Neural Labs Launches Self-Learning Module in Neural Orchestr[ai]tor Powered by NVIDIA Accelerated Computing

Transforming passive cameras into intelligent sensors capable of learning and  detecting incidents autonomously

Barcelona, Spain – November 2025

At the upcoming Smart City World Congress 2025, Neural Labs will officially present its new AID Self Learning Module, an advanced AI functionality within the Neural Orchestr[ai]tor platform. Developed with  the support of NVIDIA, the solution brings accelerated computing to large-scale video analytics, enabling  cities to monitor thousands of cameras in real time with adaptive, autonomous intelligence.

“Cities are increasingly deploying cameras for traffic and safety management, but most remain passive.  Our Self-Learning Module turns these cameras into proactive sensors that detect incidents automatically,”  said Juan Silva, Regional Sales Manager at Neural Labs. “With NVIDIA accelerated computing, Neural  Orchestr[ai]tor can process dozens of video streams simultaneously, providing instant insights where  they’re needed most.”

Solving a Critical Challenge in Smart Cities

Urban and highway networks often rely on hundreds or thousands of installed cameras operating in  passive mode. Human operators cannot feasibly monitor all streams in real time, leading to delayed or  missed incident detection and underused infrastructure.

The AID Self-Learning Module addresses this challenge by automatically learning each camera’s  environment and generating its own detection rules. Through Deep Learning & machine learning, it  identifies abnormal situations such as stopped vehicles, traffic congestion, pedestrians or animals on the  road, smoke, or wrong-way driving — without requiring any manual configuration.

Built on the Power of NVIDIA Accelerated Computing

In collaboration with NVIDIA, Neural Labs has optimized the Self-Learning Module to take full advantage of  GPU-accelerated deep learning inference, delivering:

• Real-time performance – simultaneous analysis of dozens of video streams with minimal latency. • Scalability – easy expansion of monitored cameras without performance loss.

• Energy efficiency – greater performance per watt compared to CPU-only setups.

Key Advantages and Capabilities

• Effortless setup – automatic configuration without defining zones or events.

• Continuous learning – adapts dynamically to environmental or camera position changes. • Broad compatibility – works with any RTSP camera (bullet, dome, or PTZ).

• Scalable centralized processing – AI servers available for 2 to 50 camera streams.

• Flexible licensing – floating licenses allow dynamic redistribution among large camera pools. A Smarter, More Proactive Approach to Urban Video Analytics

With the AID Self-Learning Module, Neural Labs and NVIDIA empower cities to unlock the full potential of  their video networks — moving from passive monitoring to intelligent, adaptive analytics that enhance  mobility, safety, and resource efficiency.

Live demonstrations and technical presentations will take place at the Neural Labs booth during Smart City  World Congress 2025 in Barcelona. For meeting requests or further information, please contact  info@neurallabs.net or visit www.neurallabs.net.

About Neural Labs

Neural Labs is a leading provider of AI-based video analytics solutions for smart mobility, ITS, and  enforcement systems. Its products are deployed worldwide, supporting authorities and system integrators  in enhancing urban safety, traffic management, and environmental compliance through advanced  computer vision and machine learning technologies.