We are living in the data era. More and more devices are connected to the Internet. That produces more data which, in turn, are the source of new insights and applications. “We have historical big data, which we have collected in the past”, says Jan Sonck. “In addition, we have more and more real-time big data. That’s data available at the actual moment in time, which we process and then feed back the output straight away.”
The learning experience that comes from historical and real-time big data opens the way to predictive big data. “That makes it possible, for instance, to predict the intensity of traffic problems fairly accurately, on the basis of historical data on traffic jams at specific locations, on working days, during holiday periods, etc., combined with real-time data on the weather and accidents, among other things.”
This brings us to the field of artificial intelligence. To put it simply, this is a succession of automated decisions taken by a computer, on the basis of previous experiences that the computer has acquired. The first applications of this are to be found, in the world of the Internet of Things (IoT). In practical terms, this involves the use of an intelligent reasoning engine: a system that feeds back each new experience and includes it when the next decision is taken.
For instance: a street that is liable to flooding has a sensor. The system knows that a given water level, it has to send a message to the fire service. Depending on the weather forecast – how much more rainfall will there be ? – this happens at different times. Sonck: “The system learns afterwards, too, from the result of the intervention. So the next time – depending on the circumstances – it can send a smaller or bigger team to the site.”
The use of artificial intelligence also offers a great many possibilities for the new way of working. A tool to book a meeting room can decide itself which locations offer the best solution for the participants. “Analyzing the Wi-Fi use on the company network usually provides a good source of insight,” says Sonck. “With this data it is easy to determine where, when and how many people are working there.
And there’s more: thanks to artificial intelligence, the system can also accurately predict the level of occupation of the offices. Suppose a company wants to rearrange the ways its buildings are used to improve cooperation among colleagues. A system like this offers a suitable solution.”
The predictive nature of the solution, in particular, makes the difference. “We have a great many IoT partners who are active in fleet management,” Sonck explains. “These days they use the data for time recording and to calculate journey times. We could also collate other data, apply intelligence to it and give customers feedback. Information about wear and tear enables preventive maintenance; information about driving style can provide input for measures on eco-friendly driving, etc.”
Computers provide not only faster, but often also better results. They help doctors make the right diagnosis because they can recognize a tumor on medical images far more quickly than the doctor can. Computers help customers faster in contact centers, because by analyzing natural language they recognize the frequently asked questions straight away.
“The computer analyzes not just the question, but also the emotion of the customer,” says Sonck. “If the system detects an angry customer, that may be a sign to bring in an operator. But, it is then the computer which – on the basis of previous experience – feeds the right information to the operator.”
Studied IT at the Erasmus college in Brussels. He joined Proximus in 2000 and worked in marketing and the development of vertical markets, among other things. He has been Head of Enterprise Innovation since 2014.
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