Public transit (Bus, Rail, etc)

Explore how GPU-accelerated computing enables autonomous driving from Level 2 to Level 4, supporting real-time perception, sensor processing, and vehicle control across transportation, industrial, and delivery applications.

AI-powered rail surface inspection combines high-speed cameras, edge AI, and rugged embedded computing to detect cracks, scratches, and other rail defects in real time, improving railway safety while reducing manual inspection and maintenance costs...

A Level 4 self-driving shuttle bus operates at 70 km/h in real traffic, relying on redundant GNSS, LiDAR, and camera data. Neousys' rugged Nuvo GC and VTC computers provide the high-performance GPU AI and V2X connectivity for real-time sensor fusion and control.

Neousys Technology's intelligent railway platforms excel in SCADA systems, control centers, predictive maintenance, surveillance, and communication, aiding future railway development.

The Neousys VTC series are rugged expandable in-vehicle computers that can be used to control and monitor Electrical Bus Monitoring Information Systems in harsh environments...

The future of autonomous public transport consolidates multiple application technologies to offer convenience, security and green living. With 2D/ 3D perception sensors and maps complementing one another, it allows the bus to navigate through traffic/ objects without fuss and arrive at each stop with accurate time-stamp.

The autonomous driving system utilizing Neousys’ GC series system for commercial minibuses consists of several modules such as sensory subsystems, Lidar (optic radar), camera and satellite to precisely position and monitors the bus' surroundings.

Systems using machine vision to identify license plates when entering/ exiting the parking lot can be widely seen. The fully automated system rectifies human labor needs, parking meter calculation error and the possible loss of token...