AI Captains Log

Driving Blind at Sea?

AI Captains Log — Wed, 26 Aug 2026 19:01:17 GMT

Traditional depth sounders only show where your vessel has been which is a critical limitation that leaves mariners vulnerable to dynamic sandbars and migrating shoals. In this episode of AI Captains Log, host Elizabeth Fortunato speaks with Alexia Fountain from FarSounder to explore how 3D forward-looking sonar provides real-time underwater visibility up to 1,000 meters ahead.

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What You’ll Learn in This Episode:

The Pitfalls of Traditional Sounders: Why downward-looking depth sounders are like “driving a car on the highway while looking strictly at the floorboards”.
Phased Array 3D Technology: How FarSounder’s Argos series uses a single ping to capture an entire field of view without motion blur or latency.
Seabed 2030 & Crowdsourced Data: How private vessels and recreational cruisers can act as survey platforms to help map the global ocean floor.
Sensor Fusion & AI Navigation: How integrating sensor data and AI assistance enhances situational awareness on the bridge while keeping human judgment at the helm.

Episode Chapters:

00:00 - Navigating the Future of Maritime Technology
04:04 - The Evolution of Sonar Technology
09:00 - Identifying Underwater Hazards
12:29 - The Importance of Sensor Placement
17:20 - Environmental Impacts on Marine Navigation
22:04 - Contributing to Seabed 2030
26:10 - Turning Private Vessels into Survey Platforms
30:14 - Sensor Fusion & Comprehensive Perception
35:15 - AI Assistance on the Modern Bridge
39:58 - The Future of Autonomous Maritime Navigation
47:03 - Charting the Future of Underwater Perception

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Links:

Alexia Fountain’s LinkedIn: https://www.linkedin.com/in/alexia-fountain-135a28234/
FarSounder: https://www.farsounder.com/
SeaBed2030: https://seabed2030.org/our-mission/
Elizabeth’s LinkedIn: http://linkedin.com/in/elizabeth-fortunato-idratherbeonaboat

My other channels:

YouTube
Apple Podcasts:

Spotify
PocketCast: https://pca.st/b2e88tfi

Agentic AI Moves From the Bridge to the Back Office

AI Captains Log — Mon, 17 Aug 2026 12:03:45 GMT

Rather listen than read? Need something to make the daily commute actually useful?

I’m launching a new audio newsletter series to make catching up on maritime tech as easy as pressing play.

This week: AI isn’t just taking the wheel—it’s quietly taking over the back office. Here is what’s shifting from the bridge to the desk 🧵👇

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While maritime tech conversations often spotlight autonomous steering on the bridge, the fastest operational shift is quietly taking hold in back-office workflows ashore. This audio newsletter breaks down how administrative AI systems are making financial and contractual decisions across both commercial shipping and recreational boating.

Episode Highlights

Agentic AI in Commercial Shipping: Pilot programs are deploying agentic AI to interpret dense charter party contracts, automate voyage orders, and manage insurance claims. Speed and document processing scale rapidly, but human validation remains mandatory to review outputs.
AI Valuations in Recreational Boating: Boat dealers are adopting AI-powered lead scoring to increase revenue by up to $8,700 per lead, while platforms like NextBoat and MarineMax apply automated valuations to used vessel inventory. Meanwhile, buyers aged 28–42 are shifting toward digital-first channels, researching on YouTube and social media before reaching a dealer.
Auditing the Algorithm’s Math: Unlike a bridge camera failing to spot an obstacle, errors in AI lead scoring, claims processing, or legal contract extraction are invisible. The critical human oversight role must expand from the helm to the back office to audit reasoning and ensure accountability.
Industry Radar Sweep: A quick look at Level 1 and 2 sensor fusion exceeding human perception in low visibility, private 5G networks powering automated port cranes to cut labor costs by 25%–55%, and rotor sails delivering double-digit fuel savings.

Press play above to listen to the full audio breakdown.

Where in your maritime or business operations would you feel most comfortable handing tasks over to an AI agent?

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Agentic AI Takes On Contracts and Claims as Boating Retail Goes Algorithmic

AI Captains Log — Fri, 14 Aug 2026 19:01:54 GMT

Agentic AI Moves From the Bridge to the Back Office

Much of the maritime AI conversation has centered on navigation and safety, but a newer strand of development is aimed at the industry’s massive amount of paperwork. Agentic AI (AI systems capable of independently carrying out multi-step tasks rather than simply answering a query) is being piloted for interpreting charter party contracts (the legal agreements that set out the terms for hiring a vessel), automating voyage orders, and streamlining claims management, according to a review of 2026 maritime technology trends from MLA College.

The benefit of using agentic AI for these processes is speed and consistency in functions that have historically relied on manual review by brokers, operations staff, and claims handlers. Interpreting a charter party contract, for example, requires parsing dense legal language to extract obligations around laytime (the time allotted for loading and unloading cargo) and demurrage (fees owed when a vessel is delayed beyond that allotted time). This is all work that agentic systems can flag and route without a person reading the full document first. (Caveat: A human MUST review the output and validate the response.)

AI Generated image of Agentic AI and human interaction

The technology is still early-stage, deployed alongside more established operational AI.

Predictive maintenance algorithms continue to analyze engine performance, vibration, and temperature data to flag component degradation before failure, and AI-driven voyage and weather routing is reported to cut fuel costs by up to 15%. AI-based anomaly detection is also being applied to cybersecurity as vessel and shoreside networks grow more connected which is a parallel sign that AI adoption in shipping is expanding beyond the bridge into operations, finance, and IT.

[Note: Keep an eye out for my upcoming series on ‘What concepts from commercial and federal IT transfer into the maritime domain, and what must change when those concepts are applied at sea?’ Part 1: Cybersecurity]

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Down to the Helm: AI Integration and Leading Trends in Recreational Boating

Lead scoring and valuation: AI-powered lead scoring is letting boat dealers prioritize prospective buyers more precisely, with some implementations linked to an additional $8,700 in revenue per lead, according to boating marketing research from Amra & Elma. Wholesale and trade-in platforms such as NextBoat are applying similar AI-driven valuation tools to used-boat inventory through its dealer partnership with MarineMax. NextBoat is anticipating recurring, “annuity-like” revenue from the financing and insurance renewals tied to processed vessels, per its investor relations announcement.

Fishing apps lag on conversion: Even as the broader fishing app market is projected to grow from $1.40 billion in 2026 to $2.61 billion by 2033 (according to Coherent Market Insights), most fishing-specific mobile apps still rely on ad-supported, freemium models, and developers continue to struggle converting free users into paid subscribers.

Market outlook: Mordor Intelligence projects the recreational boating market will reach $37.64 billion by 2031, growing at a CAGR of 5.10% over the 2026–2031 period. The electric boat segment is forecast to grow faster still, reaching an estimated $15 billion to $22 billion by 2033–2035 at a CAGR of 8–13%, according to industry market research.

Who’s buying: First-time boaters between the ages of 28 and 42 increasingly research purchases through YouTube tutorials and social media before ever contacting a dealer. This reinforces ‘digital-first tools’ like Argo Navigation’s LOOKOUT-powered hazard detection and NextBoat’s dealer platform as competitive differentiators against slower-moving incumbents.

AI Captains Log take: Who reviews the algorithm’s math?

This week’s commercial and recreational stories share a quieter technology thread than navigation or collision avoidance: Administrative AI. This is one of my favorite use cases for AI where systems can be trained to make or accelerate business decisions rather than steer a vessel. As I discussed, on the commercial side, agentic AI is being tested against charter party contracts, voyage orders, and insurance claims. On the recreational side, AI-powered lead scoring and vessel valuation tools are already shaping which buyers dealers pursue and what a used boat is deemed worth.

Both applications share the same appeal: they offer speed and consistency at scale. They also share a similar risk: the reasoning behind an AI-generated valuation, lead score, or contract interpretation is often less visible than the reasoning behind a docking assist or a hazard alert. A captain can see a hazard-detection camera miss an obstacle. It is harder to see why an algorithm scored one buyer above another, or how a claims system weighted a disputed clause.

That is where the human oversight requirement shifts from the helm to the back office. Commercial operators adopting agentic AI for contracts and claims are, at least in principle, subject to established review processes, insurers, and counterparties who can contest a decision. The recreational buyer scored by an AI lead-generation model, or the dealer relying on an automated wholesale valuation, requires that a human review the results and make the final evaluation to ensure there is no bias or hallucination.

As these financially consequential systems reach both ends of the market, the harder question isn’t whether the algorithm is fast or consistent — it’s whether the people using the output can be held accountable for the results. What is your take?

What is your take? Leave a comment:

Leave a comment

Now onto the rest of the news.

Industry Rundown

Autonomous Navigation and Robotics

Sensor fusion at Level 1 and Level 2: According to Orca AI, most current autonomous capability sits at Maritime Autonomous Surface Ships (MASS) Level 1 (decision support) and Level 2 (partial autonomy), combining radar, lidar, the Automatic Identification System (AIS), and optical or thermal cameras into a single situational picture. This level 2 ‘sensor fusion’ can, in some conditions, particularly limited visibility, exceed human perception.

Remote oversight expands: Shore-based control centers are increasingly involved in overseeing autonomous trials, extending to remote-controlled collision avoidance and route tracking rather than fully onboard decision-making.

Smart Ports and Infrastructure

Private 5G networks: Ports continue rolling out private 5G networks to supply the low-latency, high-bandwidth connectivity that automated cranes and robotics require to operate without communication dropouts, per Niral Networks.

Automated cargo handling: Automated guided vehicles (AGVs) and automated stacking cranes are enabling round-the-clock container movement, with some automated terminals reporting labor cost savings of 25% to 55% over manually operated equivalents, according to Hexaware Technologies.

Digital twins and IoT: Ports are building digital twin platforms — virtual models of terminal operations — to simulate infrastructure and traffic changes, while Internet of Things (IoT) sensor arrays monitor quay wall integrity and container status in real time.

Decarbonization and Propulsion Innovation

Alternative fuels: Liquefied natural gas (LNG) remains the primary transitional fuel for reducing sulfur oxide (SOx) and nitrogen oxide (NOx) emissions, while hydrogen fuel cells and ammonia-ready engine designs are progressing through pilot phases toward broader commercial adoption.

Wind-assist propulsion: Rotor sails and suction wings are delivering double-digit percentage fuel savings on retrofitted vessels, while slow steaming to reduce a vessel’s speed to cut fuel burn, remains a primary lever for legacy fleets that haven’t added new propulsion hardware.

Rotor and Suction Wing Sails

Regulation and Policy

Autonomy liability framework: Progress toward Level 4 (fully uncrewed) vessel operation remains contingent on international legal frameworks that address crew liability, insurance, and standardized fault assignment when an autonomous system is involved in an incident — questions that remain unresolved ahead of the International Maritime Organization’s (IMO) targeted 2027 consensus on its MASS regulatory framework.

Sources

About The AI Captains Log

The AI Captains Log charts the transition from traditional seamanship to the age of maritime autonomy, tracking how artificial intelligence and emerging technology are reshaping navigation, safety, and operations on the water. It gives mariners a clear, credible way to stay ahead of the developments reshaping the industry — the advances that matter, explained without the hype, noise, and advertising.

The channel reaches its audience through four formats:

This newsletter — a consolidated weekly briefing on the latest advancements in maritime AI and technology.
The podcast — conversations with industry professionals, researchers, engineers, and captains shaping the maritime industry.
In-depth articles — deeper explorations of the technologies changing how we operate, navigate, and learn.
Subscriber-only access — the good, bad and ugly of boating.

Subscribe now

Want to contribute to the conversation or appear on the podcast?

Fair winds and following seas,

Elizabeth Fortunato — The AI Captains Log

Navigating the Kadey Krogen Bankruptcy: Where Our Boat Stands & What Every Boat Buyer Needs to Know

AI Captains Log — Sun, 09 Aug 2026 17:36:49 GMT

In this update, I cover the latest developments following our first bankruptcy hearing regarding Kadey Krogen Yachts, clarify misconceptions about the Taiwanese builder, share critical lessons for fu…

From Navy Watch Officer to AI Vibe Coder

AI Captains Log — Sun, 09 Aug 2026 15:28:10 GMT

In this episode of AI Captain’s Log, host Elizabeth Fortunato speaks with Victoria Cavazos, a former Naval Surface Warfare officer turned app developer. They discuss the evolution of maritime training, the development of the SeaSmart app, and how AI is transforming the way mariners learn and prepare for exams. Victoria shares her journey from the Navy to creating a mobile training platform that focuses on intuitive learning and adaptive quizzing, making it accessible for both Navy personnel and civilian mariners. The conversation highlights the importance of understanding maritime rules and the role of technology in enhancing safety and education in the maritime industry. In this conversation, Victoria Cavazos discusses the features and functionalities of the maritime app SeaSmart, emphasizing the importance of understanding inland versus international navigation rules, the feedback mechanisms for learning from mistakes, and the innovative board mode that simulates real exam pressure. She highlights the significance of reading the rules verbatim and the historical context behind them, while also introducing interactive learning features like the Helm simulation. The conversation concludes with insights into future developments and the importance of continuous learning in maritime education.

Chapters:

00:00 Navigating the Future of Maritime Training

02:03 Victoria Cavazos: From Navy to App Development

09:21 Revolutionizing Maritime Education with SeaSmart

15:14 The Power of AI in App Development

22:05 Building a Tool for All Mariners

32:04 Sneak Peek: SeaSmart App Demo

34:03 Navigating the App Interface

35:01 Understanding Inland vs. International Rules

36:20 Learning from Mistakes: Feedback Mechanism

38:43 Board Mode: Simulating Real Exam Pressure

41:14 Reading the Rules: Importance of Textual Knowledge

43:26 Bringing History to Life: The Story Behind Rules

46:32 Interactive Learning: The Helm Simulation Feature

51:35 Future Features and Development Plans

52:55 The Buoy Run: Quickfire Questions and Insights

Links:

Substack: https://pca.st/b2e88tfi

YouTube:

https://www.youtube.com/playlist?list=PL479GKt9ybDVLP3pUZEkL2DCqGM9sBvIQ

Spotify:

https://creators.spotify.com/

PocketCast: https://pca.st/b2e88tfi

Autonomous Vessels Edge Toward a 2027 Global Framework as Regulatory Sandboxes Multiply

AI Captains Log — Fri, 07 Aug 2026 14:01:34 GMT

Autonomous Navigation’s Path From Trial to Deployment

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Autonomous and semi-autonomous vessel navigation is moving from conceptual research into commercial deployment, according to a review of current maritime technology trends from MLA College. Several nations, including Norway, Japan, Finland, and Singapore, have established regulatory sandboxes — controlled environments where new rules and technologies can be tested before full-scale legal adoption — that permit unmanned and remotely operated vessel trials outside standard regulatory constraints.

Vessels such as the Yara Birkeland, a Norwegian container ship, and the Mayflower Autonomous Ship have already demonstrated the ability to navigate complex routes with minimal human intervention. The technologies underpinning these trials include object detection, collision avoidance, and situational awareness fusion, which combines data from multiple sensors such as radar, lidar, and cameras into a single, continuously updated picture of a vessel’s surroundings.

Marine Traffic Photo

The regulatory picture is still catching up to the technology. The International Maritime Organization (IMO), the United Nations agency responsible for the safety and environmental performance of international shipping, is developing the Maritime Autonomous Surface Ships (MASS) framework, a set of rules governing how autonomous and remotely operated vessels can operate across international waters. The IMO is targeting international consensus on the framework by 2027, a milestone that would be a prerequisite for autonomous vessels to move beyond national sandboxes and operate at scale across borders. Until then, deployment remains concentrated in the coastal and short-sea trials that sandbox nations currently permit.

Down to the Helm: This week’s AI Integration and Leading Trends in Recreational Boating

NextBoat and MarineMax partnership: MarineMax has adopted the NextBoat artificial intelligence (AI) platform as its preferred wholesale and trade-in partner. The collaboration uses AI to generate vessel valuations, run rapid wholesale bidding, and connect buyers to integrated financing through Newcoast, with the goal of increasing inventory turnover and operational efficiency for dealers.

Brunswick’s ACES strategy: Brunswick Corporation has expanded its showcase of autonomous and connected features under its ACES strategy — Autonomous/Assisted, Connected, Electrified, Shared — including the Simrad AutoCaptain, which assists with docking and situational awareness at the helm.

Market landing: Mobile app sessions for marine marketplaces rose 34.7% year-over-year as of early 2026, as more consumers browse and compare boats through mobile-first tools rather than in showrooms. Future Market Insights projects the global recreational boating market will grow from roughly $48 billion in 2025 to approximately $124.6 billion by 2035, a compound annual growth rate (CAGR) of 10.0%, with technology increasingly cited as a purchase differentiator alongside hull and engine specifications.

AI Captains Log take: Where does assisted stop and autonomous begin?

The same underlying technology thread runs through both stories this week: sensor fusion and real-time hazard detection. On the commercial side, it takes the form of object detection and collision avoidance systems built to meet an eventual international MASS framework, tested in government-sanctioned sandboxes with defined oversight structures. On the recreational side, the nearly identical concept shows up as LOOKOUT and Argo Navigation’s hazard-sensing cameras and Brunswick’s Simrad AutoCaptain. Both are consumer features sold as conveniences, not regulated autonomous systems.

That is where what is happening in the USV and autonomous vessel space is reaching our helms, and it is happening faster than the regulatory frameworks. The IMO’s MASS Code work assumes trained crews, defined human oversight, and shore-based Remote Operations Centres (ROCs). None of that infrastructure exists around a weekend boater relying on an AI-assisted docking feature or a hazard-detection app.

So the harder question remains: as commercial-grade sensor fusion keeps arriving at consumer price points, where should the line be drawn between a tool that assists a captain and one that quietly starts making the decisions for them? Recreational operators generally carry far less training than commercial crews, yet the technology gap between the two is narrowing every week. What is your take?

What is your take? Leave a comment:

Leave a comment

Now onto the rest of the news.

Industry Rundown

Market Outlook

Global maritime AI market: Multiple industry researchers, including Fortune Business Insights and Grand View Research, project the global maritime AI market remains bullish and will exceed $130 billion by 2034, driven by demand for fuel efficiency, predictive maintenance, and safety technology across commercial fleets.

Vessel AI and Operational Intelligence

Predictive maintenance: Machine learning algorithms are increasingly used to monitor engine, auxiliary, and electrical systems aboard vessels, flagging component degradation before it causes failure and reducing unplanned downtime.

Voyage optimization: AI-optimized speed profiles and weather routing are delivering fuel savings of up to 15% for operators that have adopted them.

Multi-agent coordination: Multi-agent AI systems — networks of AI programs that negotiate and coordinate with one another — are being used to manage port traffic, berth allocation, and vessel routing in real time, balancing cost and emissions targets simultaneously.

Smart Ports and Infrastructure

Private 5G networks: Ports are deploying private 5G networks to provide the low-latency, high-speed connectivity that autonomous vehicles and cranes require to operate safely.

Terminal automation: Automated terminal equipment, including robot trucks and remote-controlled cranes, has demonstrated labor cost reductions of 25% to 55% compared with manually operated terminals.

Digital twins: Ports are using digital twin platforms — virtual models of terminal operations — to simulate infrastructure changes before implementing them physically.

Container tracking: Real-time container tracking using Global Positioning System (GPS) and radio-frequency identification (RFID) technology is enabling more precise cargo visibility and predictive berth scheduling.

Regulation and Policy

MASS framework timeline: The IMO is working toward international consensus on its Maritime Autonomous Surface Ships (MASS) regulatory framework by 2027, a step that would be required before autonomous vessels can operate at scale across international waters rather than within national sandboxes.

Decarbonization mandates: IMO decarbonization requirements, particularly around Carbon Intensity Indicator (CII) compliance — a measure of a ship’s carbon emissions relative to the cargo it carries and distance traveled — remain a primary driver pushing operators toward AI-based fleet management and routing tools.

Security and Geopolitical Drivers

Cybersecurity: Increased connectivity between information technology (IT) and operational technology (OT) systems on vessels and at ports has made cybersecurity a critical management priority, with ransomware and network intrusions posing significant financial risk to operators.

[Check out my upcoming series: From Federal IT to Maritime IT – what transfers, and what changes]

Edge computing: Ports are integrating high-performance edge computing, which processes data locally rather than routing it to a distant data center, to improve both security and response speed for automated systems.

Sources

About The AI Captains Log

The channel reaches its audience through four formats:

This newsletter — a consolidated weekly briefing on the latest advancements in maritime AI and technology.
The podcast — conversations with industry professionals, researchers, engineers, and captains shaping the maritime industry.
In-depth articles — deeper explorations of the technologies changing how we operate, navigate, and learn.
Subscriber-only access — the good, bad and ugly of boating.

Subscribe now

Want to contribute to the conversation or appear on the podcast?

Fair winds and following seas,

Elizabeth Fortunato — The AI Captains Log

Smart Port Market on Track for 34% Annual Growth as Maritime AI Matures

AI Captains Log — Fri, 31 Jul 2026 19:02:09 GMT

This Week’s Spotlight: Autonomy Continues to Race Ahead of a Rulebook That Won’t Arrive Until 2032

The clearest signal in this week’s data is a widening split between what autonomous vessels can already do and what the law requires of them. Commercial investment is concentrating on the lower levels of the newly released International Code of Safety for Maritime Autonomous Surface Ships (MASS Code). Level 1 is defined as decision support and Level 2 as partial autonomy. Both Level 1 and Level 2 have seen proven, quantifiable returns while Levels 3 & 4, high-level automation, remains constrained by international law.

That constraint also has a timeline attached. Industry reporting indicates the International Maritime Organization’s (IMO) roadmap toward a mandatory MASS Code is not expected to enter into force until roughly 2032, leaving a multi-year window in which increasingly capable systems operate under a non-binding framework. Traditionally, a phased-in approach allows for testing, validation and adoption of the regulations; however, with the exponential growth of AI capabilities, this adoption period may be too long.

Modern systems fuse radar, LiDAR (Light Detection and Ranging), AIS (Automatic Identification System), and thermal cameras into continuous, around-the-clock situational awareness, then layer in real-time kinematic data and AI-optimized routing. Vessels also can communicate directly with port systems through E-Navigation, the maritime standard for exchanging navigational data digitally. The result of this integration is not (yet) driverless ships, but ships that can be significantly supported through remote operations centers (ROCs).

From Massterly.com

In short: the technology for supervised autonomy is largely here, while the regulation for unsupervised autonomy is six years away. For operators, the practical question is how to use the technologies while the regulations play catch up.

For a detailed discussion on the legal fine lines being drawn, see my podcast: Can an AI Virtual First Mate be Your Legal Lookout.

Down to the Helm: AI Integration and Leading Trends in Recreational Boating

The recreational boating market has been recalibrating after its pandemic-era sales surge, settling into a steadier, more value-focused mindset with AI software, predictive maintenance, and mobile-first navigation as the primary engines of innovation. (Please note, I do not sponsor or endorse any of these tools.)

Smart routing and decision support: LOOKOUT and Argo Navigation have partnered to merge real-time 3D hazard detection with mobile route planning to create “routes that can see,” where AI-verified obstacles such as debris or whales trigger dynamic rerouting directly on the user’s screen. Others are pushing further into interpretation: SeaLegs AI issues plain-language “Go, Caution, or Avoid” recommendations by weighing more than a dozen weather models, automating analysis that once required manual meteorology.

The competitive field: The app landscape is specializing. Sentinel GO anchors the “forever free” end with document storage, pre-departure checklists, and automatic trip logging; Windy.com remains the heavyweight for weather visualization, with 40-plus map layers and multi-model support; and Wavve Boating focuses on mobile-first charts, route planning, and offline access on a 14-day trial basis.

Where AI is hitting our helm: Beyond routing, integration is spreading into predictive maintenance with engine sensor monitors set to forecast failures before they occur and autonomous docking that assists in crowded marinas. However, market sentiment remains skeptical of fully autonomous “self-driving” boats in the near term, but strongly positive toward AI that reduces cognitive load, flags hazards in real time, and streamlines maintenance.

AI Captains Log’s take: From the Bridge to the Helm

The real story this week isn’t commercial or recreational on its own — it’s both. The same core technologies are surfacing in both worlds.

On the commercial side, proven Level 1–2 autonomy runs on sensor fusion (radar, LiDAR, AIS, thermal) feeding AI-optimized routing and collision avoidance. On the recreational side, that same tech stack is arriving on our mobile devices:

LOOKOUT and Argo’s “routes that can see” are commercial hazard detection and voyage optimization scaled for a mobile app;
SeaLegs AI’s “Go, Caution, or Avoid” calls are the ‘decision-support layer’ of a MASS vessel rendered in plain language. While autonomous docking and predictive maintenance are supervised-autonomy features scaled down to the recreational boater’s helm.

That is the technical migration the newsletter exists to track: what gets validated on a container ship can now reach the consumer’s helm within a few seasons. As AI shortens development cycles, the tools will continue to get cheaper, simpler, and more available to recreational boaters.

Which is where the harder question lives: on a commercial bridge, the MASS Code assumes a trained master holds the ultimate responsibility. On the recreational helm, who holds it? The same technology that makes a novice boater safer can also tempt them to trust it past its limits. As these features come down to our helm, the oversight burden doesn’t vanish, it just changes.

So the question for the week is:

As commercial-grade AI arrives on the recreational helm, are we equipping boaters to operate these new technologies in a safe way or are we asking them to ride along as passengers observing it? (2016 flashback: Tesla driver killed while using autopilot was watching Harry Potter.)

What’s your take?

Leave a comment

Now onto the rest of the news.

Industry Rundown

Market Outlook

Maritime AI trajectory: The maritime AI market is projected to expand from $8.78 billion in 2026 to $139.4 billion by 2034, with growth attributed primarily to demand for fuel efficiency and enhanced safety. This is more than a fifteen-fold increase (a.k.a 93% increase) across eight years and is what continues to drive investment into the sector.

Vessel AI and Operational Intelligence

Predictive maintenance: Rather than servicing on a fixed schedule, operators are using machine learning to analyze vibration patterns, engine performance, and thermal data to flag component degradation before failure occurs, reducing unplanned downtime.

Voyage optimization: AI-driven tools are reporting up to 15% fuel savings through optimized speed profiles, weather routing, and automated voyage planning.

Safety and risk: Computer vision paired with sensor fusion — radar, LiDAR, AIS, and thermal cameras — is delivering round-the-clock situational awareness, letting crews adjust speed or course well ahead of collision risk or port-arrival congestion.

Smart Ports and Infrastructure

Digital twins and IoT: Ports are deploying digital twins (virtual models of terminal operations) alongside Internet of Things (IoT) sensors to simulate mooring, crane operations, and resource allocation, enabling proactive decision-making and predictive maintenance of critical infrastructure.

Automated terminals: Automated berth scheduling, robotic cargo handling, and 5G connectivity are being used to minimize crane idle time and cut manual labor requirements.

Blockchain and eBL: To streamline logistics, ports and carriers are applying blockchain to digital Bills of Lading (eBL) and immutable ledgers for cargo manifests, targeting the processing delays that have historically cost the industry billions.

Market growth: The smart port market is forecast to grow at a compound annual growth rate (CAGR) of 34.3% through 2033, as ports pursue digital transformation to address congestion and sustainability pressures.

Sources

About The AI Captains Log

The AI Captains Log charts the transition from traditional seamanship to the age of maritime autonomy, tracking how artificial intelligence (AI) and emerging technology are reshaping navigation, safety, and operations on the water. It gives mariners a clear, credible way to stay ahead of the developments reshaping the industry — the advances that matter, explained without the hype, noise, and advertising.

The channel reaches its audience through four formats:

This newsletter — a consolidated weekly briefing on the latest advancements in maritime AI and technology.
The podcast — conversations with industry professionals, researchers, engineers, and captains shaping the maritime industry.
In-depth articles — deeper explorations of the technologies changing how we operate, navigate, and learn.
Subscriber-only access — the good, bad and ugly of boating.

Subscribe now

Want to contribute to the conversation or appear on the podcast?

Fair winds and following seas,

Elizabeth Fortunato — Host of The AI Captains Log

Kadey Krogen Yachts Declares Bankruptcy

AI Captains Log — Thu, 30 Jul 2026 19:10:13 GMT

Being the biggest debtor in a bankruptcy filing is not a badge of honor; its a nightmare. If you want to follow along with us in the journey, this is the place to do it. Here we will share our story …

Maritime AI Market Set to Reach $139 Billion by 2034 as Automation Scales

AI Captains Log — Fri, 24 Jul 2026 13:30:30 GMT

This Week’s Spotlight: Improved AI Path Planning Brings Ships Closer to Reliable Collision Avoidance

New research describes an Improved Artificial Potential Field (IAPF) method for real-time ship path planning, aimed at helping autonomous and AI-assisted vessels detect and avoid collisions in dynamic traffic. The approach models nearby vessels and obstacles as fields of virtual force, allowing a ship’s navigation system to continuously recalculate a safe course as conditions change, rather than following a fixed route plan.

The method is designed to comply with the International Regulations for Preventing Collisions at Sea (COLREGs), the rules governing right-of-way and maneuvering between vessels, so that AI-generated course corrections stay consistent with the maneuvers a human operator would be expected to make. According to the research, the approach improves on earlier potential-field techniques, which could produce local minima (a situations where a path-planning algorithm finds no safe route forward) by adding constraints that keep a vessel moving toward its destination even in cluttered traffic.

Photo by Chris Linnett on Unsplash

While this is still in the research phase, it is clear that AI-driven navigation is moving from general concept toward the kind of specific, testable algorithm needed for true collision avoidance and smart navigation. The algorithm builds on an increasingly assembled toolkit: sensor fusion across radar and sonar, IAPF for real-time path planning, and predictive maintenance models. Together, these support a graduated approach to autonomy, in which coastal and short-sea vessels are already operating with reduced crews even as fully autonomous deep-sea shipping remains a longer-term goal.

AI Captains Log take: Where Do We Draw the Line?

Although this is still in the research phase, the question of when a human operator should step in—at the first sign of potential risk or only when a collision becomes imminent—touches the core challenge of maritime autonomy.

If humans take the controls at every potential risk, the benefits of autonomous navigation vanish. Marine traffic is full of overlapping potential hazards. Algorithms like the Improved Artificial Potential Field (IAPF) are engineered specifically for that environment to calculate continuous, COLREGs-compliant path adjustments through a busy harbor without human fatigue or distraction.

Rather than choosing strictly between “potential” or “imminent,” could the hand-off line be better drawn between predictability and unpredictability?

Routine Potential Risk (AI Domain): When surrounding vessels obey standard right-of-way rules and marine traffic flows predictably, real-time path planning excels, AI can handle the calculations of collision avoidance (with a properly trained model) far earlier and more smoothly than a human operator might.
Algorithmic Uncertainty (Human Domain): The hand-off should trigger the moment predictability breaks down, such as when another vessel behaves erratically, ignores COLREGs, or severe conditions degrade sensor data.

Waiting until a collision is imminent doesn’t give a human operator enough time to take back control and execute a safe maneuver. And if intervening at the first potential risk defeats the purpose of the technology maybe the sweet spot for human intervention is when the algorithm encounters human-like unpredictability.

What is your take? Leave a comment:

Leave a comment

Now onto the rest of the news.

Industry Rundown

Market Outlook

Fortune Business Insights projects the global maritime AI market will reach $139.4 billion by 2034, growing at a compound annual growth rate (CAGR) of 41.28% from 2026. Hardware — sensors, navigation equipment, and automation gear — is expected to remain the largest category, commanding over 40% of market share, according to the same forecast. North America currently leads maritime digitization adoption, while Asia-Pacific is forecast to grow fastest, driven by port modernization and 5G rollout.

Vessel AI and Operational Intelligence

Fuel and voyage optimization: AI-driven fleet-management systems are delivering up to 15% in fuel savings by generating optimized speed profiles and dynamic weather routing. Industry reports cited this week indicate that data-driven voyage optimization has shortened Atlantic transit times by as much as 2.5 days on some routes.

Predictive maintenance: Rather than servicing equipment on a fixed schedule, machine learning models are analyzing vibration, engine performance, and temperature data to flag component failure before it happens. The same shift toward continuous monitoring extends underwater: autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs) are increasingly performing hull inspections once handled by divers.

Smart Ports and Infrastructure

Connectivity: Private 5G networks are becoming standard infrastructure at modern ports, providing the low-latency connections needed for real-time cargo tracking and coordination between automated equipment.

Automation and digital twins: Deployment of automated guided vehicles (AGVs) and automated stacking cranes (ASCs) has roughly doubled since 2023, letting ports handle higher container volumes with less labor. Ports are also building digital twin platforms (virtual models of terminal operations) to test infrastructure changes and optimize berth scheduling before committing to them physically, which reduces vessel idling time and emissions. Rotterdam and Shanghai were named as leaders in applying AI and IoT sensors to this kind of monitoring.

Photo by Xie Jian on Unsplash

Decarbonization and Propulsion Innovation

Fuel transition: Shipping is moving beyond heavy fuel oil toward hydrogen, ammonia, and liquefied natural gas (LNG), with hydrogen fuel cells being piloted on short-haul routes.

Propulsion design: The American Bureau of Shipping (ABS), a classification society that certifies vessel safety and design, has approved Korean containership designs incorporating molten salt nuclear reactors. Separately, the industry is testing wind-assisted kite traction for floating production, storage, and offloading (FPSO) units, which are offshore platforms that process and store oil and gas, to cut fuel use during transit.

Sources

About The AI Captains Log

The channel reaches its audience through three formats:

This newsletter — a consolidated weekly briefing on the latest advancements in maritime AI and technology.
The podcast — conversations with industry professionals, researchers, engineers, and captains shaping the maritime industry.
In-depth articles — deeper explorations of the technologies changing how we operate, navigate, and learn.

Coming soon: Subscriber-only access to the good, bad and ugly of boating.

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Fair winds and following seas,

Elizabeth Fortunato — The AI Captains Log

Smart Ports Deploy Unified AI Stacks as Autonomous Shipping Market Accelerates

AI Captains Log — Fri, 17 Jul 2026 19:27:42 GMT

About The AI Captains Log

The channel reaches its audience through three formats:

This newsletter — a consolidated weekly briefing on the latest advancements in maritime AI and technology.
The podcast — conversations with industry professionals, researchers, engineers, and captains shaping the maritime industry.

In-depth articles — deeper explorations of the technologies changing how we operate, navigate, and learn.

Subscribe now

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This Week’s Highlight

Integrated AI Stacks Move Smart Port Automation From Pilot to Practice

At TOC Europe 2026, terminal operators demonstrated production deployments that unify three previously separate layers of port automation into a single AI-driven stack, marking a shift from isolated pilots toward integrated systems. Westwell’s smart port automation platform was among the deployments showcased, combining perception, decision-making, and execution in one coordinated system.

The perception layer uses high-resolution optical character recognition (OCR) to identify containers and establish a shared “single source of truth” across the terminal.
A decision-making layer then continuously simulates terminal conditions — yard density, traffic flow — using AI engines that dispatch task sequences in real time.
On the execution side, autonomous electric-powered vehicle fleets, including Q-Trucks, operate without the magnetic pins or fixed lane markings that older automated terminals require.

Image from: https://en.westwell-lab.com/resources/CaseStudies/westwell-port-automation-solutions-at-toc

Terminals that have fully integrated these systems report operating cost reductions of 25–55% and asset utilization gains of 10–35%, according to vendor-reported case studies (these figures have not been independently audited). The approach depends on infrastructure investment: ports are increasingly deploying private 5G networks to support the sub-millisecond latency needed to coordinate autonomous heavy machinery, robotic trucks, drones, and remote crane operations in real time.

The development signals that AI-driven terminal automation is moving past isolated technology trials toward systems built as integrated operating stacks — a shift likely to shape procurement decisions at ports now evaluating automation investment across their operations.

Industry Rundown

Regulation and policy

The IMO’s MASS Code is now in force. The International Maritime Organization (IMO) formally adopted the non-mandatory International Code of Safety for Maritime Autonomous Surface Ships (MASS Code) in May 2026 and it took effect on July 1, 2026. The code sets safety goals and risk-assessment principles rather than prescriptive rules, defining operating conditions such as weather limits and permissible sea states for autonomous vessels. It keeps the master responsible for the ship at all times and is supported by Remote Operations Centers (ROCs), that are shore-based facilities that monitor vessel operations and can intervene when needed (i.e., COLREG Rule 05).

Market outlook

Forecasts point to sustained double-digit growth in maritime AI. Industry analysts project the global maritime artificial intelligence (AI) market will reach $64.7 billion by 2032, growing at a compound annual growth rate (CAGR) of 40.8%, according to a GlobeNewswire-published industry outlook.

The global autonomous ships market is forecast to grow from $9.8 billion in 2026 to $21 billion by 2035. Analysts attribute the growth to pressure on operators to cut fuel costs, raise operational capacity, and offset ongoing labor shortages. The smart port automation segment is separately projected to approach $40 billion by 2034.

Vessel AI and operational intelligence

Voyage planning and maintenance are shifting from static to predictive. AI systems are replacing fixed voyage plans with dynamic routing informed by weather resistance, ocean currents, and real-time engine condition data. Digital twins and sensor-fusion models are increasingly used for predictive maintenance, flagging likely mechanical failures before they occur rather than after. Commercial platforms such as the Veson Platform and MOL’s AI-powered operations center are consolidating weather, geopolitical, and vessel-performance data into single command-level interfaces. Generative AI is also entering ship design: the GenDSOM project pairs generative design with additive manufacturing to optimize vessel performance before construction begins.

Autonomous navigation and robotics

Sensor and propulsion technology is expanding autonomous capability. Advanced radar and sonar systems, including the Argos Forward Looking Navigation Sonar, are improving situational awareness for autonomous vessels operating in challenging conditions. Robosys Automation and propulsion manufacturer Sleipner announced a collaboration to expand multi-original-equipment-manufacturer (multi-OEM) support for remote vessel control. Designated trial areas, including one established in Plymouth Harbour, continue to be used to validate autonomous vessel prototypes under real-world conditions.

Security and geopolitical drivers

Geopolitical tension is accelerating demand for maritime surveillance AI. Elevated risk in critical shipping chokepoints such as the Strait of Hormuz is driving demand for AI-based threat detection and vessel movement-pattern recognition. Increased security risk is also pushing operators toward remote fleet-intelligence platforms that allow assets to be monitored from shore, combined with unmanned systems for response and surveillance — now treated as a core requirement for maintaining trade continuity in contested waters.

Sources

Thanks for reading this far! Want to contribute to the conversation or appear on the AI Captains Log podcast?

Fair winds and following seas,

Elizabeth Fortunato, The AI Captain

The Used Boat Pitfall: Is Your MMSI Number Sending the Wrong Signal?

AI Captains Log — Thu, 09 Jul 2026 17:15:50 GMT

At the dock, a boat can look ready for anything. The lines are tidy, the gear is aboard, and the new owner is already imagining the first passage. But beneath the surface of any used-vessel purchase, there is often one small detail that deserves real attention—and ignoring it can have dangerous consequences.

Take the vessel’s Maritime Mobile Service Identity (MMSI) number. Some boat sellers treat this unique nine-digit maritime identity like a personal cell phone number, packing it up and programming it into their next vessel’s system. In reality, an MMSI belongs strictly to the boat’s VHF radio, not the captain. When an old number is stripped away or improperly transferred, it creates a critical safety blind spot, leaving emergency responders hunting for the wrong vessel or contact information when every second counts. Navigating the paperwork of a used-boat purchase means ensuring the MMSI stays exactly where it belongs: with the vessel’s VHF radio.

The good news is that once it is programmed into a DSC-capable VHF radio, it becomes part of the vessel’s digital identity and should not require changing – unless the previous owner reused it or it cannot be transferred. What does require changing is who is assigned to the MMSI.

Digital Selective Calling (DSC) capable marine radio is a VHF radio equipped with an emergency distress button and selective calling capabilities.

In a distress situation, that number helps identify the boat, and when the radio is connected to your chart plotter, it can also help transmit position information. That is what gives the MMSI its real value: it helps search and rescue respond with a clearer picture of who is calling and where the vessel is located.

That matters whether you are coastal cruising, preparing for an offshore passage, or operating a charter vessel that depends on reliable communications. When the number is wrong, outdated, or still attached to the previous owner, the system loses clarity right when clarity matters most.

What an MMSI actually does

MMSI stands for Maritime Mobile Service Identity. It is a nine-digit number used by marine radios and other safety systems to identify a vessel.

Think of it as the communications nameplate for the boat. It helps digital distress calls and safety transmissions connect to the right vessel and the right registration information. It is one of those small systems that quietly supports a much larger safety net.

For offshore boaters in particular, that value is easy to understand. When you are away from the dock and outside easy reach, you want every system aboard to be speaking with the same voice.

Buying a used vessel

If you are buying a used boat, one of the first questions to ask is whether the MMSI is still assigned to the previous owner.

That number may be tied to the vessel’s radio identity, but it must also reflect the current ownership information. Before you rely on it as your own, confirm that the seller has released it or that the transfer process has been handled correctly. If that step is skipped, the radio may still carry information that belongs to someone else.

This is one of those small tasks that can save you from a large mess later. It is far easier to handle the transfer at closing than to discover, months later, that the vessel’s communications identity was never updated.

A practical note: when it is time to reprogram or reset the radio, consult the owner’s manual for your specific unit. Different manufacturers handle MMSI programming in different ways, and the manual should always be the first reference.

How the U.S. process works

For a U.S.-registered vessel, the MMSI is managed through U.S. authorities and approved registration paths.

If you are purchasing the boat, confirm whether the previous owner has released the MMSI and then complete the steps needed to register it properly in your name. The radio information should match the actual vessel that is now underway. That alignment is what keeps the system useful.

The key idea is simple: the number should follow the vessel. The registration should reflect the current owner.

Steps

Confirm whether the vessel already has an MMSI. Before anything else, determine whether the boat already has an MMSI assigned in the VHF radio. Reference your VHF manual to find it in your menu settings. Copy this number and search it on marinetraffic.com. This will quickly tell you which vessel name this number is assigned to.
Ask the seller which authority issued it. This is an important step because the issuing authority tells you what rules govern the number and how the transfer should be handled. If the MMSI was issued in the United States, it may have come from one of the main recreational registration providers: BoatUS, United States Power Squadrons, Inc., or Shine Micro. In some cases, the MMSI may have been tied to an FCC ship station license instead, particularly for vessels that travel internationally or need formal licensing. Knowing the source helps you figure out whether the number should be transferred, released, or reissued.
Make sure the seller releases or transfers it properly. The MMSI should not simply be assumed to “move” with the boat. The seller needs to take the proper steps to release the number or transfer the registration so the record reflects the new ownership. If that does not happen, the vessel may still show the previous owner’s contact details or radio identity, which can create problems in an emergency. This is one of the quiet details that is easy to overlook but worth handling carefully before the sale is complete.
Register it in the new owner’s name if required. Once the vessel changes hands, the MMSI record should reflect the new owner whenever registration is required by the issuing authority. This is what keeps the radio identity tied to the right person and the right boat. If the vessel was previously registered under another owner, the new owner may need to complete a fresh registration or update an existing one, depending on where the MMSI came from. The important thing is that the emergency and vessel information linked to the number is current and accurate.
Reprogram the radio using the owner’s manual (hopefully this will not be required because it is not easy). After the paperwork is sorted out, the radio itself may still need to be updated. Use the owner’s manual for the specific radio model, because MMSI programming steps vary by manufacturer and some radios limit how often the number can be changed. This is especially important for DSC-capable VHF radios, where the MMSI is part of the digital distress identity stored in the unit. If the radio was previously programmed for another vessel, it should be reset or re-entered only according to the manufacturer’s instructions.
Verify the MMSI matches the vessel and owner. Once everything is set up, confirm that the number on the radio, the registration record, and the boat itself all point to the same vessel and owner. This is the final check that keeps the communications system consistent. It is easy to assume the number is “good to go,” but a mismatch between the boat, the owner, and the radio can defeat the point of having the MMSI at all. A few minutes of verification here can make the difference between a clean system and one that fails quietly in the background.

For recreational owners, this is usually a manageable task. For offshore or charter use, confirm any additional licensing requirements. Boats that travel offshore or operate in charter service often need a little more attention than a purely local recreational vessel. In those cases, the MMSI may be only one part of a larger communications and compliance picture that can include radio licensing, AIS setup, ship station requirements, and other documentation. It is smart to confirm those requirements before the vessel goes into service, not after. That way, the radio identity, legal paperwork, and actual use of the boat are all aligned from the start.

How the non-U.S. process differs

The process changes when the vessel is registered outside the United States (Step 7 depicted above).

For a non-U.S.-registered vessel, the MMSI is generally issued by the vessel’s flag state or home-country authority rather than through the U.S. FCC system. That means the transfer or reissue process may look similar in principle, but it is governed by a different authority.

This is where many boaters can get turned around. The radio may be the same, the number may still be nine digits, but the registry behind it is what matters. If the vessel is foreign-flagged, follow the rules of the country that governs that vessel.

Rescue 21, explained

There is one more piece worth understanding if you plan to properly test your radio.

Rescue 21 is the U.S. Coast Guard’s modern coastal VHF distress communications network. It monitors DSC distress alerts, helps identify the caller, and uses direction-finding tools and recorded communications to narrow down where a distress call is coming from. In plain English, it is the Coast Guard’s system for hearing distress calls more clearly and responding faster.

That is why the test call to the Coast Guard’s MMSI number only works in areas served by Rescue 21. The system has to be there to receive and acknowledge the call.

How to safely test your MMSI number

Do not press the red distress button on your VHF radio as a test. Doing so can trigger a false distress alert and may lead to an unnecessary rescue response.

Instead, use the Coast Guard’s designated MMSI test number: 003669999. Enter it into your radio’s calling memory, then select the Test Call option from the radio’s DSC call menu. Press the call or enter key, and the radio should send a silent digital test call on Channel 70.

If your equipment and the Rescue 21 system are working properly, you should receive an acknowledgement from the Coast Guard almost immediately. This gives you a safe way to confirm that both your radio and the system are functioning as expected.

One important note: this test is only available in areas served by Rescue 21.

Tracking and voyage sharing

There is also a useful and fun side to all of this.

Having the MMSI can also allow a vessel to be tracked worldwide on services such as MarineTraffic.com, which some boaters use as a simple way to share voyage information with friends, family, or a float plan holder on shore. For offshore passages, that can offer another layer of visibility for people who want to follow your progress while you are underway.

It is not just a convenience. For many crews, it is a reassuring bridge between the boat and the people keeping watch from land.

The real takeaway

If you are buying a used vessel, do not treat the MMSI as a technical footnote. Treat it as part of the handoff.

Confirm who currently controls it. Make sure it is transferred or reissued correctly. Update the radio so it matches the boat you actually own. And when in doubt, use the owner’s manual as your guide for the radio itself.

The number is small, but the role it plays is not. A correctly assigned MMSI helps keep your vessel aligned to the systems that matter most: safety, communication, and accountability. In boating, that is the kind of detail worth getting right.

Helpful links

Can an AI Virtual First Mate be your legal lookout?

AI Captains Log — Wed, 01 Jul 2026 23:00:44 GMT

In today's rapidly evolving maritime industry, the integration of technology and traditional seamanship raises critical legal questions. As we transition from conventional methods to maritime autonomy, understanding the implications of regulations, particularly the COLREGs (International Regulations for Preventing Collisions at Sea), becomes essential. In this episode, we explore key insights shared by Greg Singer, a senior maritime litigation attorney, on the intersection of technology, law, and seamanship.

Key Takeaways:

Understand Your Responsibilities - Ensure your vessel complies with the COLREGs, even when using advanced technologies.
Utilize Technology Wisely - Incorporate AI and other technological advancements as supplementary tools, not substitutes for human oversight.
Stay Informed on Regulations - As maritime laws evolve, keep abreast of changes that may affect your operations, especially regarding autonomous vessels.

Chapters:

00:00 Introduction to Maritime Autonomy

01:38 Greg Singer’s Maritime Journey

03:39 Rule Five: The Lookout Requirement

08:27 AI and Autonomous Vessels

11:59 Understanding the IMO and Its Role

14:30 Mobile Technology in Navigation

23:02 Command Responsibility and Rule Two

29:28 Trusting AI in Maritime Navigation

31:51 Data Overload and Liability in Shipping

35:31 Responsibility and Software Liability

38:14 Advancements in Boating Technology

41:28 The Future of AIS and AI Integration

46:00 Legal Implications of Autonomous Systems

51:46 The Boating Boom and Community Impact

Key Links:

Substack: https://pca.st/b2e88tfi

YouTube:

https://www.youtube.com/playlist?list=PL479GKt9ybDVLP3pUZEkL2DCqGM9sBvIQ

Spotify: https://creators.spotify.com/

PocketCast: https://pca.st/b2e88tfi

Lochner Law Firm: https://boatinglaw.com

IMO: https://www.imo.org/en/mediacentre/pressbriefings/pages/imo-adopts-mass-code.aspx

When Your Route Starts Learning: How Digital Twins Are Changing Voyage Planning

AI Captains Log — Fri, 19 Jun 2026 16:28:31 GMT

You may know that moment offshore when the forecast and the sea state quietly part ways. The plotter still shows your pre‑planned route arcing confidently across the chart, but the wind has backed a little more than expected, the swell is steeper on the bow, and the boat just feels different than the line you drew in the comfort of port.

For decades, commercial captains have lived in that tension: the route on paper, and the reality under the keel. Traditional voyage plans are carefully built, but they’re still fundamentally static—based on generic ship tables, coarse‑grid forecasts, and a lot of human judgment layered on top.

Now a new layer is coming into focus: AI‑driven routing systems built on digital twins of individual vessels. These twins don’t just know “a Panamax bulker” or “a 60‑meter yacht”—they learn your hull, your engines, your fouling, and how your ship actually behaves in real seas.

In this article, we’ll do three things:

Walk through (conceptually) how most route planning still works today, without digital twins
Explore what a vessel digital twin really is and how it’s built
Compare a “normal” route to one guided by AI on top of a digital twin—and what that shift means for the contract of trust between the numbers on your screen and the water under your keel

How voyage planning works without a digital twin

If you strip away the acronyms and software, voyage planning in deep‑sea shipping still follows a familiar four‑stage pattern: appraisal, planning, execution, and monitoring1.

Step 1: Appraisal: assembling the big picture

Before a long passage, the bridge team gathers – or you as the captain of a delivery or private yacht:

Charts and ENC coverage
Sailing Directions and routing guides (like Ocean Passages for the World)
Tide and current atlases
Notice to Mariners updates and nav warnings
Seasonal weather and wave climatology
Any company routing instructions or charter‑party constraints

The goal is to understand the ocean “chessboard” for this passage: likely storm tracks, ice or piracy risk areas, traffic schemes, drafts and air‑draft constraints, and port limitations.

Step 2: Planning: drawing the line

Next comes the actual route:

A primary route—often great‑circle or composite—connecting departure and arrival, adjusted around known hazards and separation schemes.
One or more alternative routes to account for seasonal weather or security concerns.
A notional speed profile based on timetable and generic speed–power curves from trials or manuals.

Some operators and captains subscribe to traditional weather‑routing services: ashore, a routing team uses global forecasts and simplified ship performance models to recommend a track and speed schedule that avoids the worst weather while keeping time and fuel in mind.

Step 3&4: Execution and monitoring–holding the plan and trimming around it

Once the plan is approved, it’s transferred to Electronic Chart Display and Information System (ECDIS) and/or paper charts. During the voyage, the bridge team:

Monitors conditions vs. forecast
Adjusts course and speed around heavy weather, traffic, or unexpected constraints
Sends noon reports and performance data back to shore
May get updated advice from a routing service when major systems move in

It’s a professional, structured process—but the intelligence sits mostly in people, not in the tools. The assumptions under the route are often:

Generic ship behavior: standard speed‑power tables and sea margin assumptions, not tuned to the specific hull’s fouling, loading, or age.
Coarse weather: global models at relatively low resolution, interpreted manually by crews or forecasters.
Static trade‑offs: a route chosen up front for “fastest” or “safest,” then only occasionally revisited when circumstances force the issue.

It works—but it leaves a lot of performance, comfort, and predictability on the table.

The limits of ship‑agnostic routing

From the helm, you feel those limits as:

Fuel and emissions creep. A few percent extra fuel on each leg doesn’t show up like a grounding, but across a fleet it’s the difference between meeting carbon intensity indicator (CII) targets or not.
Weather surprises. Forecasts evolve. Ensemble models may radically adjust storm tracks a few days out, but your original plan was built on a single snapshot.
Vessel individuality. Two sister ships on the same line behave differently: one with a clean hull and tuned autopilot, the other with rougher bottom and different loading patterns. Traditional routing tends to treat them as identical.

In other words, most current routing is still ship‑agnostic and episodic. The plan may be updated, but it’s not constantly asking: “Given who this ship is today and what the ocean looks like today, is there a better route and speed profile?”

That question is exactly where digital twins come in.

What a vessel digital twin really is

“Digital twin” gets thrown around a lot, but in the maritime performance world it has a fairly concrete meaning.

At its core, a digital twin is a living, data‑driven model of a specific vessel’s behavior, continuously updated with real‑world measurements. It typically combines:

The Digital Twin Stack

1. Design‑time physics

From the shipyard and naval architects you get:

Hull resistance and propulsion curves
Propeller characteristics and engine mappings
Seakeeping predictions: motions and accelerations in different sea states and headings
Stability and loading envelopes

These models are derived from computational fluid dynamic (CFD)2, tank tests, and design calculations, and they set the initial “personality” of the twin.

2. Environmental response

Next, the twin encodes how this hull responds to:

Different wave heights, periods, and directions
Winds from various angles and strengths
Currents and swell interacting with the ship’s course and speed

NOAA‑linked work on real‑time digital twins emphasizes predicting motions and loads in actual waves so crews can anticipate comfort and structural risk along candidate routes. For DP vessels and offshore units, research shows twins can be trained to forecast thruster loads and six‑degree‑of‑freedom motions under complex metocean3 forcing.

3. Operational “truth data”

Finally—and most importantly—the twin is tied to the ship’s real life:

Noon reports and daily performance logs
Engine, shaft, and fuel‑flow telemetry
Speed over ground, draft, trim, and sometimes motion sensors
Recorded voyages under varied loading and fouling conditions

NAPA describes this explicitly: they merge “big data” from voyage histories with design‑time models and port data to create a ship performance model that forms the vessel’s digital twin, continuously refined as more data comes in. Spire’s voyage‑optimization services, which can incorporate high‑fidelity digital‑twin technology from partners such as Syroco, follow a similar loop—using operational data to keep the virtual ship aligned with how the real hull is actually performing at sea. In pilot projects, Syroco has reported double‑digit improvements in energy efficiency by combining continuously calibrated digital twins with weather‑optimized routing, without extending voyage time.

When that loop is healthy—design physics plus measured behavior feeding back into the model—you end up with something powerful: a twin that knows how this hull, in this condition, actually moves and burns fuel in today’s seas. That’s the safe‑passage baseline for AI routing: a trustworthy link between the numbers on the screen and the real hydrodynamics under your keel.

How Operators Measure Success

The real work in making sure a digit twin is effective is all in the data: data cleaning, anomaly detection, and quality control. It is exactly this “messy middle” layer that underpins AI routing but rarely gets talked about in press releases. So, lets take a slight detour into the “messy middle” for a moment.

Life of a Data Point: From Ocean to Optimization

In traditional voyage planning, the data flow is simple and human‑centric: you gather charts, routing guides, and a few weather apps, plan a route, and then adjust manually based on what experience while underway. Once you step into the world of digital twins and AI routing, the data flow becomes much richer—and much easier to get wrong—because thousands of data points are now offering micro‑adjustments for you (of course, you will have the option to approve them – ‘human in the loop’ is required).

This is where the life of a data point matters. Every single piece of information—one wave‑height estimate, one shaft‑power reading, one current vector—passes through a pipeline before it ever influences the route. Understanding that pipeline is the key to trusting the line that shows up on the screen.

Life of a Data Point: From Ocean to Optimization

You can think of the journey like this:

1. Ocean and ship: the raw reality

Everything starts with the real world: waves hitting the hull, wind wrapping around the superstructure, engines turning, and the vessel responding in speed and motion. That physical interaction is what we ultimately care about—comfort, safety, fuel, and arrival time all live here.

2. Sensors and logs: reality becomes numbers

Sensors and systems try to capture that reality as data:

Position and speed from GPS and AIS (Automatic Identification System)
Wind from anemometers
Engine load, RPM (revolutions per minute), and fuel‑flow meters
Draft, trim, and sometimes motion sensors
Noon reports and manual entries

This is the first translation—from water and steel into numbers. It’s also where errors, gaps, and mis‑calibrations start creeping in (listen to my podcast episode with Tocaro Blue to learn more about how radar data is translated).

3. Data ingestion: assembling the puzzle

In a modern system, those numbers don’t live in one place. They arrive from:

Onboard systems and logs
Shoreside performance databases
External feeds like satellite‑driven metocean (meteorological and oceanographic) datasets for winds, waves, and currents

A data pipeline pulls all of this into a common environment. At this stage, it’s like dumping every logbook, weather fax, and instrument printout into one big box—useful, but not yet safe to base decisions on.

4. Data quality and cleansing: the “messy middle”

This is the critical middle step between traditional route planning and a trustworthy digital twin.

In data‑science terms, this is where you profile, clean, and standardize the data so the models are learning from reality instead of from noise. Specifically, teams:

Fix or flag missing values (e.g., a blank fuel‑flow reading).
Remove duplicates and obviously impossible readings (a vessel “jumping” 200 nautical miles in 5 minutes).
Align timestamps and time zones so wind, wave, and ship response data are actually talking about the same moment.
Standardize units and formats (knots vs. meters per second, metric vs. imperial).
Check for systematic bias—for example, a sensor that consistently reads low in certain conditions.

Why this matters: AI and digital twins are pattern‑matching engines – similar to how LLM models work. If you feed them inconsistent, misaligned, or biased data, they will faithfully learn—and then amplify—those errors. That’s how you end up with “smart” routing that underestimates fuel burn, misjudges motions, or optimizes for the wrong conditions altogether.

From a mariner’s perspective, this cleansing step is the data equivalent of keeping your logbook neat and your instruments calibrated. It’s unglamorous, but it’s the difference between a trustworthy record and one you side‑eye every time you make a decision.

5. Digital twin update: teaching the model who your ship really is

Once the data has been cleaned and aligned, it flows into the vessel’s digital twin. This is where the model learns:

How this hull actually slows down in head seas vs. quartering seas
How fuel consumption changes with small RPM changes under different loads
How fouling and maintenance are affecting performance over time

Over many voyages, the twin stops being a design‑office guess and becomes a live, evidence‑backed portrait of your ship’s behavior. Without that clean data feeding in, the twin never matures—it stays stuck in “trial condition” fantasy land.

6. Route optimization engine: turning behavior into better routes

Only after all of this does the routing engine start doing its work: simulating millions of possible route and speed combinations against live metocean fields, using the twin to predict time, fuel, motions, and Carbon Intensity Indicator (CII) performance for each option.

This is the point where traditional and AI‑assisted routing diverge most clearly:

Traditional routing jumps almost directly from “forecast and generic tables” to “chosen route.”
AI routing inserts a rigorous middle layer: data pipeline → digital twin → optimization, so the route is grounded in how your ship actually behaves in the ocean it is actually sailing through.

7. Bridge and shore: human judgment on top

Finally, that optimized guidance shows up where you live: on the helm and in the operations center. Masters, captains and operators see recommended tracks and RPM plans, plus clear trade‑offs between time, fuel, comfort, and compliance—and can accept, modify, or reject them based on seamanship, traffic, and real‑world constraints. Similar to how a human harbor pilot operates today. They make recommendations to the Captain who can choose to follow or not follow.

How AI routing uses the digital twin

Once the digital twin is in place and the data has been cleansed, route optimization stops being a one‑time line‑drawing exercise and becomes an ongoing computation.

Most modern systems follow a similar pattern:

Step 1: Decide what “best” means

Operators set the objective:

Minimum time
Minimum fuel or CO₂
Best time‑charter equivalent (TCE)
Compliance with Carbon Intensity Indicator (CII4) or other environmental metrics

They also encode constraints: arrival window, maximum motion limits, no‑go zones (ice, piracy, protected areas), speed limits, and emission control area rules.

What Are We Optimizing For?

Step 2: Pull in high‑resolution ocean intelligence

Instead of coarse global models, these platforms ingest dense, frequently updated metocean fields:

Wind
Swell and wind waves
Surface currents
Sometimes mixed‑layer properties and other ocean parameters

Sofar Ocean’s Wayfinder, for example, builds on a global network of free‑floating buoys and satellite data to produce what it calls “the most accurate marine weather,” updated in near‑real time while Spire’s solutions leverage space‑based observations to feed high‑resolution weather and current fields into their routing engines.

Step 3: Let the twin “sail” millions of candidate routes

Here’s where the magic and the math happens (and you know I love math!). For each candidate route and speed profile, the optimizer asks the twin:

If we steer this track, at this RPM, in this evolving weather, what speed over ground will we actually make?
How much fuel will we burn?
What will motions and loads look like along the way?

Because the twin encodes vessel‑specific behavior, those answers are tailored to the actual ship—not to some generic curve. Whichever system you have, NAPA, Sofar (Wayfinder), or Spire, will routinely evaluate millions of route/speed combinations to find the ones that best satisfy the chosen objective under realistic forecasts.

Step 4: Deliver a route and RPM plan

Instead of a single static route, the captain and shore teams (if using one) receive:

One or more recommended routes
RPM or power profiles by leg, often with daily guidance (e.g., “Today: 68 RPM; tomorrow: 62 RPM as you enter a favorable current”)
Predicted arrival time, fuel consumption, and emissions for each option

Wayfinder advertises 4–9% verified fuel savings per voyage by providing this vessel‑specific RPM and routing guidance, while maintaining schedule. Spire cites similar multi‑objective optimizations that lower energy use without lengthening the trip. This seems like a huge benefit if you are a mega-yacht captain trying to optimize your owners’ fuel costs.

Step 5: Keep updating as reality unfolds

Crucially, this isn’t a one‑and‑done computation. As the voyage progresses:

The forecast evolves
The ship’s actual performance deviates slightly from predictions
Operational constraints change (port congestion, schedule tweaks)

The digital twin ingests new data, and the optimizer recomputes.

It’s like having a routing team and performance engineer running in the background every day of the voyage, tuned to your vessel.

This is where the “contract of trust” comes in. If the twin is well‑maintained—fed by clean, quality‑checked data—the guidance it offers is not a black box; it’s a transparent negotiation between your ship and the sea.

Side‑by‑side: life of a route with and without a digital twin

To make this concrete, let’s zoom out and compare two Atlantic crossings.

Traditional Route vs. Digital‑Twin‑Driven Route

Scenario A: Traditional routing

You plan a great‑circle route with a diversion around a forecast mid‑ocean low.
The weather‑routing service recommends a couple of minor adjustments and a speed schedule based on generic performance tables.
On passage, the low deepens and shifts. You alter course based on updated advice, maybe give up a bit of fuel to maintain schedule, and ride out some rougher‐than‑expected seas.
Fuel ends up a few percent higher than planned; arrival is roughly on time; comfort was acceptable but not great.

Scenario B: Digital‑twin‑driven AI routing

Before sailing, your routing platform loads the latest metocean fields and spins up your vessel’s digital twin.
It explores millions of route and RPM combinations, looking not just at avoiding the core of the low but at how your hull will ride the resulting wave fields on each option.
It proposes a track that skirts the worst motions while catching favorable currents on later legs, with a tailored RPM plan to hit your ETA and minimize fuel.
Each day, as the forecast shifts and your actual performance is logged, the twin updates and the guidance adjusts: “Today, reduce RPM slightly—currents are stronger than expected; tomorrow, you can regain time in smoother seas without extra fuel.”

As the Captain, you still have veto power. Human judgment and COLREGs never leave the bridge. But the underlying analysis is no longer constrained by generic curves and static assumptions.

From your helm’s perspective, the difference is subtle but profound:

The line on the chart is no longer a guess; it’s a continuously negotiated truce between physics, weather, and your commercial reality.

Why this matters at the tactical helm

Even if you’re not running a 300‑meter bulker, this shift is worth paying attention to.

At the tactical helm level, here’s what vessel‑specific routing unlocks over time:

More predictable fuel and arrival windows. When route and speed guidance reflect how your boat actually performs in chop, you can plan fuel and schedules with more confidence—whether you’re crossing an ocean or optimizing your charter fleet operations.
Higher “comfort per mile.” Digital‑twin‑aware routing can prioritize not just survival, but minimizing long exposures to headings and periods that induce the worst motions for your hull.
Better use of your attention. Integrated tools like LR OneOcean’s route optimization modules bring weather, hazards, and constraints into a single picture, reducing manual plotting work so you can focus on lookout and decision‑making.

Zooming out to the safety objective for every crossing and extended voyage, this is exactly the future of passage making that should make us optimistic: massive satellite‑driven metocean datasets and high‑end vessel models distilled into route options and RPM numbers that can be managed by a Captain at the helm.

And for the contract of trust? That’s really what digital twins are about. They’re a promise—backed by physics, data, and continuous validation—that when your screen tells you, “If you steer this way at this speed, you’ll arrive at this time burning this much fuel in this sea state,” it’s not pretending to know every uncertainty, but it is telling the truth it has earned based on your vessel’s data.

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This is a very simplified version of what a professional shipping captain does for voyage planning. The intension is to describe it at the 10,000’ level and paint the picture of ‘what is possible’ when using a digital twin. I am not a professional shipping captain and make no claims that this is 100% accurate based on the actual day-to-day requirements of the job. If you are a professional shipping captain and have read this far, please reach out to me! I would love to have your input.

CFD (Computational Fluid Dynamics) is a branch of fluid mechanics that uses numerical methods and computer simulations to solve the equations governing fluid flow and predict how liquids and gases move around objects.

In naval architecture and ship design, it is used to:

Model how water flows around a specific hull form and appendages.
Predict resistance, wave patterns, sinkage, trim, and seakeeping behavior in different sea states.
Optimize hull shapes and configurations digitally before building or tank‑testing, improving performance and reducing fuel consumption.

Metocean data (meteorological + oceanographic data) is the combined picture of weather and sea state: wind, waves, currents, tides, water temperature, etc.

For routing and digital twins, the key metocean variables are things like:

Wind speed and direction
Wave height, period, and direction
Surface currents
Sometimes sea level, temperature, salinity, and more

CII (Carbon Intensity Indicator) – The International Maritime Organization’s operational efficiency metric that measures a ship’s annual carbon intensity (CO₂ emissions per unit of transport work) and assigns an A–E rating based on how it performs against required benchmarks.

AI-Enhanced Marine Radar

AI Captains Log — Thu, 04 Jun 2026 21:26:58 GMT

A Deep Dive into Tocaro Blue’s Sensor Fusion Tech

The Death of Marine Radar Blips: How AI is Changing Navigation Forever

AI Captains Log — Mon, 25 May 2026 20:27:43 GMT

The Digital Horizon: How AI is Transforming Marine Radar

For over a century, marine radar has relied on a simple premise: send out a pulse, catch the echo, and look at a blinking blip on a screen. But in the Age of Autonomy, a blind blip isn’t enough. We need genuine understanding.

In this episode of The AI Captains Log, we chart the incredible evolution of marine radar technology. From its crude beginnings in 1904 to the world-changing cavity magnetrons of World War II, we look at how mariners have historically fought the brutal battle against wave clutter.

Then, we fast-forward to the current revolution happening right now on the bridge. We are diving deep into how modern Solid State Radar, Doppler shift tracking, and Artificial Intelligence are moving us away from anonymous screen data and into a world of automated target classification.

What You’ll Learn in This Episode:

The Physics of the Echo: How the pulse principle changed navigation history.
The War on Clutter: How digital signal processing (DSP) took the “art” out of adjusting your sea gain.
The Doppler Shift: How modern displays color-code targets based on relative motion.
AI & Sensor Fusion: The groundbreaking shift where radar, AIS, and optical PTZ cameras fuse into a single, intelligent display.
The Tocaro Blue Sneak Peek: A look at how the Apollo Core system is turning marine radars into intelligent classification systems for next-generation intelligent autopilots.

If you want to understand how the “Connected Craft” is reshaping commercial shipping and recreational boating, hit that Subscribe button and step onto the digital horizon with us.

TIMESTAMPS

0:00 – The Evolution of the Marine Radar
1:45 – 1904 to WWII: Unlocking Ranging & The Cavity Magnetron
4:15 – The Battle Against Sea Clutter
6:30 – The Solid-State Revolution (Simrad, Garmin, Raymarine, Furuno)
8:45 – Enter Christopher Doppler: Color-Coded Motion Profiles
11:15 – The AI Future: Machine Learning & Object Classification
13:30 – Sensor Fusion & The Tocaro Blue Apollo Core Preview

CONNECT WITH THE AI CAPTAIN

🌐 Website: https://substack.com/@aiboatcaptain

#MarineRadar #ArtificialIntelligence #AutonomousBoating #MaritimeTech #BoatingSafety #TocaroBlue #BoatLife #ShipNavigation #AICaptainsLog

Resources

Tocaro Blue - Proteus Core - https://www.tocaroblue.com/products#proteuscore
History of Radar - IEEE Spectrum - https://spectrum.ieee.org/magnetron
FMCW Radar - Keysight Technologies - https://www.keysight.com/us/en/assets/7018-06911/technical-overviews/5992-4216.pdf
Sensor Fusion in Maritime Systems - https://ieeexplore.ieee.org/document/8569890

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Navigating the Future of Maritime Technology: Manned vs. Unmanned Surface Vessels

AI Captains Log — Sat, 16 May 2026 14:02:44 GMT

In this episode, maritime expert Jack Dougherty shares insights on autonomous vessels, remote operations, and the future of maritime technology. Discover how AI, sensors, and policy shape the next generation of maritime security and boating safety.

Key Topics

Levels of vessel autonomy and human in the loop
Challenges of testing autonomous vessels in real-world conditions
Sensor failures and integration issues in maritime tech
Regulatory and liability concerns in unmanned operations
AI learning and decision-making in autonomous vessels

Chapters

00:00 Introduction to Manned and Unmanned Vessels

02:41 Understanding Unmanned vs. Autonomous Vessels

04:01 Challenges in Testing Maritime Systems

07:16 The Role of Testing in Maritime Operations

08:04 Common Failures in Maritime Technology

09:22 Hardware vs. Software Challenges

10:39 Bridging the Gap: Mission and Technology

11:13 Autonomous Operations: Current Limitations

13:41 Advancements in Autonomous Technology

15:50 Comparing Maritime and Automotive Autonomy

19:51 The Future of Maritime Technology and Security

20:38 Partnerships in Energy Security

24:26 Innovative Maritime Defense Solutions

28:17 The Human Element in Maritime Operations

33:46 Training the Next Generation of Mariners

39:44 Navigating Policy and Liability in Maritime Operations

42:51 Future Skills for the Maritime Industry

As the maritime industry continues to embrace technological advancements, the balance between human expertise and automated systems will be essential for navigating the complexities of the sea.

Want to learn more about the advancements in maritime technology? Check out my Substack page and Podcast to and stay informed on the latest trends.

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Maneuvering Your Boat in Tight Spaces: Bonus Content

AI Captains Log — Wed, 06 May 2026 12:53:50 GMT

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When it comes to boating, one of the most daunting tasks can be maneuvering your vessel in tight spaces, especially in smaller marinas. In this short episode, I’ll walk you through a real-life experience of moving our boat into a narrow slip and share valuable insights on how to handle your boat with precision and confidence.

Understanding the Challenge of Tight Spaces

Maneuvering your boat in a small marina can present unique challenges. With narrow fairways, limited space on either side of the boat, and potentially obstructive neighboring vessels, it requires careful planning and execution. I recently faced this challenge when we moved our boat into a new marina, only to realize we had entered the wrong slip, which was extremely narrow with only a few inches of clearance on either side. Here’s how we managed to navigate this tricky situation.

Step 1: Assess Your Surroundings

Why this matters: Before attempting any maneuvers, it’s crucial to understand your surroundings. Identify the layout of the marina, including the width of the slips, the presence of other boats, and any potential obstacles.
How to do it: Take a moment to observe the area and plan your approach. Look for pivot points, such as nearby pylons or other boats, that can aid in your maneuvering process.
Common mistake: Many boaters rush this step, leading to miscalculations when entering the slip.

Step 2: Use a Spring Line

Why this matters: A spring line is essential for controlling your boat’s movement when space is tight. It allows you to pivot your boat effectively.
How to do it: We used a long spring line of about 75 feet. As we began to back up, I instructed my husband to pull on the line to help steer the boat. This technique allowed us to use the pylons as pivots while maintaining control of our direction.
Example from my experience: As we were backing up, I focused on the starboard engine, gently bumping it to drift backward while my husband managed the spring line to turn the boat toward the correct slip.

Step 3: Communicate Clearly

Why this matters: Coordination is key when maneuvering in tight quarters. Clear communication ensures that both you and your crew are on the same page.
How to do it: Use headsets or hand signals to communicate effectively. Let your crew know when to pull or release lines and when it’s clear to proceed. We picked key words that quickly would communicate any necessary action.
Common mistake: Failing to communicate can lead to confusion, resulting in mishaps or collisions.

Step 4: Execute with Confidence

Why this matters: Once you’ve assessed your surroundings, set up your lines, and communicated with your crew, it’s time to execute your plan with confidence.
How to do it: Focus on maintaining a steady pace while adjusting your throttle as needed. Use your pivot points for guidance and remain aware of your surroundings as you complete the maneuver.
Example from my experience: After backing up and pivoting, I could see we had enough room to maneuver the boat into the slip. I was able to ‘spin’ the boat (forward on starboard and reverse on port throttle) to ensure a smooth entry into the correct slip.

Key Takeaways from Our Experience

Know your boat’s pivot points: Understanding where your boat pivots helps in executing maneuvers smoothly.
Practice makes perfect: The more you practice in tight spaces, the more confident you’ll become. We also practice on paper whenever we are in a challenging situation. I am also a huge fan of reviewing what went wrong and what we could do better next time. There is a reason the emergency responders and the military practice all the time!
Stay calm and focused: Keeping a level head during tense situations ensures better decision-making.

In conclusion, maneuvering your boat in tight spaces can be a rewarding challenge with the right techniques and preparation. By following these steps, you can enhance your docking skills and ensure a safer boating experience.

Frequently Asked Questions

How can I improve my docking skills?

Practice regularly in various conditions and seek guidance from experienced boaters or instructors.

What equipment is essential for docking?

A good set of fenders, spring lines, and a reliable communication system are essential for safe docking.

Are there specific techniques for different boat types?

Yes, techniques may vary based on the type and size of your boat; it’s important to understand your vessel’s unique handling characteristics.

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Navigating with dynamically updated AI-enhanced charts

AI Captains Log — Wed, 29 Apr 2026 12:03:43 GMT

Summary

In this conversation, Elizabeth Fortunato, the AI Captain, discusses the revolutionary advancements in ocean mapping technologies, emphasizing the transition from traditional static charts to dynamic, living charts created through a combination of satellite imagery, underwater drones, and AI. She highlights the importance of these technologies in enhancing our understanding of the ocean’s depths and conditions, making navigation safer and more efficient.

Takeaways

The ocean charts are evolving into living charts.
Satellite technology is crucial for modern ocean mapping.
Underwater drones can operate for over 30 days at sea.
AI is enhancing the accuracy of ocean depth measurements.
The endurance layer captures data that human crews cannot.
Multiple autonomous vessels can map vast areas quickly.
Satellite derived bathymetry allows for depth measurement without physical contact.
Technological advancements are making ocean exploration safer.
Mapping coral reefs is now possible without disturbing them.

Chapters

00:00:00 Hello, and welcome to the AI Captains Log.

00:00:27: But in 2026, the living chart is being built

00:00:45: The second layer is the endurance labor,

00:01:19: Next layer, the third layer, is the swarm.

00:02:07: Now, let’s talk about the first layer from the sky.

00:02:27: Using 2026 AI, NOAA analyzes imagery from space to measure how light changes and hits the bottom.

00:02:57: What’s the fusion?

00:03:17: What’s my take?

00:04:14: How does it all hit your helm?

00:04:45: If a robot from the Ocean Infinity or Chance identifies a new shoal,

00:05:13: The Living Chart is your new silent partner.

00:05:36: You can find me on Substack, Spotify, YouTube podcasts.

Frequently Asked Questions

What is a living chart?

A living chart is a dynamic mapping system that incorporates real-time data from various technologies to provide accurate insights into ocean conditions.

How does satellite-derived bathymetry work?

Satellite-derived bathymetry uses AI to analyze changes in light as it hits the ocean floor, allowing for depth measurement without direct contact.

What are the benefits of using ocean drones?

Ocean drones can operate for extended periods, collecting data in challenging conditions, which is essential for accurate mapping and monitoring of the seafloor.

How can I access real-time ocean data?

Mariners can access real-time ocean data through chart plotters that subscribe to live feeds, providing updates on changing conditions directly to their devices.

The Power of "Why"

AI Captains Log — Mon, 20 Apr 2026 12:05:43 GMT

We’ve all been there: the relentless “why” of a child. For me, that curiosity wasn’t just a phase; it was a permanent state of being. In fact, I asked “why” so often that my father eventually handed me a copy of The Question Book. To be clear, it wasn’t meant as a gift to celebrate my inquisitive mind—it was a gentle (if slightly exhausted) plea for a little peace and quiet.

But looking back, that book was a badge of honor. That innate drive to peer behind the curtain and understand the mechanics of the world has been the North Star of my life and career.

The Architecture of Understanding

Throughout my education, I found that I couldn’t simply accept facts at face value. I needed to see the blueprint.

In Engineering: I wasn’t content knowing that a structure stood; I wanted to understand the physics of the load-bearing joints.
In Psychology: I sought the “why” behind human behavior—what internal scripts drive our external actions?
In Biology: I was fascinated by the “why” of physiological responses—how the body maintains a delicate stasis against external stressors.
In Business: During my MBA, I fixated on the nuance between finance and accounting. One tells you where you’ve been; the other tells you where you’re going and why the capital moves the way it does.

Even on the water, working toward my USCG 50-ton captain’s license, “why” was my best tool. Understanding the why of tide charts and engine maintenance isn’t just academic; it’s a matter of safety and mastery. When you know why the current is pulling a certain way, you aren’t just reacting—you’re leading.

The Wall of Status Quo

As I transitioned into the professional world, I noticed a shift. Suddenly, “why” wasn’t always welcomed with a book; sometimes, it was met with a wall. We’ve all heard the refrains that stifle innovation:

“Because we’ve always done it that way.” “Why fix what isn’t broken?” “People hate change; they’ll fight it regardless of the benefits.” “The internet is a fade, it will pass.”

And my personal favorite: “Because I said so.”

These phrases are the graveyard of progress. Research in organizational psychology suggests that “status quo bias” is a powerful force; humans are naturally wired to prefer the familiar. But growth doesn’t live in the familiar. Innovation lives in the discomfort of a question.

Why “Why” Matters for AI

Today, we are facing one of the most significant technological shifts in human history: Artificial Intelligence. It can feel overwhelming, like a black box of complex algorithms and “magic” outputs. It’s tempting to just hit the “generate” button and stop asking questions.

But if we stop asking “why,” we surrender our agency. To truly harness AI, we must apply that same childhood curiosity:

Why does the model produce this specific output? Understanding the weights and biases helps us identify hallucinations or inaccuracies.
What data is feeding the model? Knowledge of the “why” behind the training sets allows us to spot inherent biases and ensure ethical use.
Why should (or shouldn’t) we use AI for this task? Just because we can automate a process doesn’t mean we should. We must understand the value proposition to keep the “human in the loop.”

Don’t Close the Book

Asking “why” is how we move from being passive users to empowered innovators. It’s how we pierce the veil of “that’s just how it is” and discover “how it could be.”

It can be intimidating to be the person in the room still asking questions when everyone else seems ready to move on. I’ve felt that pressure too. But remember: curiosity is the heartbeat of growth. Whether you are navigating a boardroom, a laboratory, or open waters, your “why” is your compass.

My challenge to you: The next time you encounter a new tool, a rigid process, or a “because I said so,” don’t stay silent. Channel your younger-self and curious mind. Pick up your own version of The Question Book.

Continue to ask “why.” Our growth in this new AI sector, and our collective innovation, depends on it.

AI Captain Podcast Introduction

AI Captains Log — Fri, 10 Apr 2026 19:09:23 GMT

Hello and welcome to The AI Captain’s Log. I’m your host, Elizabeth Fortunato.

I’ve spent over 30 years navigating the complexities of IT, and more recently received my USCG 50-ton Captain’s license after a lifetime on the water. Today, my two worlds are colliding.

We stand at the cusp of a significant shift in boating. AI-driven perception is no longer a ‘future’ concept—it is beginning to augment our traditional manual skills right now. But how do we bridge the gap between machine logic and a Captain’s intuition?

This podcast is a dedicated space for everyone across the marine world—from the engineers building the next generation of ships to the people behind the helm. We’re going to move beyond the AI hype to look at technology in action, the strategies behind the innovations, and the future of the ‘Connected Craft.’ Our goal is simple: To explore how these technologies can offer us more confidence and better awareness on the water.

The fog is lifting on the next technological leap. Let’s navigate it together.

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