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added value. Local conversion of sensor data to smart data by iCOMOX results in a lower data flow and consequently less power consumption than is the case with direct transmission of raw sensor data to the edge or the cloud. The iCOMOX and its AI algorithms can be applied to monitoring machines, systems, structures and processes – extending from detection of anomalies to complex fault diagnostics and immediate initiation of fault elimination. If behaviour models are available for certain damages, they can even be predicted. Maintenance measures can be taken at an early stage and thus avoid unnecessary damage-based failure. If no predictive model exists, the embedded platform can enable successive learning of a machine’s behaviour over time, to derive a comprehensive model for its predictive maintenance. In addition, the iCOMOX can be used to optimise the complex manufacturing processes to achieve a higher yield or better product quality.
Embedded AI algorithms for smart sensors With data processing by AI algorithms, automated analysis is even possible for complex sensor data. Through this, the desired information – and, thus, added value – are automatically arrived at from the data along the processing chain. Selection of an algorithm often depends on existing knowledge about the application. If extensive domain knowledge is available, AI plays a more supporting role and the algorithms used are quite rudimentary. If no expert knowledge exists, the algorithms can be much more complex. In many cases, it is the application that defines the hardware and through this the limitations for the algorithms. For the model building, which is always
a part of an AI algorithm, there are basically two different approaches: data-driven and model-based. If only data is available but no
background information that could be described in the form of mathematical equations, then so-called data-driven
Figure 3: Data-driven approaches for embedded platforms
Figure 1: Division of the algorithm pipeline into embedded, edge and cloud platforms
Figure 2: iCOMOX block diagram
www.electronicsworld.co.uk May 2022 07
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