RMG/941: Remote Maintenance Gateway

Remote Maintenance Gateway RMG/941

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.



  • With LTE- or NB-IoT-Modem
  • Freely programmable
  • Extensive machine learning components
  • Data flow programming with Node-RED
  • Functional enhancements via App
embedded Machine Learning

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.

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.

Thus, an edge solution for condition monitoring can be realized within a very short time.

Condition Monitoring with RMG/941 and AWS

We have published a comprehensive example of machine learning-based condition monitoring with the RMG/941, the soft sensor MLS/160A and the Amazon Cloud (AWS). The complete condition monitoring example, including all code and CSV files and a detailed description, can be found on GitHub:

Condition Monitoring with RMG/941 and AWS on GitHub.

ML-based condition monitoring with RMG/941 and AWS

Secure Device Update

If you look at a typical control solution in automation from the perspective of IT security, many solutions would actually have to be shut down immediately. The main reason is usually the lack of possibilities for software updates. In most cases patches do not even exist although some controllers have long known weaknesses.

Secure Device Updates (SDU) solve these problems and also offer the possibility to distribute new functions to the users.

If a component, machine or system is to be supplied with software and configuration updates via an IoT connection, IT security must be taken into account in addition to system security.

With the current state of the art, this requires a public key infrastructure (PKI) for digital signatures with private and public keys, certificates, revocation lists, etc., to at least guarantee the authenticity and integrity of the update.

All necessary components are included in SDU.

Secure Device Update

User Story SDU

I have 150 machine control systems in operation at over 90 customers in three countries. From time to time, I would like to automatically equip them with a new software update.

Virtual Private Network

User Story VPN

My specialized machines run with completely different configuration settings. Our service department has to check them once a month and readjust them if necessary.

Virtual Private Network

A VPN for remote maintenance has a star-shaped topology with a VPN (switching) server as the central functional unit. All remote maintenance gateways (VPN clients) automatically establish a connection to this VPN server via the Internet and, depending on the configuration, maintain this connection only for the duration of a remote access session or permanently, if necessary. The connection establishment is initiated by the gateway itself.

The trigger is a specific event in the OT network or a manual activity of the operator. On the other hand, a service technician with a computer on which the VPN software is installed can also connect to the VPN server at any time.

For the actual remote maintenance, a virtual LAN connection with its own IP addresses is created between the computer and the controller in the machine or system.

The RMG/941 serves as a VPN security endpoint, but is otherwise completely transparent with regard to remote maintenance activities.

Internet of Things

Most IoT service providers offer their customers only pseudo-secure solutions that are however very easy to use which is probably why they are so widespread. Generally, the confidentiality, authenticity and integrity of sensor data and actuator data is terminated in the provider's cloud. Here the data is available in unencrypted form. For this reason, IoT cloud platforms have also become a frequent target for cyber attacks.

In order to still guarantee a highly secure connection between sensor and actuator with the help of the overall completely insecure Internet, real end-to-end security is required that does not end in the cloud. To achieve this, the end points of an IT solution must be integrated into an independent public key infrastructure (PKI) and private keys must be securely stored in an IoT sensor.

In order to still guarantee a highly secure connection between sensor and actuator with the help of the overall completely insecure Internet, real end-to-end security is required that does not end in the cloud. To achieve this, the end points of an IT solution must be integrated into an independent public key infrastructure (PKI) and private keys must be securely stored in an IoT sensor.

Internet of Things

User Story IoT

We rent air compressors. For billing the amount of compressed air produced, we need a secure and legally sound method of getting sensor data from the compressor to our accounting software.

Remote Assistance

The Remote Assistance application consists of three elementary functional units: the condition agent, the assistant app, and the cloud service with an integrated digital twin.

The agent uses data analysis to periodically determine the current machine status, provides updates to the digital twin and continuously sends status beacons via Bluetooth Low Energy (BLE).

The app and cloud service work in a system network and provide the user with meaningful information on the current condition of the machine as well as extensive maintenance and repair information. Voice chats with external experts are also possible via the app.

User Story Remote Assistance

We want to offer our customers better service than our competitors for the machines we supply in order to increase customer satisfaction.

To this end, the customer should be able to call up extensive status information on each individual machine at any time with the help of an app or a locally available website and, in the event of a malfunction, immediately start a chat with our service center.

To enable us to help the customer at any time, a digital twin is created for each machine, providing our technicians with the detailed information they need.

Additional maintenance information is also available to the customer via this database.

Technical Data

Single Board Computer
Model DIL/NetPC DNP/9535
Manufacturer / Type Atmel ATSAM-A5D35 SoC
Clock speed 528 MHz
Flash 4 MB NOR
Storage medium 1x internal SD-card holder
Ethernet 1x 10/100 Mbps (RJ45)
Serial I/Os 1x RS485 serial port (screw terminal)
COM (service port) 1x 6-pin connector
Antenna 1x SMA interface for LTE/NB-IoT antenna
Special functions
Real time clock (RTC) 1x RTC with internal battery backup
Watchdog 1x Timer watchdog
(Hardware-based, Software-configurable)
1x Power supervisor (Hardware-based)
SIM-Card 1x Holder for Mini-SIM-cards (accessible from the outside)
LTE-Modem (RMG/941L)
Mobile radio standards GSM/UMTS/HSPA+/LTE
Transfer rates 100 Mbps max. download, 50 Mbps max. upload
Frequency bands LTE: B1/B3/B5/B7/B8/B20
GSM/GPRS: GSM850/GSM900/DCS1800/PCS1900
Authentification PAP, CHAP, CHAT, none
Supported APNs Telekom, Vodafone, 02, E-Plus, user-defined
NB-IoT-Modem (RMG/941N)
Mobile radio standards GSM/LTE
Transfer rates LTE Cat M1 375 Kbps max. download, 375 Kbps max. upload
Transfer rates NB-IoT (LTE Cat NB1) 32 Kbps max. download, 70 Kbps max. upload
Transfer rates GSM GPRS: 107 Kbps max. download, 85,6 Kbps max. upload
EDGE: 296 Kbps max. download, 236,8 Kbps max. upload
Frequency bands LTE Cat M1 LTE FDD: B1/B2/B3/B4/B5/B8/B12(B17)/B13/B18/B19/B20/B26/B28
Frequency bands NB-IoT (LTE Cat NB1) LTE FDD: B1/B2/B3/B4/B5/B8/B12(B17)/B13/B18/B19/B20/B26/B28
Frequency bands GSM/GPRS: GSM850/GSM900/DCS1800/PCS1900
Authentification PAP, CHAP, none
Supported APNs 1nce
Displays / control elements
LEDs 1x Power
1x System status (programmable)
2x LAN LED for Ethernet interface
Electrical characteristics
Supply voltage 11 .. 28 VDC from external power supply
Power consumption < 15 W
Mechanical characteristics
Protection IP20 industrial housing for 35 mm DIN-rail
Mass < 150 g
Dimensions 112 mm x 100 mm x 22,5 mm
Operating temperature 0 .. 60 °C
Storage temperature -40 .. 85 °C
Standard and certificates
Environmental standards RoHS, WEEE

Software Features

Operating system Embedded Linux
Web server lighttpd mit SSL
Runtime environment PHP, Java, Node.js, Python 3
IP-address assignment Static, DHCP, AutoIP, UPnP, SSV IP-by-Net
Protocol stack ARP, ICMP, IP, TCP, UDP, Telnet, FTP, HTTP, TFTP, Modbus TCP/RTU (server + client), MQTT, OPC UA and more...
Security protocols SSL/SSH, TLS, HTTPS, OpenVPN (server + client), IPsec
TCP server Telnet, FTP, TFTP, HTTP
Firewall netfilter + iptables
Proxy functions HTTP(S), FTP, Telnet, SSH, generic TCP port mapping
Configuration SSV/WebUI
Machine learning components PyDSlog-library for data acquisition
NumPy-library for numerical calculations
Pandas-library for evaluating and editing tabular data
SciPy-library for scientific computing (e.g. FFT)
Matplotlib-library for mathematical representations
Seaborn-library for statistical graphics
Sklearn-library for machine learning
TensorFlow Lite-interpreter for deep learning
Jupyter Notebook Kernel for web-based testing
Miscellanious Node-RED: graphical data flow programming based on Node.js including Node-RED dashboard

Product Variants

Name Description
RMG/941 Without LTE-modem, without antenna interface
RMG/941L With LTE-modem and antenna, without SIM-card
RMG/941N With NB-IoT-modem, antenna, and preinstalled SIM-card


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