Real-time Intelligence for Maximum Performance and Safety

Connected vehicle technology adds an entirely new dimension to transportation by extending vehicle operations and controls beyond the driver to include external networks and systems. FogHorn’s edge intelligence enables distributed roadside services such as traffic regulation, vehicle speed management, toll collection, parking assistance, and more.

Use Cases


Lower maintenance costs, improve asset performance and longevity, and maximize yield.


Reduce repair costs, minimize downtime, maximize output, and improve remediation efficiency.

Asset Performance

Maximize high-value asset output, balance reliability, performance, and cost.


Improve automation, enhance practitioner collaboration, reduce manual data entry and errors.


Optimize systems for maximum KPI performance, quickly adjust to changing conditions.


The future of transportation with autonomous vehicles (AVs) remains largely unknown even as technology developers and manufacturers are investing furiously in research and development. Much will depend on creating the intelligence required to build and operate AV systems. And while safety systems and high definition mapping have received a lot of attention, there are many other intelligence-intensive technologies that also need to be developed before large scale AV acceptance is possible.

As an example, nearly all AVs are expected to be electric cars and these will require substantially more in-vehicle intelligence and system life cycle management. These are needed to maximize the efficiency and lifespan of battery and charging systems as well as other systems that support braking, motor performance, safety, passenger environment and predictive maintenance.

FogHorn’s edge intelligence platform, brings high performance processing directly inside the vehicle rather than relying on remote data centers for critical command and control decisions. Its extremely small footprint makes it possible to provide a full range of real-time, autonomous industrial-strength analytics and machine learning capabilities using a vehicle’s own processors.

And because the FogHorn platform is built to operate in heterogeneous environments, it simplifies the integration of a wide range of disparate systems from multiple vendors within a single vehicle. In addition to supporting dozens of autonomous, on-board edge systems, the platform can also upload selected data points to remote, cloud-based data centers for additional analysis and overall system optimization.

Case Study

FogHorn and Porsche Leverage
Edge Computing for Vehicles