Millennium Canal Sparked with Digital Intelligence Vitality
The entire length of the Su Bei Canal is 475 kilometers, making it the highest-grade navigational channel of the Beijing-Hangzhou Grand Canal and the busiest golden waterway in terms of ship density, with cargo throughput exceeding 300 million tons for 12 consecutive years. This major transportation artery slopes north-to-south, with 11 navigation cascade levels and 30 ship locks along its route, creating the largest inland ship lock cluster in the country. As inland waterway freight continues to thrive, issues such as insufficient coordination for cross-lock scheduling under traditional ship lock operations, reliance on manual safety supervision, and relatively short transport service chains are gradually emerging.
Jiangsu's transportation department, based on the realities of the Su Bei Canal, has established an integrated digital sensing system encompassing "air, ground, and underwater," aggregating multidimensional data including ships, waterways, locks, hydrology, and meteorology. It has developed three core models: multi-tier ship lock network scheduling, automatic operation supervision for locks, and the "Big Canal Smart Navigation" assistant, utilizing digital and intelligent methods to revolutionize ship lock operation models and infuse fresh vitality into the millennia-old canal.
Smart Network Scheduling for Seamless Waterway Traffic
In the past, ship locks on the Su Bei Canal operated independently. When encountering lock repairs, water condition changes, or severe weather, there was a lack of downstream and upstream linkage, easily leading to ship congestion and navigational bottlenecks. To unlock full-line navigation bottlenecks, the key lies in achieving multi-tier ship lock coordinated linkage.
Jiangsu was the first in the industry to implement the Ship Info App, enabling one-click lock crossing applications, full-line information overview on a single screen, and command-based navigational scheduling on a map. The AI multi-tier ship lock network scheduling model collects real-time data on ship movements across the entire navigation segment, lock statuses, water levels, and meteorology, automatically generating coordinated scheduling plans for the entire line, proactively predicting navigational risks, and shifting from reactive handling to proactive prevention.
In May this year, during a major repair of the Liu Lao Jian No. 3 ship lock, the number of ships waiting to cross surged. Upon system identification of navigational warnings, the AI scheduling model quickly initiated an emergency coordinated scheduling mechanism. On one hand, the model balanced the navigational load by coordinating the progressive release of ships at upstream and downstream locks; on the other hand, it guided some ships to shift to branch waterways for distribution, quickly alleviating navigation pressure. Relying on this intelligent scheduling system, the Su Bei Canal has consistently achieved seamless "green wave" water traffic, eliminating bottlenecks where "one lock jams the line, slowing everything downstream."
Improved Safety Coefficients and Operational Efficiency
Varying lock sizes, diverse ship types, and compounded variables such as water conditions, weather, and construction bring multiple challenges to the safe and efficient operation of ship locks. The AI automatic operation supervision model consolidates nearly a thousand scheduling rules and integrates various dynamic sensing data, outputting optimal lock scheduling plans and ship docking schemes within seconds, maximizing lock chamber utilization and lock passage efficiency.
Using intelligent sensing devices such as video and sensors, the Su Bei Canal achieves grid-based and around-the-clock inspections in ship lock areas, transitioning safety supervision from traditional "manual defense" to "intelligent defense." The system integrates with lock control devices, enabling automated lock operations while ensuring safety and exploring an "unmanned station, emergency-only staffing" operational model. The entire lock-crossing process requires no manual on-site operation as gate opening/closing, water level adjustment, and ship docking are all completed autonomously by the system, simultaneously enhancing navigation safety and operational efficiency.
Intelligent technology extends beyond ship lock operations and reaches the two ends of the spectrum: seafarers and logistics companies, building a digitized service system encompassing the entire transportation chain. For seafarers, the "Big Canal Smart Navigation" assistant works like a water-based GPS, intelligently planning optimal routes based on ship travel paths and providing real-time safety warning information such as water depth and bridge clearance. It also includes intelligent voice customer service, catering to the habits of elderly crew members and responding swiftly to various inquiries and rescue requests.
For ports, manufacturing, and logistics enterprises, the transportation department conducted a "100-company needs survey" to deeply explore sector-specific demands, introducing specialized data products such as "ship lock crossing schedules." Enterprises can track the real-time locations of ships and predict arrival times to optimize production planning, procurement, and inventory management. A representative from Huaian Zhongtian Steel Group told reporters that after integrating the system, their inventory turnover rate increased by over 52%, significantly enhancing the efficiency of supply chain operations.
The implementation of a series of AI technologies has led to noticeable changes: the operating efficiency of ship locks on the Su Bei Canal has increased by 18%, the average wait time for ships to cross locks has decreased by 21%, the emergency response time for unexpected incidents has shortened by more than 30%, and satisfaction with shipping services along the route has consistently remained above 99%. Currently, this practical experience has been promoted across trunk waterways in Jiangsu Province and has attracted several domestic navigation management units to exchange and learn from it.
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