Minimizing Drill Errors at Sea with AI-Powered Video Analysis

“A ship in the harbor is safe, but that’s not what ships are for!”.

Yes, ships are always associated with the word ‘adventure’. But we must ensure that this adventure is safe. That’s where safety drills come into play. Out at sea, it’s not just a formality but a real lifeline at the ocean. From fire response to lifeboat launching, these drills make crews ready to react quickly under life-or-death stress. The International Convention for the Safety of Life at Sea (SOLAS) and the ISM Code mandate regular safety drills on vessels, with detailed logs, oversight, and compliance requirements.

Safety drills often suffer from the same weaknesses that cause many manual processes: human error, inconsistent observation, and a heavy burden on safety officers. A delayed fire-hose activation or improperly donned breathing apparatus may go unnoticed during a drill—but could prove fatal during an actual emergency.

This is where AI and automation enter the picture. In particular, computer vision—a branch of AI that specializes in interpreting visual information—provides a revolutionary means of monitoring, analyzing, and enhancing safety simulations with accuracy and impartiality.

What Is Computer Vision?

Computer vision allows machines to interpret and understand visual input from cameras and sensors. In maritime drills, it can perform:

• Object Detection – Identifying equipment like fire extinguishers, life-jackets, hoses, and masks.
• Pose Estimation – Understanding human posture and movements (e.g., crawling low in a fire drill).
• Action Recognition – Distinguishing specific procedures (e.g., vent closure, hose charging, escape routes).

Key Capabilities for Drill Scenarios

AI-powered vision systems can support drill monitoring by:

• Detecting Required Equipment: It ensures each crew member is wearing the right personal protective equipment (PPE), and identifying missing or improperly worn gear.
• Tracking Crew Movement: It tracks individual crew routes and formations to ensure coordination and compliance with standard protocols.
• Recognizing Correct vs. Incorrect Actions: Flagging deviations like missed vent closures, hose kinks, or untested nozzles in real time.

Key Benefits of AI-Powered Drill Review

Traditional drills are reviewed after the fact—often with minimal video footage and heavily reliant on human memory. AI in maritime industry changes that:

• Instant Feedback: Instead of waiting for post-drill debriefs, crew members can receive immediate, specific, and timestamped feedback.
• Unbiased Assessment: Removes subjectivity from the equation, ensuring every crew member is evaluated fairly, based on visual evidence.
• Best-Practice Library: Successful drills can be cataloged into a searchable video library to train new crew members or support audits.

Human + Machine: A Winning Combo

AI isn’t replacing the safety officer—it strengthens their capability.

• Second Pair of Eyes: While humans might miss a poorly clipped harness or a 3-second delay, AI detects it with unwavering accuracy.
• Coaching vs. Note-Taking: With AI handling observations, safety officers can focus on guiding, encouraging, and correcting crew in real-time.
• Targeted Training: Drill footage and analytics reveal patterns over time—empowering officers to run focused sessions addressing specific weak spots.

Overcoming Adoption Hurdles

Despite the benefits, introducing AI to traditional maritime operations can raise valid concerns:

• Crew Buy-In: Transparency is key. Make it clear that the system is designed to support the crew. Emphasize learning over surveillance.
• Start Small: Launch a pilot with one type of drill (e.g., fire response) and one camera setup. Expand only after seeing results.
• Privacy & Data Ownership: Clearly define who can view the footage, how long it’s stored, and how it’s used. Establish trust through well-communicated policies.

Case Study: AI-Assisted Fire Drill on a Crewed Vessel

Overview

In an effort to enhance onboard emergency preparedness, a fire drill was conducted aboard a crewed commercial vessel using AI-powered vision analytics. The objective: simulate a real fire scenario in a high-risk area, analyze crew response, and deliver actionable insights to improve safety protocol adherence and reaction times.

Scenario Setup

A high-fidelity simulation was initiated while the vessel was underway at 8 knots, introducing real-world operational stress. The artificial emergency was triggered in one of the most critical zones onboard—the engine-room fuel-oil header, an area prone to ignition due to high pressure and temperature.

• Conditions: All crew members were stationed as per standard fire drill protocols.
• Purpose: To monitor reaction time, PPE compliance, fire suppression procedure execution, and coordination using advanced AI vision tools.

Drill Execution & Monitoring

To capture every critical action and enable granular post-drill review, multiple video recording tools were deployed:

Camera Deployment

• Fixed Overhead CCTV: Installed across the engine-room to capture full-area activity and vent behavior.
• Helmet Cams: Worn by the chief engineer and fire-party leader for first-person perspective and task verification.

Action Timeline

1. Alarm Activation: Fire alarm sounds, simulating engine-room detection.
2. Initial Response: Crew is expected to shut down ventilation and fuel systems.
3. PPE & Equipment: Fire-party dons full BA (Breathing Apparatus), collects hoses, and checks nozzles.
4. Fire Suppression: Fire mains are pressurized; simulated fire suppression is executed using CO₂ and mock fire barrels.
5. All-Clear: Drill ends with a coordinated “all-clear” declaration.

AI-Vision Analysis & Incident Highlights

The AI system analyzed over 20 minutes of video footage using real-time object recognition, time-sequencing, and posture detection. Here’s what it found:

1. Vent Closure Compliance

• Issue Detected: Two engine-room vents remained open for four seconds post-alarm.
• AI Insight: This delay indicates a compliance breach and potential escalation risk in a real fire.

2. PPE/BA Harness Violation

• Issue Detected: One crew member was flagged for having an unfastened BA harness.
• AI Insight: A loose harness compromises respiratory protection, posing a severe safety threat.

3. Hose Deployment Issue

• Issue Detected: A kink in the high-pressure hose near a bulkhead connection was observed.
• AI Insight: This can restrict water flow, reducing suppression effectiveness. Also, a 3-second delay was recorded between “all-clear” and water nozzle activation.

Debrief & Coaching Outcomes

Instead of wading through the full-length drill footage, the safety officer received 4 concise, AI-curated clips with visual annotations:

These clips formed the backbone of the post-drill debriefing session, helping crew visualize mistakes and understand precise areas of improvement—enhancing retention and safety awareness.

Impact

• Time Saved: Reduced review time by over 85%.
• Training Value: Transformed a routine drill into a precision-based learning experience.
• Safety Compliance: Highlighted and corrected real-world safety blind spots before an actual emergency.

Conclusion

Safety drills save lives, but only when executed flawlessly and learned from thoroughly. AI-powered computer vision transforms these drills from just exercises into precision training tools. By offering instant feedback, reducing human oversight burden, and surfacing meaningful insights, this technology can elevate maritime safety standards across commercial, cargo, and luxury vessels alike.

As the shipping industry continues to modernize, integrating AI maritime compliance software into critical processes like safety drills is a necessary evolution. With smart adoption, clear communication, and crew involvement, AI becomes a trusted partner in building safer, more responsive seafarers.