Traffic systems rely on all kinds of sensors and IP cameras to gather real-time information from the field regarding traffic flows and congestions. Such information could be used to control traffic lights, information displays, video cameras, actuators, or simply to monitor traffic flows.
Read more: Rugged AI Platform for Traffic Management
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A few extensive warehouse facilities are already using some sort of automation, especially Autonomous Mobile Robots (AMRs), to help them stay ahead in their industry. But AMRs don’t come without challenges, especially when deploying them indoors in closed spaces. AMRs need to respond in real-time; they need to be able to make decisions on the go.
In this solution, we propose Lanner’s edge Artificial intelligence (AI) appliance EAI-I130. This onboard industrial-grade AI inference system can empower AMRs at a large-scale warehouse by providing an AI inference system and allowing them to operate at a private 5G edge network.
AMRs use onboard sensors, cameras, and processors to move and transport other objects around without needing guidance. To help AMRs navigate easily across large-scale warehouses and plan their routes, they can also be deployed with pre-defined maps. But one of the critical technologies for AMRs is Artificial Intelligence (AI).
With AI, not only can AMRs detect and navigate around objects with more precision, but they can also learn from experience and adjust their behavior to new inputs. For instance, AMRs-empowered with AI can learn to avoid high-traffic areas or when the warehouse is too crowded with warehouse staff to move around.
To operate efficiently in large-scale warehouses, AMRs require the following:
One of the best ways to solve the challenges mentioned above is to bring AI models to operate on the edge device (Edge AI). This approach reduces (and eliminates in most cases) the need for an Internet connection and cloud computing. Bringing AI to the edge also produces extra low latency results, achieving faster AI inference and supporting real-time use cases such as AMRs.
Lanner’s EAI-I130 is an industrial-grade AI inference system for 5G edge, powered with NVIDIA® Jetson Xavier NX/Jetson Nano. The embedded GPU computer (NVIDIA Jetson family) boasts 21 Tera Operations Per Second (TOPS) for AI performance and energy efficiency.
The EAI-I130 also supports 5G/Wifi6 for robust wireless communications to ensure fast and reliable communication to an AMR monitoring and management base. In addition, the appliance can operate in harsh environments, as it also comes with a fanless design and is compliant with the IP40 standard.
The EAI-I130 can empower AMRs at a large-scale warehouse by providing an onboard AI inference system and allowing the AMR to operate on a private 5G edge network.
Below is a diagram of how the AMR with embedded GPU computing operates with the EAI-I130. The AMR relies on its built-in sensors to collect data from the external environment. This data feeds into the edge AI appliance (EAI-I130), which processes it onbard. In addition, with a private wireless network (Wifi6, 4G, or 5G), the AMR can also send data to the cloud or a high-end server for further analysis, storage, or remote monitoring.
The main benefit of an edge AI solution for the AMR is that it brings the proper computing performance closer to where data is generated— to where sensors are located (in the Autonomous Mobile Robot). An edge AI computing platform like Lanner’s EAI-I130 allows AI to run directly on the AMRs, without having data leaving the warehouse floor. Running AI on the AMR can immediately enable real-time processing, lowers the need for bandwidth, and strengths security.
The EAI-I130 appliance processes collected field data and runs the necessary deep learning algorithms to help the ARM navigate and learn. In addition, the collected data can also help predict future demand, gain insights, or improve current processes. All benefits will ultimately generate new sources of revenue and save additional costs.
AMRs with embedded GPU computing bring logistic…
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With escalating inflation and supply chain challenges, retailers need to consider adding new technologies to their businesses to both enrich their offerings to attract new customers, amplify customer loyalty, and increase process efficiencies, while reducing costs in the long run. Automation and technology can change both customers’ and employees’ experience in the store, from new ways for consumers to find and pay for items, to information systems for workers.
Read more: SD-WAN Accelerating Digital Transformation for Distributed Fuel Retailers
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The ISD-O370 (from Lanner) is an edge-rugged cellular router. It is compliant with IP67 and the MIL-STD standards (to ensure the device operates in harsh environments) and also supports 5G and Wi-Fi 6 for demanding wireless applications. The appliance can also provide edge computing capabilities. It runs on Linux on Intel’s Atom C3000 with up to 64GB DDR4 (64GM eMMC).
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With the continuously growing demand for consumer electronic applications, creating increased data transfers from emails, video conferencing, and remote applications, often utilizing unprotected public networks, makes productivity application tools vulnerable to attacks. The increasing number of network security breaches, increasing adoption of cloud technologies, the trend of network automation, and 5G networks, makes protecting network transmitted data imperative, further increasing the demand to improve network security.
Read more: Network Encryption Appliance Enable Quantum-Safe Security HSM Solutions
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