The Industrial IoT has been an emerging market for several years now. As such, it has enabled manufacturing companies to increase production efficiency and to increase product quality. A major innovation driver is the usage of raw sensor and process data from production control systems and PLCs for downstream analytics tasks. With the convergence of Information Technology (IT) and Operational Technology (OT), many new use cases have appeared which allow to analyze fine-grained sensor data in real-time, to detect undesired situations and to apply these findings to improved process execution and optimized maintenance.
From a technical perspective, distributed edge-cloud architectures, often in combination with event-driven architectures, have emerged as the architectural paradigm of choice to realize such use cases. In these architectures, lightweight edge devices collect data directly from the shop floor (e.g., PLCs), pre-process data locally to reduce network traffic and to filter out irrelevant events and forward data to central systems (which might be at factory or cloud level) which provide the data analytics infrastructure. In addition, offloading of analytics tasks to edge nodes has recently become more popular due to increased processing power at the edge. This is especially useful for low-latency analytics applications.
Another shift in the past years was the uptake of open-source technologies in realizing such architectures. While the usage of open-source technologies is nothing new in the IT sector, with many market-dominant systems (e.g., in the Big Data world) being developed as open-source software, the manufacturing industry has started to adopt open-source technologies in their own stacks as well.
A popular open-source project in the Industrial IoT domain is Apache StreamPipes. StreamPipes is positioned as a self-service tool for flexible data analytics and realizes a development platform for industrial analytics applications. As an end-to-end toolbox, StreamPipes supports fast connectivity with a set of reusable adapters for popular industrial protocols (e.g., S7, Modbus, MQTT, OPC-UA), provides a pipeline tool to define alarming rules and notifications without programming and includes various tools for (visual) analytics. Many companies use Apache StreamPipes to gather and integrate Industrial IoT data and to run real-time analytics on continuous data streams in order to increase production efficiency, e.g., by implementing predictive maintenance applications.
Bytefabrik.AI is a technology startup from Karlsruhe, Germany with a focus on self-service manufacturing analytics applications for the Industrial IoT. The company follows an open core business model with Apache StreamPipes at its core.
Founded by the original creators of Apache StreamPipes, Bytefabrik.AI invests heavily in open-source development and contributes the latest software technologies for intelligent, real-time data analytics to the Apache StreamPipes project.
Within the ISOLDE project, Bytefabrik.AI aims to contribute substantial new features into Apache StreamPipes which will help to foster not only the RISC-V ecosystem in terms of application support in an evolving application area, but also help to develop future technological USPs for StreamPipes. We believe that RISC-V can become an important cornerstone of future Industrial IoT architectures - not only because of its open architecture. Several promises of RISC-V, e.g., energy-efficiency, ability to operate in low-power edge computing environments and low operating costs are highly relevant for distributed edge-cloud scenarios.
Planned development highlights of Bytefabrik.AI’s contributions within ISOLDE will be a lightweight edge client which will be able to stream data from source systems such as PLCs to a central Apache StreamPipes instance, an edge-cloud orchestrator to manage existing edge clients and an analytics runtime for time-series machine learning model execution. We will apply the technical outcomes to the Smart Home Demonstrator developed within ISOLDE.
We plan to make major parts of our technical achievements within ISOLDE part of Apache StreamPipes – this will ensure sustainable dissemination of project outcomes and will help to foster the RISC-V application ecosystem.
Links
Bytefabrik.AI – https://bytefabrik.ai
Apache StreamPipes – https://streampipes.apache.org
