Smart factory digitization
Machine learning sensors from quantity 1
SSV now also offers task-specific industrial sensors for machine learning applications in the smart factory in quantities of 1 with the help of a modular system.
Sensor data for smart factory digitization tasks requires a significantly higher quality information content than, for example, in classic sequence control applications. Using a selection of sensor elements suitable for the task, sensor fusions for linking different measured values and AI algorithms, the raw sensor data in the SSV sensor solutions becomes valuable information that can be used for various tasks in process optimization, machine and system maintenance and intralogistics.
With the Smart Factory sensor product family, which is based on a modular system, SSV offers retrofit sensors with an application-specific data output. The housing, sensor elements, signal processing, power supply and the data and configuration interface are adapted to the task. A support docker with various functions tailored to the respective sensor is supplied as an accessory for each sensor. In addition to Node-RED functions, this also includes a TensorFlow Lite inference interpreter for real-time analysis of the sensor data with the help of previously trained neural networks in order to create the required information for transfer to higher-level systems such as an MES.
In line with this topic, SSV is hosting the webinar "IoT wireless sensor technology for machine learning applications" during Sensot+Test 2021 on May 6 from 11 a.m. to 12 noon. This will cover the technical aspects of sensor data processing and information acquisition with artificial neural networks. This webinar will be followed by an interactive hands-on session with virtual guidance, in which each participant can pre-process live sensor data on their own computer using Google Colab and analyze it with TensorFlow.
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