FEATURE Smart factories and AI
Feature sponsored by
By Francesco Vaiani, Software Product Manager at SECO T
he ever-evolving IoT is entering a new phase, where OEMs and manufacturers are focusing on creating value through the
servitisation of their products. Service- based revenue models build upon data generated from embedded IoT devices enables predictive maintenance of on usage patterns. Manufacturers in the industrial sector are now turning to AI and ML for added capabilities, to drive competitive advantages.
Hence, developers of service-based
revenue and Product-as-a-Service, (PaaS) models, facing the twin challenges of speed to market and reduced development costs, need rapid access to structured data, and middleware is emerging as a valuable tool. By simplifying the interconnection of multiple, disparate IoT platforms and providing a layer of abstraction, middleware, such as Clea from SECO, allows the developer to concentrate on creating value-adding applications.
The evolution of the IIoT Thanks to the extensive array of sensors and embedded devices integrated into equipment, rich data sets are available, giving detailed insights into their operation. At the same time, advances in the processing power of embedded IoT technology enable sophisticated algorithms, including AI applications, to be hosted at the edge – close to the equipment – removing decision making from the cloud, which reduces latencies, making it close to real-time responses. Unfortunately, due to the rapid pace of innovation, and despite standards such as SMARC and COM Express in the hardware world, IoT architectures are extremely heterogeneous, complicating the developer’s challenge. The sheer amount of knowledge required to integrate a wide range of disparate platforms, whilst also applying AI-based solutions, requires a comprehensive team, high development costs and long time. Developers are therefore looking toward tools such as middleware, which introduce
36 June 2024 | Automation
a layer of abstraction, allowing them to focus on building AI-based applications. connection of applications, services and data sources that were not originally designed to interact with one another, shielding developers from the intricacies of underlying hardware platforms, operating systems and network protocols. and promoting collaboration between applications, middleware optimises the streamlining the development process and freeing up valuable development time and resources.
SECO’s Clea solution
SECO’s Clea is an example of a powerful software platform that integrates data orchestration with its core middleware components and also supports rapid deployment of AI models at scale. It’s an open-source software suite that gives developers full control over their data, from how it is collected to how it is processed and where it is stored. This modular software stack scales from POC to full production deployments involving huge numbers of devices and exchanged messages.
Built on Kubernetes, Clea is cloud- agnostic and provides developers
with all the tools needed to orchestrate data in the Cloud and clean it before adding intelligence. Clea abstracts the developer from the complexities of the management features, including secure systems, and containerised applications running on IoT devices. The solution, which can run Google Cloud Services out-of-the-box also facilitates the rapid development of value-added services, including advanced pre-built structures through the Clea App Framework.
Smart solutions
As one of the early adopters of IoT technology the industrial sector is also leading the way in the adoption of AI, as and competitiveness. In the smart factory, for example, AI routines can monitor machine data to spot anomalies and early signs of failure, enabling predictive maintenance and avoiding costly planned downtime for the factory owner. OEMs are increasingly collecting data
maintenance capabilities and other value- added services, such as remote assistance to their end customers.
automationmagazine.co.uk
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