AI Vision Stadium Lighting: Game-Changing Illumination with Industrial GPU Computers

 
Overview
 

This world leader in designing and manufacturing innovative lighting system solutions has served the sports, transportation, and infrastructure industry for 40+ years. They are pioneers in developing state-of-the-art arena and stadium lighting solutions from special effects, optimized LED technologies, enhanced athlete and viewer experience, and even mobile solutions. With the substantial global impact of AI, this lighting systems manufacturer plans to integrate AI vision to revolutionize the stadium lighting experience. However, to power their cutting-edge AI vision lighting system, they needed a high-performance, industrial-grade edge computing solution.

Challenge: 

  • Lacked an industrial computing solution to power their AI vision lighting experiences for sporting events
  • Needed to connect various IoT devices such as advanced vision cameras, sensors, and lighting equipment
  • Reliable solution that can withstand deployment into outdoor driver-control cabinet enclosures that are prone to extreme weather conditions
  • Required PoE (Power-over-Ethernet) connectivity for multiple vision cameras, sensors, and various lighting equipment
  • Safety standards compliance for safety assurance and seamless solution certification process  

Solution:

  • Premio’s AI Edge Inference Computer, RCO-6000-RPL Series, configured with 13th Gen Intel Core TE processor, DDR5 memory, and an NVIDIA RTX 4000 SFF
  • Modular EDGEBoost Node technology to integrate GPU acceleration with PCIe Gen 4 performance
  • Modular EDGEBoost I/O technology to provide additional RJ45 LAN ports with PoE
  • Super-Rugged durability with a fanless and cableless design
  • World-class certifications (CE, FCC, UL) for safety standards compliance

Benefits: 

  • Provide a fully loaded edge computing solution out of the box with customized BIOS, proprietary OS imaging, and customized shipping requirements done in-house
  • Manufacturing capacity to meet high volume production within a stringent time frame
  • Premio’s dedicated engineering and sales team to provide expertise to meet all customer requirements
  • Effective communication between Premio and solution provider with transparency and competency

 

The Challenge 

After consulting with Premio, several critical challenges were identified as significant hurdles for the lighting solutions manufacturer. These ranged from installation location constraints to ensuring IoT device compatibility. With that said, let’s take a closer look at each challenge and understand their pain points.

 

Hurdles Of Enabling Vision AI At The Rugged Edge 

AI has become a transformative force in modern technology, and this leading lighting manufacturer recognized its potential to revolutionize stadium lighting systems. After successful in-house testing results, the company was ready to bring their AI-powered solution to its piloting phase with real-world deployment. However, they faced a critical challenge: they needed a dependable, industrial-grade edge computer to operate their resource-intensive vision software. 

First, they turned to cloud computing since it had an abundance of processing power in datacenters but quickly realized that it was not a viable option. Due to high data bandwidth costs, dependency on stable connectivity—especially challenging during packed stadium events with thousands of connected devices—and the latency that undermined the AI system’s responsiveness, cloud computing was unable to deliver. 

Edge computing was essential for their AI vision lighting system, which required real-time capabilities to detect, track, and adjust the lights dynamically. This demanding AI application required GPU acceleration to intake multitudes of detailed data and process it through a sophisticated AI model. Integrating a GPU-powered industrial computing solution is not as simple as it sounds. It poses challenges such as thermal management, size constraints, and continuous operations in harsh environments.  

 

Compatibility for High-Spec IP PoE Vision Cameras 

The stadium lighting manufacturer also needed to integrate multiple high-specification PoE vision cameras. These advanced cameras were essential for capturing precise, high-resolution footage of critical elements like the ball, players, field markings, and other key details within the stadium. Power over Ethernet (PoE) technology was pivotal to their system. By using a single cable for both power and data transmission, PoE enabled a streamlined, clutter-free configuration that reduced complexity and ensured reliable connectivity for the high-fidelity data needed to power the AI-driven lighting adjustments effectively. 

 

Stadium Lighting Deployment Restrictions 

Each stadium light pole is equipped to have a 15-foot-high driver-control cabinet to house vital electronic devices and prevent malicious tampering. Since these light poles are outdoors, the cabinet is exposed to the elements and requires the internal components to be just as operationally rugged in extreme weather conditions. Since this control cabinet is space-constrained and lacks ventilation, the edge computing solution not only needs to process intensive AI workloads but also be sizable enough to retrofit into the housing and remain operational in varying weather conditions.  

Additionally, the stadium lighting manufacturer required the edge computing solution to be UL certified. By meeting UL standards, the lighting manufacturer could ensure that the system is in compliance with safety standards and also expedites the overall system certification process. 

 

The Solution 


Premio understood the challenges that this stadium lighting manufacturer faced and recommended the RCO-6000-RPL Series AI Edge Inference Computer for them to start their pilot project. 
 

 

Industrial GPU Computers for Edge AI Vision Workloads 

The stadium lighting AI vision technology demanded significant processing power due to the resource-intensive nature of its real-time AI workloads. To address this, a dedicated GPU was essential for accelerating AI inferencing and delivering reliable performance. Premio’s RCO-6000-RPL Series AI Edge Inference Computer met these requirements with its extremely modular design and heterogenous computing with advanced edge AI components.

 
The RCO-6000-RPL Series is a high-performance industrial computer that leverages a powerful 13
th Gen Intel Core TE processor, blazing-fast DDR5 RAM, and high-speed NVMe storage. It seamlessly supported an NVIDIA RTX A4000 SFF Ada with 307 TOPS (FP8) of AI tensor performance through modular EDGEBoost Node technology. All of these edge computing components within the RCO-6000-RPL Series were vital to powering the AI vision stadium lighting model with extreme performance reliability.  

 

EDGEBoost I/O Technology for Advanced Vision Cameras 

In addition to enabling edge AI, the stadium lighting manufacturer required support for multiple advanced PoE vision cameras. These high-fidelity vision cameras are critical to streaming data to the industrial GPU computer for AI inferencing. However, powering multiple vision devices while simultaneously inferencing these instances is very challenging.

 
The RCO-6000-RPL Series was able to seamlessly address this requirement with the support of EDGEBoost I/O technology. Unlike EDGEBoost Nodes which is used for performance acceleration, EDGEBoost I/O provides a seamless approach to IoT connectivity and compatibility. The RCO-6000-RPL was configured with an EDGEBoost I/O module that featured four RJ45 LAN ports with PoE
 

 

Industrial-grade Reliability For Stadium Lighting  

The stadium lighting manufacturer needed to retrofit their components into a driver-control cabinet. These cabinets are mounted 15 feet above ground and directly onto the stadium light pole. This demanded a solution capable of meeting space constraints and withstanding harsh environmental conditions. The RCO-6000-RPL Series AI Edge Inference Computer addressed this challenge with a space-conscious construction while designed for industrial-grade reliability.

The RCO-6000-RPL Series features a fanless and cableless design, which ensures exceptional ruggedness by preventing the ingress of dust and debris. This design also supports wide operating temperature ranges, wide power input ranges, built-in power protection, and resistance to shock and vibration, ensuring reliable performance even in challenging environments. 

Internally, the RCO-6000-RPL Series aligns with a robust embedded computing philosophy. It incorporates an Intel Core TE processor, chosen for its power efficiency with a 35W TDP and inclusion in Intel’s 10-year embedded product lifecycle support. This guarantees long-term deployment consistency, reducing the risk of system redesigns or component obsolescence during its lifecycle. Driving the AI vision technology is an NVIDIA RTX 4000 SFF Ada GPU, which balances low power consumption (70W TDP) with high-performance AI processing. This GPU was specifically selected to meet the demands of the stadium lighting AI system while maintaining energy efficiency and reliability, making it a perfect fit for the rugged edge computing environment. 

With this combination of rugged design and cutting-edge internal components, the RCO-6000-RPL Series delivers the durability and performance required to power AI-driven stadium lighting systems under even the most demanding conditions. 

 

The Benefits  

As a leader in the edge computing industry, Premio provides additional value-added benefits to establish strong long-term partnerships with OEMs, system integrators, and industry 4.0 businesses.  

 

Tailored Edge Computing Portfolio for Diverse Stadium Deployment

The stadium lighting manufacturer, having initially selected the super-rugged RCO-6000-RPL Series, sought to diversify their edge computing solutions to optimize their deployment in varying stadiums. To address this need, Premio introduced the cost-effective, industrial-grade KCO-3000-RPL Series Fanned Industrial Computer. Both series share identical processor, memory, and GPU acceleration, ensuring equal edge AI performance and versatility for a wide range of AI vision applications.

 
While the RCO-6000 Series is designed for the harshest outdoor environments, the KCO-3000 Series is well-suited for demanding industrial settings. This flexibility allows the stadium lighting manufacturer to tailor their AI vision system to specific stadium requirements, deploying the RCO-6000 Series in challenging outdoor stadiums and the KCO-3000 Series in less harsh outdoor environments.

 

In-House Manufacturing Support 

Premio accommodated the stadium lighting company's product deployment by providing end-to-end manufacturing expertise. By collaborating to optimize BIOS configurations and flashing their proprietary OS images, Premio eliminated complex integration challenges for them.  Beyond configuration, Premio's comprehensive approach included rigorous burn-in testing protocols, ensuring exceptional product reliability. The result was a plug-and-play AI Edge Inference Computer that arrived fully configured and ready for immediate installation. Our in-house manufacturing capabilities allowed the stadium lighting manufacturer to bypass time-consuming technical preparations for accelerated system integration and reducing internal resource expenditure. 

 

Dedicated Engineering and Sales Support 

Premio’s sales and engineering expertise worked closely with the stadium lighting manufacturer at every step of the project. This personalized approach not only ensured a deep understanding of the project’s requirements but also helped minimize lead times. The close collaboration solidified the partnership to meet their needs quickly and effectively, paving the way for long-term success. 

 

Scalable Warehouse and High-Volume Production Capabilities 

With a robust 150,000 square feet facility and strategically based in Los Angeles, California, Premio demonstrated the capabilities to fulfill high-volume orders. This scalability was crucial for meeting the manufacturer’s current deployment needs and supporting future growth, enabling them to expand their AI vision lighting system without logistical delays.