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Rugged Fanless PC Powers Real-Time AI Inference on Smart Factory Floor

A leading provider of material handling equipment approached Things Embedded to integrate advanced technology into their operations. Seeking a rugged fanless PC with built-in GPU, they aimed to enhance the intelligence and efficiency of their solutions. These embedded systems were required to support demanding real-time AI applications, enabling smarter and more reliable material handling across diverse industries.

Driven by a commitment to innovation, they provide comprehensive material handling solutions customised to meet each customer’s unique needs. Their end-to-end approach encompasses warehouse optimisation, fleet management, and operator training, ensuring enhanced efficiency, productivity, and safety across various industries. With expertise in electric forklifts, pallet jacks, reach trucks, and AGVs, this solutions provider empowers customers in sectors such as retail, warehousing, and distribution to transform their material handling operations.

Transitioning to a Smart Factory Floor with Real-Time AI Inference

The transition to smart factory floors introduces new opportunities and challenges, especially with the integration of autonomous vehicles into material handling operations. One key requirement is the need for advanced pedestrian avoidance systems and precise route navigation to ensure the safe and efficient movement of autonomous vehicles. Unlike traditional operations, smart factories demand systems that can adapt to dynamic layouts and fluctuating traffic patterns. Legacy detection systems often struggle in these environments, resulting in false alarms or missed hazards, which can lead to safety risks, operational disruptions, and increased costs.

Autonomous vehicles play a crucial role in optimising material handling on smart factory floors. However, their successful deployment depends on real-time AI inference and advanced data analytics to monitor vehicle movements, prevent collisions, and adapt to real-time changes. The harsh conditions of factory floors, including shock, vibration, and dust, further necessitate the use of rugged computing systems that can withstand these challenges. By leveraging embedded systems with integrated GPUs or AI Accelerators, smart factories can enhance safety, streamline operations, and make better, data-driven decisions to achieve greater productivity and efficiency.

Deploying discrete GPUs in harsh industrial environments presents several technical challenges. Discrete GPUs typically require high power input and active cooling with onboard fans to manage heat dissipation. The additional exposure to constant shock, vibration, dust, and debris can also degrade system performance and reliability, increasing the risk of hardware failure and maintenance costs.

NVIDIA, renowned for designing and manufacturing cutting-edge discrete GPUs for industrial applications, has expanded its innovation to edge computing with the introduction of NVIDIA Jetson, a powerful platform tailored for AI-driven edge applications. Part of the latest Jetson series, the Orin NX system-on-module provides an efficient alternative. Capable of delivering up to 100 TOPS of AI performance with a low-power draw of 10-25W, these system-on-modules can be integrated inside ruggedised PCs. This makes the latest embedded system architecture from NVIDIA ideal for real-time AI inference in harsh environments without the need for active cooling or high energy consumption.

Enabling Edge AI with Ruggedised Fanless PCs

Integrating a rugged fanless PC powered by the NVIDIA Jetson Orin NX architecture delivered ground-breaking advancements for the customer’s autonomous vehicles being deployed in smart factory environments. Equipped with powerful AI capabilities, the JCO-3000-ORN-B by C&T Solution enhances real-time object detection and pedestrian avoidance, optimising route navigation to minimize risks and promote workplace safety. Their ability to process and analyse imaging data instantaneously ensures seamless adaptation to shifting layouts, traffic patterns, and environmental conditions, making it an indispensable solution for dynamic material handling and evolving industrial workflows.

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