Michael Schöller

Manufacturer-independent sensor networking with CloudRail.Box and Azure IoT Hub | Schmitz Cargobull

This podcast episode presents two use cases built on Azure, Microsoft’s cloud service that can be used to collect information on a large scale, analyze it, but also process it directly for further use and trigger appropriate actions. Michael Schöller brings along a practical application from Schmitz Cargobull: Using IoT in road transport, sensors and a cloud connection can be used to permanently record and transmit, among other things, the temperature and global position of the valuable freight, but also the maintenance status of the vehicles. This makes it possible to monitor compliance with cold chains without having to resort to time-consuming and error-prone manual processes. They were so enthusiastic about their set cloud partner Microsoft in the process that they have since dispensed with local data centers and switched all internal processes to the cloud universe. “We are pursuing a cloud-first strategy!” – All in the name of the end of data silos, as Philip Weber also sees coming, who describes CloudRail’s services as a second use case: They specialize in making machines IoT-ready and bringing them into Microsoft’s Azure cloud. Different requirements in different industries, a wide variety of technologies, older systems (retrofit) – thanks to abstraction, all this is no problem for CloudRail. With a uniform data model, the use of the IODD database and strict reliance on standards, such as the IO-Link protocol, they manage to effectively implement the IoT plug-and-play idea. The first proofs of concept can be shown in just a few hours. Those who then want to expand the result further into the enterprise additionally benefit from CloudRail’s centralization strategy. If the machines are already connected to the cloud for the purpose of IoT, then – not least in terms of data protection – the regular updates, for example, can be controlled centrally. For the user, IoT thus brings numerous advantages. Predictive maintenance: I know at all times how my machines are doing and when and where they need to be upgraded. Manual tracing is no longer necessary. It also reduces downtime due to any unforeseen incidents between maintenance intervals. This applies to the exemplary transport vehicles equipped with Cargobull’s telematics sensor technology as well as to the software status of any machines connected by CloudRail. The ability to manage its assets remotely also eliminates travel time in many cases. The capital freed up in this way can be used for new investments. In order to easily convince themselves that the use cases also work in their own company, both Schmitz Cargobull and CloudRail have suitably packages ready for the first steps, which can then be built on if desired. Microsoft’s Thomas Frahler also agrees that offering bundles, packaged services, is essential to fully address growth and market needs.