On December 25, a cargo ship loaded with iron ore docked at Qianwan Terminal of Qingdao Port in Shandong Province. Unlike traditional procedures, port planners no longer need manual adjustments for berthing schedules. Instead, the newly developed "Berthing Intelligence System" integrates real-time data on vessel schedules, tides, and other critical factors to generate optimal berthing plans while simultaneously issuing operational commands—achieving seamless "work-on-arrival" efficiency. This marks a significant milestone in AI-driven port operations.
As the first national AI application pilot base in China's transportation sector dedicated to ports, Qingdao Port has focused on industry-wide challenges since its establishment on September 9. By consolidating resources in industry, data, computing power, and talent, the port has built a comprehensive innovation chain encompassing R&D, scenario validation, industrial incubation, and ecosystem development. Within just three months, it successfully launched two major innovations: a visual AI model for safety monitoring and a multi-scenario dry bulk cargo operations cluster. These breakthroughs exemplify the cultivation of next-generation productivity and mark a critical step toward data-driven, intelligent collaboration.
**Safety Visual AI Model: 500+ Smart Cameras for Full-Scene Monitoring** Addressing the limitations of traditional "on-site inspection + video surveillance," Qingdao Port's AI model—piloted at Dagang Terminal—establishes an intelligent safety inspection system. Anchored to 137 general and 71 severe violation protocols, the model covers 99 high-risk scenarios. Its hybrid approach of "fast small-model detection + comprehensive large-model analysis" enables 500+ cameras to function as round-the-clock "AI safety inspectors," instantly capturing violations with real-time alerts. Notably, the model introduces three industry-first features: 1. **No-code visual development**, allowing non-technical staff to configure systems via graphical interfaces. 2. **Dynamic violation-scenario input**, enabling interactive updates by safety personnel. 3. **Full-dimensional integration** of violation cases for a flexible smart recognition framework.
Since deployment, the model has promptly identified multiple violations, enhancing precision in safety management. Future plans include expansion to container and dry bulk terminals, with scalable solutions for the industry.
**Dry Bulk AI Cluster: 80% Berthing Accuracy, 99.8% Debris Detection** The AI cluster optimizes core processes like vessel berthing, cargo transfer, and rail dispatch. The "Berthing Plan Intelligence System" automates scheduling by synthesizing 132 vessel parameters, achieving 80% accuracy in berthing plans while enabling end-to-end automation from equipment positioning to workflow initiation. Key innovations include: - **Conveyor Belt AI**: Integrates semantic interaction and smart controls, reducing false alarms to 0.2% with 99.8% debris detection. - **Stacker-Reclaimer Automation**: Combines vision and radar for 94% automation and collision avoidance. - **Digital Yards**: Enable unmanned operations via precision geo-fencing.
In loading/dispatch, AI-driven gantry cranes achieve 100% safety detection and 80% autonomous operation, while smart rail systems automate 97.24% of loading processes. These advancements position Qingdao Port as a blueprint for dry bulk terminal modernization.
**Pilot Base Expansion: 26 Demo Scenarios Underway** Backed by unified data standards (187 items) and a centralized data platform (1,000+ services), Qingdao Port has emerged as a national leader in high-quality datasets. Its AI multimodal dataset was recognized as a benchmark case, while its scheduling AI won top honors in a national transport innovation competition. Three projects also ranked among "Qingdao’s Top 100 AI Products."
Looking ahead, Qingdao Port aims to establish dual hubs for "R&D demonstration and成果转化" by 2026, driving standardization and ecosystem growth to advance AI integration in transport and实体经济.
