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Performance monitoring for modern waste-to-energy solutions

IoT Use Case - b.telligent + MARTIN GmbH
6 minutes Reading time
6 minutes Reading time

Initial situation and challenges

MARTIN GmbH, a leading provider of advanced waste-to-energy solutions, wanted to improve its services by using loT data to monitor plant operations and provide customized data solutions. The existing on-premise data platform no longer met the requirements of the increasing query load and flexibility. To unlock the potential of data-driven products, the company needed a versatile solution that also took data sovereignty concerns into account.

The biggest challenge for MARTIN was to expand its data capabilities to effectively incorporate machine data. The company needed a solution that could not only handle higher query loads and deliver high-performance query performance, but also provide the flexibility to gain insight into MARTIN technology in advanced waste-to-energy solutions. Another central criterion was to gain control over data and ensure data sovereignty.

About Martin GmbH

We have the solutions for today’s challenges and are developing the technologies of tomorrow. This is how we make a decisive contribution to our future: with our systems and components, we contribute to the optimal and sustainable recycling of waste. As one of the world’s leading suppliers of thermal waste treatment plants, we offer our municipal and private customers a full range of services over the entire service life of plants. We are a fourth-generation family business that thinks and acts for the long term.

Our company was founded in Munich in 1925. With the highest standards of quality and professionalism, company founder Josef Martin developed the company into a strong brand and established values that we are now carrying into the future as a family-run company in the fourth generation.

Solution approach

MARTIN GmbH had already decided to use the IONOS Cloud in combination with Managed Stackable as a data platform for this project. With the help of the IoT Adoption Framework developed by b.telligent, the required services and requirements for the individual areas were evaluated and an IoT platform solution was designed. These six phases were run through and conclusions were drawn for the IoT platform and strategy:

Phase 1: Business objectives

Together with MARTIN GmbH, the requirements and technical prerequisites for the implementation of the Combustion Performance Report were defined. A cloud architecture and implementation roadmap was created.

Phase 2: Connectivity

MQTT is used to collect data from the waste incineration plants and transmit it to the cloud via the edge device.

Phase 3: Edge computing

The data is pre-processed on the edge device installed by MARTIN so that only relevant data points are forwarded to the cloud.

Phase 4: Cloud computing

With the help of Managed Stackable, the cloud infrastructure for the IoT data platform was provided in the IONOS Cloud. The management of the infrastructure and the Kubernetes cluster was implemented using Terraform, ArgoCD and GitLab.

Phase 5: Data analytics

Data harmonization, complex calculations and transformations were carried out on the basis of Spark and executed with Airflow at regular intervals. Power BI was used to create a regular report on combustion performance.

Phase 6: Business Application

Access to this data can now be used both internally at MARTIN GmbH and made available to its customers. This provides new insights into the complex combustion process and can be used as a basis for process optimization.

The Stackable Data Platform provides a powerful solution for the seamless collection and management of loT data and enables advanced services such as asset monitoring, paving the way for smarter analytics solutions. Together with b.telligent’s expertise in building complex IoT data platforms, the challenges in processing and visualizing the time series data were overcome and additional KPIs were calculated.

The Stackable Data Platform gives us new insights into our products. We are now able to identify and analyze deviations within the operating data and draw conclusions to support our customers.

The diagram below summarizes the services and tools for data processing and visualization. The interaction of the services used covers the following areas:

  • (Real-)Time Streaming Processing & Monitoring
  • Batch Processing & Reporting
  • Self-service analytics
IoT Data Platform

Based on the Stackable Data Platform, we were able to lay the foundation for future IoT analytics use cases together with MARTIN GmbH. We were able to make the best possible use of our expertise in the IoT sector and not only solve current challenges, but also lay a future foundation.

Results and successes

The flexibility of the data platform enabled MARTIN to gain insights into its own technologies in modern waste-to-energy processes, which in turn enabled the provision of new digital services. In addition, the introduction of the Stackable Data Platform for IoT data processing met the company’s exact requirements and ensured that MARTIN retained control of its data assets and data sovereignty.
By implementing Managed Stackable and working with b.telligent, MARTIN was not only able to overcome immediate data challenges, but is also future-proofed for further growth and innovation in the area of modern waste-to-energy solutions.


IONOS - The European cloud platform

IONOS Cloud stands for true sovereignty, scalability and high availability. Companies and the public sector benefit from high-performance IaaS compute, storage, backup and PaaS services.

IONOS Cloud consistently reduces the shared CO2 footprint. The company uses 100% green energy from renewable sources for all data centers in Germany and the UK, sustainable production and disposal chains and regular upgrades to the data center infrastructure.


The Stackable Data Platform combines openness and flexibility. It offers you a coordinated selection of the best open source data apps such as Apache Kafka®, Apache Druid, Trino and Apache SparkTM. While other providers either rely on proprietary solutions or increase vendor lock-in, Stackable takes a different approach. All apps work together seamlessly and can be added or removed in no time at all. Based on Kubernetes, the platform runs everywhere – in your own data center or in the cloud.

Create unique and enterprise-wide data architectures. The platform supports modern data warehouses, data stores, event streaming, machine learning and data meshes, for example.

Text taken from the original – b.telligent

In application

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