- Seamless data transmission between different applications
- Simple linking of components and applications using "Software Glue"
- Machine or server-based
- Use of standards and quasi standards
- Minimized effort for realization through middleware
- Automation of routine tasks
Interoperability is the key to seamless data transmission between distributed systems and therefore to the Internet of Things (IoT). Besides other machines, also distributed sensors or smaller devices are included within the eco-system of a mobile machine.
Standardized solutions are necessary in order to manage the accruing data volumes. Without requiring development effort, they should support the communication between machines and sensors and between different applications.
Machine-based support mostly functions according to the publisher-subscriber principle. Using MQTT (Message Queue Telemetry Transport) or DDS (Data Distribution Service), messages of a certain class are sent by the publishers, whilst the subscriber receives messages of a certain class - each respectively without the knowledge of the other. Whereas MQTT requires a broker (e.g. realized in machines.cloud), with DDS the middleware handles this itself.
A further middleware is ROS, the Robot Operating System. ROS provides a framework for the software development for the interconnection of robots.
Cloud solutions such as machines.cloud, also provide the ideal approach for middleware. As a result, the collected machine data can be transmitted here, for example, to a data hub such as DKE Data Hub in agriculture or the integration platform Zapier. With the connection to DKE, STW opens up the world of Farming 4.0 to attachment and equipment manufacturers, and with Zapier more than 750 Apps can be accessed.
- Simplify software development by adding a layer of software enabling data transfer between different applications, link/connect components/applications together, “software glue”
- High level approach for software developers „glue software together“ e.g distribute sensor data
- Send measurements to IoT systems (cloud), bring various expert knowledge into your app