29 August 2018

Reimagine the World

Match day at a modern football stadium is a prime demonstration of the way data is changing our perception of the real world. Data is everywhere.

Human analytics are changing our perception of the world around us

What can the noise of a crowd tell us? In the opening game of the Bundesliga in which FC Bayern played vs. Hoffenheim we captured the sound of 75.000 fans inside the Allianz Arena with sound mapping technology. The fans can create a deafening wall of sound, but for a data scientist, each individual voice is a unique data point. Through these minute data points, data scientists draw patterns and make predictions, painting an increasingly more vivid picture of the happenings on the pitch. In the ever increasing digital world we are living in IoT, AI and sports analytics have the power to revolutionize the way fans watch and experience a game.

Football is all about data.

On the pitch, players wear devices that collect information on their movements, allowing their performance to be analysed later. And the stadium itself can also incorporate a complex network of Internet of Things (IoT) sensors and recording equipment. At the Allianz Arena, the pitch will be kept in optimum condition thanks to data on a huge number of variables, such as light, wind, humidity, the wind, and even the chlorophyll content of the blades of grass. The information will be sent to a Siemens MindSphere hub, which analyses the data before converting it into recommendations, such as whether to water the pitch, to change the strength of the light or alter the temperature of the underground heating.

When the crowd leave the stadium, they may well travel by road or rail, in which case they will find themselves once more surrounded by a mass of invisible data networks. Sitting on a train, they will be unaware of the mechanical information being collected around them. Thousands of data-points are taken from sensors positioned throughout the train and along the tracks, sending real-time information back to hubs to be analysed and turned into insight. Over the course of a year, a single train can produce more than a billion data points, which, when amalgamated, gives engineers a clear picture of which parts may need servicing or replacing before it breaks. The same kind of predictive analytics is being used in the public sector to target the buildings and manhole covers most at risk of fire, or the areas most susceptible to crime at a given time; allowing the limited number of officers to patrol the streets that need them most.

While data analytics help us prevent unwanted events, the insight it gives us can, perhaps more importantly, lower the chances of these events occurring in the first place. On the roads, cars are monitored by a whole range of radar and recording technologies that send traffic data back to turn this information into insight. Turning these data points into insight, traffic managers can then implement lane or speed restrictions, as well as sending information about the route directly to in-car satellite navigation systems. With 68% of the world’s population projected to live in urban areas by 2050, our ability to get home in-time for kick-off will increasingly come to rely on the efficiency of these systems.

Nevertheless, the evolution technology will soon give us even greater insight into our systems and behaviours, making our journeys shorter and routes more efficient. As autonomous vehicles become the norm, most cars will be equipped with laser scanners and cameras, as well as radar and ultrasound sensors, allowing them to coordinate their movements with other cars and central WiFi signal towers. The combined data will make it possible to predict situations on the road and initiate the most appropriate action to avoid traffic jams and a host of potentially dangerous situations.

When supplemented with physiological data, capturing people’s reactions to travelling through different parts of a city, the analysis becomes even more revealing. Scientists in Germany and Austria have developed a wristband sensor that collects things such as skin temperature. Together with GPS data and a clever algorithm it can detect and map stress in users as they move around the city. In one project with cyclists in the German city of Karlsruhe they were able to create an ‘emotional map’ of the town revealing where stress was greatest, allowing planners to identify specific locations of potential danger, such as intersections where oncoming traffic had to be negotiated or places where car drivers’ views of the cycle lane were blocked and there was a risk of collision.

This kind of insight is also helping businesses around the world streamline their process and minimise any wasted time, money or effort. In a modern-day port, for example, thousands of lorries need to be unpacked or loaded up with cargo every day, before being sent on their journey. To maximise efficiency, strategists are turning to the data.

Duisburg in Germany is home to the world’s largest river port, with 120 million metric tons of goods passing through each year. Traffic volumes in and around the port are high, and to direct heavy vehicles into, and out of the port as quickly as possible, Siemens has developed an “Integrated Truck Guidance” system. Cameras record the registration numbers of approaching lorries and the information is then forwarded to the control room, allowing each vehicle to be given a slot. This information is then relayed directly to the drivers on their smartphones.

The offices in which we work also increasingly make sophisticated use of data. So-called ‘smart buildings’ can read weather forecasts to adjust their heating and cooling systems, use lights to guide people to safety in an emergency and automatically park cars in their multi-storey car parks. But such systems tend to operate independently and their data is not integrated. The key is to create a ‘system of systems’ that brings all of the data together.

An integrated building management system such as Desigo CC from Siemens does just that, collating huge amounts of data from all around the building , allowing it – and the building manager – to make better decisions. For instance, if a conference room is only needed for one hour on a specific day, the room’s cooling will begin half an hour before the meeting and will stop half an hour after it finishes, reducing energy use and helping the environment.

It’s just one more example of the large amounts of data increasingly being quietly collected and put to use all around us and helping us to reimagine the world in ways we once could only have dreamed of.

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