Transforming Stadium Lighting with AI-Driven Edge Computing

A global leader in innovative lighting solutions, the client has been at the forefront of designing and manufacturing advanced lighting systems for over 40 years. Their expertise spans industries such as sports, transportation, and infrastructure, offering cutting-edge arena and stadium lighting solutions. By continuously pushing the boundaries of lighting technology, they have enhanced athlete and viewer experiences with state-of-the-art LED systems, special effects, and mobile lighting solutions. Now, with the rise of AI vision technology, the company sought to revolutionise stadium lighting by integrating AI-powered vision processing into their systems.

To achieve this, they needed an industrial-grade edge computing solution capable of supporting high-performance AI workloads in real-world environments. This would enable the seamless and dynamic operation of AI-driven lighting systems to elevate the overall stadium experience.

After consultation, the lighting manufacturer identified several key challenges that needed to be addressed:

1. Lack of an Industrial Computing Solution for AI Vision

AI-powered lighting systems require real-time computing capabilities to detect, track, and adjust lighting dynamically. The manufacturer needed an edge computing platform that could handle resource-intensive vision AI models without relying on cloud computing, which posed several challenges:

• High Data Bandwidth Costs: Transmitting large volumes of video data to the cloud would incur significant bandwidth costs.
• Dependency on Stable Connectivity: Packed stadium environments with thousands of connected devices make maintaining stable internet connectivity difficult.
• Latency Issues: Cloud-dependent solutions could introduce delays, undermining the responsiveness of AI-powered lighting adjustments.

2. Compatibility with IoT Devices

The client needed an edge computing solution capable of seamlessly connecting multiple IoT devices. This included:

• High-spec Power-over-Ethernet (PoE) Vision Cameras: These cameras capture real-time footage of the game, players, field markings, and audience, providing data for AI-driven lighting adjustments.
• Sensors and Lighting Equipment: The system needed to respond dynamically to real-world conditions such as crowd movements and weather changes.

3. Rugged Reliability in Harsh Outdoor Conditions

Stadium lighting systems are housed within 15-foot-high driver-control cabinets mounted directly onto stadium light poles. These cabinets contain essential electronic components that must withstand:

• Extreme Weather Conditions: Exposure to heat, cold, rain, and dust is inevitable.
• Vibration and Shock: Outdoor environments expose the systems to physical impacts and vibrations.
• Limited Ventilation and Space Constraints: The solution needed to be compact yet powerful, with efficient thermal management.

4. Power-over-Ethernet (PoE) Connectivity for Vision AI Cameras

To simplify installation and reduce clutter, the client required PoE connectivity for multiple high-fidelity cameras and sensors. PoE technology transmits both power and data through a single Ethernet cable, eliminating the need for additional wiring and ensuring a streamlined setup.

5. Safety Compliance and Certification

To expedite deployment and ensure regulatory compliance, the client needed a UL-certified edge computing solution that met strict safety standards. Certification was essential to guarantee:

• Seamless System Approval: Faster regulatory approval for stadium deployment.
• Safety Assurance: Long-term reliability in outdoor environments, ensuring robust and hazard-free operation.

To address these challenges, C&T Solution Inc.’s RCO-6000-RPL Series AI Edge Inference Computer was recommended. This rugged, high-performance industrial computing solution is specifically designed for real-time AI workloads in challenging environments.

Key Features of the RCO-6000-RPL Series

• 13th Gen Intel® Core™ TE Processors: These processors deliver high-performance computing while maintaining energy efficiency, making them ideal for AI-driven applications.
• EDGEBoost Node Technology: Modular GPU acceleration via PCIe Gen 4 enables AI inferencing for complex vision models.
• EDGEBoost I/O Technology: RJ45 LAN ports with PoE support ensure seamless integration of cameras and sensors.
• Super-Rugged Design: A fanless and cableless design ensures resistance to dust and debris while maintaining long-term durability.
• Comprehensive Certifications: UL, CE, and FCC certifications ensure compliance with international safety and performance standards.

Industrial GPU Computing for AI Vision Workloads

To meet the high processing demands of real-time AI inferencing, the RCO-6000-RPL Series has been integrated with a NVIDIA RTX 4000 SFF Ada GPU. This AI-optimised GPU offers:

• Energy Efficiency: With a 70W TDP, the GPU balances power consumption with high-performance AI inferencing.
• Advanced AI Processing: The GPU enables real-time detection, tracking, and lighting adjustments to enhance stadium environments.
• Optimised Cooling: The fanless design ensures reliable operation, even in extreme conditions.

PoE-Enabled Edge Computing for Advanced Vision Cameras

The RCO-6000-RPL Series, equipped with EDGEBoost I/O technology, supports:

• Multiple RJ45 LAN Ports with PoE: This allows the system to power several high-resolution vision cameras simultaneously, ensuring a clutter-free and efficient installation.
• Real-Time AI Inferencing: The system processes large volumes of visual data on-site, enabling dynamic and responsive lighting adjustments.

Rugged Design for Harsh Stadium Environments

Designed for long-term outdoor deployment, the RCO-6000-RPL Series features:

• Compact Form Factor: The small size allows it to fit into space-constrained driver-control cabinets.
• Wide Operating Temperature Range: The system performs reliably in extreme weather conditions, from scorching heat to freezing cold.
• Shock and Vibration Resistance: This ensures durability and stability in outdoor installations.

Real-World Impact

By integrating C&T Solution Inc.’s RCO-6000-RPL Series, the lighting manufacturer successfully deployed an AI-powered edge computing solution capable of transforming stadium lighting. The solution delivered:

• Real-Time AI Vision Processing: The system dynamically adjusts lighting based on real-time data, enhancing the viewing experience for both live and remote audiences.
• Seamless Integration: PoE cameras, sensors, and lighting equipment work together seamlessly, streamlining the overall setup.
• Rugged Reliability: The system operates flawlessly in extreme outdoor conditions, ensuring long-term performance and minimal maintenance.
• Reduced Latency and Connectivity Issues: By processing AI workloads at the edge, the solution eliminates the need for cloud-based operations, addressing latency and connectivity challenges.

The integration of C&T Solution Inc.’s RCO-6000-RPL Series AI Edge Inference Computer marks a significant leap forward in stadium lighting technology. By harnessing the power of AI-driven edge computing, the lighting manufacturer has set a new standard for dynamic and responsive stadium illumination. The system not only meets the demanding requirements of modern stadiums but also enhances the overall experience for athletes, spectators, and event organisers alike.

This groundbreaking solution demonstrates how innovative technology can address complex challenges, paving the way for smarter and more efficient infrastructure across various industries. As AI and edge computing continue to evolve, their transformative potential in applications like stadium lighting will only grow, unlocking new possibilities and redefining what is achievable in modern venues.