•
Apr 15
Sand Technologies
Over 80% of global trade flows through marine terminals. Congestion, security vulnerabilities and outdated systems slow operations at these critical hubs, creating ripple effects across supply chains and economies. As a result, many terminals are turning to AI for improved operations. The magnitude of this trend has caught the attention of leading research companies like Research and Markets, which added port and terminal operations to their research report offerings last year. The firm valued the market at $23 billion in 2023, set to reach $232.6 billion by 2030.
U.S. ports lag behind their global counterparts in automating terminal operations. However, the news isn’t all bad. The top ten U.S. terminals have at least some automation. AI and data analytics can further transform US terminal operations by enhancing operational efficiency, elevating worker safety and terminal security, and shifting from reactive to predictive decision-making. That translates to a critical market advantage for terminal managers in an increasingly competitive global shipping environment.
Marine terminals and ports are getting busier. The global ports that adopted AI have become hubs of efficiency and precision, transformed into “smart terminals” with predictive analytics. For US terminals, leveraging AI is not just an innovation; it’s a necessary step toward creating a more efficient and sustainable shipping industry.
Congestion can add millions to the cost of shipping. AI reduces these costs with optimized vessel traffic by analyzing real-time data, such as weather patterns, vessel schedules and terminal capacity, and maximizing the movement of vessels in and out of the terminal. Advanced algorithms ensure that arrival and departure times are perfectly synchronized, minimizing bottlenecks and wait times.
AI-powered systems analyze real-time data to predict vessel arrivals, ensuring that pilots and tugboats are scheduled with precision. Berth allocation becomes seamless, with dynamically assigned dock spaces based on vessel size, cargo type and departure schedules. These improvements optimize vessel traffic and cargo movement, ensure efficient workforce and equipment use, and reduce operational expenses.
In 2024, US terminals received 28,196,462 twenty-foot equivalent units (TEUs), a 13% increase from 2023. As shipping volumes continue to grow, efficiency in yard operations is critical. AI-driven algorithms can determine the optimal container stacking order, ensuring faster and more precise retrieval. This capability eliminates unnecessary crane movements, reduces vessel turnaround times and maximizes yard space utilization. This capability means terminals are better positioned to handle increased trade volumes while minimizing delays.
AI is ushering in a new era of efficiency and safety for marine terminals. Looking at CDC U.S. port injury data from 2011 – 2017, the annual fatality rate was 15.9 per 100,000 workers, five times the rate for the rest of the U.S. workforce. The injury rate was 4,916 per 100,000, almost double that of the U.S. workforce. This data should make employee safety a chief use case for AI in terminal operations.
AI-powered wearable devices and cameras can monitor worker activities in real time, ensuring compliance with safety standards. These tools detect unsafe behaviors and identify potential hazards, providing immediate alerts to prevent accidents before they occur. Advanced AI systems can detect when workers enter restricted areas or fail to wear mandatory safety gear. This proactive approach elevates the safety of the workforce and improves adherence to safety regulations.
Marine terminals must address many threats, including unauthorized access, smuggling and cyberattacks. AI can bring unprecedented efficiency and security to a global trade hub. AI-powered surveillance systems can monitor the entire terminal in real time, identifying anomalies and potential threats that standard monitoring methods might miss. With AI analyzing live video feeds, terminals can proactively identify real-time suspicious activities, unauthorized access and possible security breaches.
Advanced AI systems can also identify suspicious patterns in shipping manifests that could indicate smuggling or illegal activity. These insights are generated faster than traditional methods, allowing security teams to respond proactively.
Companies in many sectors are moving from reactive to proactive decision-making, particularly in industries with heavy equipment. AI and data analytics are proving highly effective in predicting when equipment needs maintenance or is nearing failure.
Marine terminal operations can cost from $1 million to $10 million for medium to large terminals. Considering that maintenance costs run 10-20% of this budget, moving from a reactive to a predictive stance on equipment maintenance can lead to significant savings.
AI enables predictive equipment maintenance so marine terminals can anticipate when critical machinery, such as cranes or container handling equipment, requires servicing. This proactive approach extends the life of the equipment, prevents potential injury to dock workers and minimizes unexpected downtime. The ripple effects are cost savings, worker safety and a more favorable reputation among shippers.
AI will revolutionize marine terminal operations by transforming terminal managers’ planning strategies. Advanced algorithms can predict potential bottlenecks, optimize container placements and allocate resources dynamically, streamlining operations and reducing delays. This ability will give marine terminal managers the tools to stay ahead of demand fluctuations.
For example, by analyzing historical data and current market trends, AI systems can accurately predict future shipping volumes, allowing marine terminals to optimize their resources and operations with unparalleled precision. This capability means fewer delays, smarter allocation of labor and equipment and the ability to anticipate ebbs and flows in demand well before they happen. The result is a more efficient supply chain, reduced costs and strengthened reliability — key factors in maintaining a competitive edge in today’s fast-moving global shipping market.
Leveraging AI-powered systems and utilizing real-time data requires an integrated view of all data across terminal operations. AI-powered platforms can consolidate data from disparate sources — including vessel schedules, cargo manifests, weather patterns, etc. — providing terminal managers with a comprehensive view of the entire operation. With AI, they can anticipate disruptions, automate decision-making and allocate resources more effectively, lowering costs and improving reliability. For marine terminals, the integration of AI isn’t just an upgrade — it’s a fundamental shift toward smarter, more agile operations.
How does it work?
Marine terminals need consolidated data for insights that lead to better decision-making. But, like most organizations, terminal data is in silos. It turns out AI can play a crucial role in combining data silos in several ways, enabling marine terminals to have unified data that unlock valuable insights.
AI handles intelligent data integration by automatically identifying and ingesting data from various sources, regardless of format or location, reducing manual integration effort and errors. It also performs smart data mapping. AI can understand the structure and semantics of data from different silos and automatically map fields and transform data into a consistent format, even with complex datasets. Furthermore, AI algorithms can identify and correct inconsistencies, errors and duplicates in data, ensuring accuracy and reliability.
With combined data, marine terminals can leverage AI and digital twins for advanced analytics, uncovering insights and performing accurate what-if scenario planning. To do this, AI conducts pattern recognition and anomaly detection to identify hidden patterns, correlations and deviations humans might miss. In addition, AI’s predictive analytics use historical data, including terminal SCADA data, to forecast future trends and outcomes, enabling proactive decision-making. Moreover, natural language processing (NLP) can analyze unstructured data like text documents and video to extract valuable insights that were previously inaccessible.
The result?
Consolidated data breaks down organizational barriers, facilitating collaboration and communication between departments and teams by providing a unified data view. AI-powered tools democratize data, making it easier for users across the organization to access and analyze data, regardless of their technical expertise.
Other articles that may interest you
