Transportation

The Edge AI appliance is designed to revolutionize computer vision solutions for both vehicles and railways. This innovative platform combines the power of rugged design, AI acceleration, rich I/O interfaces, and wireless connectivity with real-time processing capabilities, paving the way for in-vehicle computer vision solutions with reduced latency and improved decision-making.

 

 

Urban mobility is increasingly strained by congestion, traffic violations, and inefficient parking—challenges that demand smarter, real-time traffic management. Lanner, together with DataFromSky, offers an advanced AI-powered solution that turns standard IP cameras into intelligent traffic sensors. By processing video at the edge, directly inside traffic controllers, this joint solution delivers immediate insights and automated control capabilities for modern cities.

Rail service providers are facing increasing cybersecurity risks within their wayside signaling and train control infrastructure. With thousands of rail-specific assets and applications distributed across a wide network, there is a pressing need for continuous threat detection and monitoring to ensure network integrity and passenger safety.

Rail Obstacle Detection refers to the process of alerting railway operators about obstacles or obstructions present on the railway tracks. These obstacles can range from debris and fallen branches to unauthorized vehicles or individuals trespassing on the tracks.

We will be reviewing a machine vision system for light rail collision avoidance. This solution allows a light rail to avoid unexpected obstacles down the rail and reduce the chances of a collision. It uses an onboard industrial-grade edge AI appliance EAI-I130 provided by Lanner, capable of running MV models onboard. This appliance brings machine vision capabilities as close as possible to the light rail, allowing data captured by sensors to be processed right on-site.

Continuous surging growth in urban populations creates a demand for urban mobility, a greater demand for faster traffic flow, improved public safety, and more innovative transportation. A good urban traffic management network will not only improve traffic safety and boost local economies, but it will also improve public health and protect the environment.

Countless mines worldwide are already deploying autonomous driving mining vehicles to improve productivity and safety. In this post, we will review an autonomous driving vehicle solution that relies on different components, including in-vehicle computing, devices, networks, and the cloud.

Boats and ships traveling offshore usually have limited access to fast Internet connections. Without fast internet, they can’t benefit from what cloud computing has to offer, including data analytics and AI/ML technologies. But now, thanks to edge computing and improvements in wireless communications, the maritime industry is starting to introduce words like “smart” and “autonomous” into their dictionaries— you’ll now hear: smart boats, autonomous ships, etc.

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