Automotive Telematics &
Connected In-Vehicle Services

Turbocharge development of vehicle telematics device software.

Telematics and connected in-vehicle services based on mobile communication network technologies (UMTS, LTE, 4G, 5G) providing features such as controlling vehicle comfort functions via mobile app or checking an electric vehicle's charging status are now ready for the next evolutionary step — the fully connected car.

Cellular communication modules are now more than powerful enough to run Linux and on one or more of its CPU cores. This enables the evolutionary step from simple feature-restricted telematics systems to dynamically extensible, flexible and secure platforms based on modern IoT technologies. Such platforms make it possible to dynamically deploy new software features during the entire lifecycle of the vehicle. In-vehicle apps distributed through an "app store" enable car manufacturers and their partners to introduce new services and open new revenue opportunities.

Possible applications are automatic remote vehicle systems monitoring, emergency assistance, real-time fleet management, automatic log books, optimized service and maintenance logistics, theft protection, as well as car-sharing and rental services. provides a flexible, modern and industry-proven foundation for this new breed of flexible in-vehicle services platforms. Combining efficient C++ code with a high performance JavaScript engine makes it possible to run on cost-effective hardware, while still being able to write "apps" in high-level JavaScript, one of the most popular programming languages.'s sandboxing feature protects the core system from misbehaving apps. Together with's support for code/bundle signing, this enables the dynamic deployment of third party apps to the in-vehicle telematics system.

Contact us to discuss how can turbo-charge your next vehicle telematics project.

Connect to vehicle bus systems such as CAN and Ethernet and obtain vehicle performance and sensor data.

Connect to cloud services via MQTTS and HTTPS, access APIs and integrate with backend applications.

Process location information from connected GPS/GNSS receivers for vehicle tracking, automated log books and analysis.

Perform on-vehicle data processing and analysis to optimize maintenance and service operations.

Allow third parties to write in-vehicle apps for applications like fleet management, rental or car sharing in JavaScript or C++.

Industrial IoT

Rapidly implement industrial IoT gateway and edge computing applications.

With the Industry 4.0 revolution being already underway, it's time to make automation technology ready for the Industrial Internet of Things. Off-the-shelf industrial IoT gateways and edge computing devices powered by Linux and provide a solid foundation to introduce IoT technology to manufacturing systems.

The market offers a rapidly growing selection of industrial IoT gateway and edge computing devices based on Intel or ARM architectures. However, these devices are usually delivered with just a basic Linux operating system and a few low-level libraries. This makes software development for these devices slow, error-prone and inefficient.

Enter feature-rich APIs for working with industrial sensors and automation devices using technologies such as Modbus, CANopen, USB, RS-232, or OPC-UA, as well as wireless protocols such as Bluetooth LE or XBee, combined with a high-performance JavaScript engine make it easy to quickly build custom applications to optimize manufacturing processes. A built-in web application server enables web-based visualizations of process and sensor data that can be displayed on mobile devices or HTML-capable industrial display panels. Support for HTTPS, MQTTS, REST, JSON-RPC and SOAP protocols make it easy to securely communicate with enterprise or cloud applications. And finally,'s modular plug-in based architecture and remote management capabilities makes it possibly to roll out application software upgrades or entirely new applications to a large number of field devices.

Contact us to discuss how can help you realize the Industry 4.0 vision.

Connect to industrial automation devices using bus systems such as Modbus or CANopen, as well as OPC-UA technology.

Obtain data from on-board or external sensors like temperature, humidity, light, pressure or acceleration.

Perform edge computing for production monitoring and optimization, failure mitigation and predictive maintenance.

Securely deliver sensor, process and performance data to cloud-based or on-premise analytics platforms and digital twins.

Build web-based live dashboards for process and sensor data and show them on mobile devices or industrial display panels.

Smart Connected Sensors

Smarten up connected sensors for infrastructure, environmental and traffic monitoring with Edge Computing.

Smart connected sensors for environmental, infrastructure and traffic monitoring are one of the cornerstones of the Industrial Internet of Things. Applications like automated monitoring of critical assets such as road bridges, railway infrastructure or power grids, as well as traffic and environmental conditions can benefit greatly from IoT and edge computing technologies.

In many cases, such systems are deployed at locations where power and broadband network connectivity are scarce resources. Being implemented with efficiency and scalability in focus, can be used on energy efficient low-power cellular hardware that can operate for years on battery power. Intelligent sensor data aggregation, preprocessing, filtering and buffering on the smart sensor edge device helps to minimize data transmission volumes, deal with intermittent network availability and reduce loads on backend systems. is also perfectly suitable for gateways aggregating sensor data from wide-area low-power wireless sensor networks (LPWAN) like LoRaWAN or Sigfox.

Contact us to discuss how can help you smarten up your connected sensors.

Aggregate, preprocess and perform edge-analysis of data from multiple sensors such as environmental, acceleration, strain or location.

Improve energy efficiency of battery or solar-powered devices through efficient C++ code.

Save costs by intelligently filtering sensor data on the edge device to reduce data transmission volumes and backend processing loads.

Securely deliver sensor data to cloud-based or on-premise analytics platforms using HTTPS/REST or MQTTS.

Securely access and manage sensors in remote locations with Remote Manager.