Smart applications against regulatory pressure - Interview with Sascha Schlosser

IoT has arrived at the municipal utilities. But many of them are still hesitant to take on the role of digital infrastructure operator, says Sascha Schlosser of Digimondo.

 

Smart applications against regulatory pressure

IoT has arrived at the municipal utilities. But many of them are still hesitant to take on the role of digital infrastructure operator, says Sascha Schlosser of Digimondo.

IT. More and more municipal utilities have launched projects in the Internet of Things (IoT). So far, these have mainly been pilot projects, but some of them have already had a concrete operational effect. They are not only about smart city applications. Some also alleviate the regulatory pressure on municipal utilities.
Sascha Schlosser sees a particular need for the use of the Internet of Things in the heating sector. Here, the operators are under regulatory pressure to digitalise their networks, says the managing director of the IoT service provider Digimondo in an interview with E&M. They need to find efficient solutions for this. "A Lorawan network is a good choice here, as it can be implemented quickly and cost-effectively compared to a complex control centre connection," says Schlosser.

Parking space monitoring or monitoring the fill levels of waste bins are common applications with which municipal utilities are taking their first steps in the IoT world.

But there are also the "right" energy industry approaches, such as monitoring the low-voltage level. "When a grid operator adapts the topic for itself, it naturally first looks at its own needs," says Schlosser. And here the need is great, because the distribution grids have so far been designed for an assumed maximum load and then basically seen as a black box.

Predictive maintenance saves money

Until now, operators were largely unaware of how the grids were affected by flexibilised consumption and volatile feed-in. This is now changing as more and more sensor technology is brought into the grid. This makes the low-voltage grid visible to the staff in the control centre, explains the Digimondo managing director. "They can recognise conspicuous values and also an- ticipate where problems with the operating equipment could occur. And if faults do occur, they can be localised quickly and remedied accordingly," he says. If you can maintain with foresight and avoid faults, you can ultimately save a lot of money.
However, Schlosser observes, many municipal utilities are not yet ready to take on the role of digital infrastructure operator for themselves and the municipality. As a rule, they have a great deal of trust with the population and the local economy compared to the large digital companies, which can also occupy this field. That is why the pilot phase must now be followed by the next stage of evolution, he says.

The "refinement" of data is crucial

Before joining the management of Digimondo last year, Schlosser had developed the company-wide digitalisation strategy at the measurement technology provider Zenner. He calculates that the potential savings are offset by a relatively small investment for network operators when they set up an IoT network. For a medium-sized city, the 50 gateways required for around 1,000 euros each are the biggest chunk.

In addition, one has to take into account that municipal utilities usually have enough properties where gateways and antennas can be installed. "Nothing has to be rented," emphasises Schlosser.
Digimondo itself has developed a platform with which the service provider concentrates on the "refinement" of data, as the managing director puts it. For example, temperature, pressure or stress data are usually only valuable if they are linked with other data from other systems.

Three or four years ago this was still different, as can be seen from the company's first own product. At that time, Digimondo had brought a software onto the market that exclusively managed the infrastructure of sensors and gateways. Today, on the other hand, it is no longer a question of what works technically, but how data can be processed and what insights can be derived from it.