Security gateway RMG/941

IoTVPNLinux

The RMG/941 has a software which makes its field of application very versatile. It is suitable for VPN access, IoT applications of all kinds, high security software updates from anywhere you like up to complex embedded machine learning edge applications. Also the embedded Linux system software makes the installation of additional software possible. Highlights With LTE- or NB-IoT-Modem Freely programmable Extensive machine learning components Data flow programming with Node-RED Functional enhancements via App User Story eML We use low-cost triaxial acceleration sensors for the condition monitoring of our drive elements. Real-time data analysis for condition detection only works sufficiently accurate by machine learning. embedded Machine Learning The workflow of a machine learning (ML) based condition monitoring application consists of two phases. In a training phase, historical data with feature vectors are first collected from the sensors belonging to a specific application in a text file (CSV file) and then used to model a suitable ML algorithm. Schema embedded Machine Learning Zoom image In the subsequent inference phase, a single feature vector with real-time sensor data is then analyzed using the mathematical model by means of supervised learning and the respective operating state is classified. The RMG/941 is delivered with a Python3 runtime environment with numerous data science libraries offering various ML functions up to neural networks. PyDSlog is also a preconfigured software for data acquisition, which can be used to easily generate the feature vectors for modeling.