Nut Core Computing Helps the Express Industry Practice Smart Logistics Strategy
Background
With the rapid development of the e-commerce industry, the total volume of express delivery business has grown rapidly. To cope with the surge in business volume and improve the collection and delivery efficiency of parcels, express delivery companies have implemented a grid warehouse strategy, using an intelligent distribution sorting system driven by visual artificial intelligence (AI) to automatically sort parcels. At the same time, due to the time-sensitive nature of the express delivery industry, it is also necessary to promote the optimization of full chain time efficiency. Therefore, express delivery companies are vigorously promoting a distribution video analysis platform to analyze distribution videos, including grid ports, and optimize incentive mechanisms and business management capabilities.
Requirements
  • High accuracy and low latency
  • high computational power
Solution

The Nut Core Computing servers S4212 is a high computing power platform solution designed for visual AI and intelligent cloud computing scenarios, based on Intel CPUs and NVIDIA GPUs. It can ensure the throughput of multithreading processing, while supporting hardware encoding/decoding of H.264, H.265 (HEVC), and AV1 encoding/decoding, which is highly compatible with the visual AI solutions of courier companies for image and video processing needs. Based on the comprehensive testing and branch pilot results, the visual AI solution based on this server can effectively meet the needs of express delivery companies in terms of computing power, latency, accuracy, concurrency ability, stability, and heat dissipation ability, and bring them business advantages.

Value
  • Improving business efficiency and reducing costs: The deployment of intelligent sorting systems significantly improves sorting line efficiency, thereby improving delivery efficiency and time efficiency, as well as achieving labor and cost savings.
  • Optimize business management and decision-making: Achieved more efficient allocation of video stream analysis, which can help optimize cross year/quarter forecasting, reasonable pricing, branch efficiency improvement, and reward and punishment formulation.