich flows of human- and machine- generated data, city authorities and administrators get an accurate view of the services under their control and the issues facing citizens. This forms the basis for improved decision-making – from budgeting decisions, public transport planning and traffic management strategies to policing issues,” he explains.

However, step three is a number of years away, despite the encouraging progress. Ubiquitous smartphone penetration and the proliferation of free urban WiFi networks are required for the third step to smart cities, but the bigger infrastructure and environmental requirements will likely become a reality only within the next few years, avers Moyal.

“Step three requires the mass-scale adoption of citizen reporting and engagement tools, a wide array of smart city services across many areas of service delivery, departments and city authorities and big data insights that are processed by sophisticated systems using machine learning.

“In this way, the flood of incoming data is handled in real time by processing systems. “These systems can dynamically alter the timing of traffic lights, the schedules of maintenance and sanitation crews, the dispatching of emergency teams, the routings of trains and buses or just about any other form of smart city service,” he enthuses.

The logical sequence and incre- mental steps towards the development of smart city systems will help South Africa learn the optimal ways of configuring its smart city systems as it progress to achieve the vision of smart cities, concludes Moyal.