Welcome to AISflix

• Vessels under 50 m are shown on the map but excluded from collision calculations.
• Ships moving under 3 kt are omitted entirely to keep things fast and clean.
• AIS data is received from aisstream.io — thanks to them for sharing this!

Live

The Live module delivers a real-time map of vessel positions, updated instantly as AIS messages are received. It runs collision-risk analysis on the fly, flagging potential near misses before they happen. This view is ideal for enthusiasts wanting a live snapshot of maritime activity, and for exploring patterns in busy waterways. You can pan and zoom to focus on specific areas of interest, whether that’s a local harbor or open sea lanes.

History

The History module lets you replay past vessel movements with full trajectories, speeds, and calculated risk scores. It’s useful for reviewing incidents, studying traffic behavior over time, or understanding how near misses evolved. You can jump directly to a vessel’s callsign or scrub through time to pinpoint moments of interest. This is especially valuable for educational analysis and for enthusiasts studying maritime navigation in detail.

Weekly

The Weekly module condenses seven days of AIS data into statistics, charts, and heatmaps. It highlights the busiest regions, the number of near misses, and evolving traffic patterns. This helps identify long-term trends, such as seasonal traffic shifts or emerging bottlenecks in shipping lanes. Comparing weeks side by side can reveal how maritime activity responds to weather changes, port schedules, or large-scale events.

CPA (Closest Point of Approach)

CPA measures the smallest distance two vessels will pass each other if they continue on their current course and speed. It’s a vital early-warning concept — small CPAs can signal the need for a course adjustment, while large CPAs mean a safe passing distance. Mariners watch CPA to anticipate and act well before a close encounter.

TCPA (Time to CPA)

TCPA estimates the time remaining until two vessels reach their CPA. A short TCPA means action may be needed quickly, while a longer TCPA allows for more planning and monitoring. Combined with CPA, it gives both distance and urgency, helping crews prioritize responses.

CRI (Collision Risk Index)

CRI is a numeric score (0–99) estimating the relative collision risk between two vessels. It blends ship size, speed, and course convergence into a single value. The higher the CRI, the more energy and convergence exist in the encounter, and the greater the potential hazard. CRI is not an absolute predictor but a helpful guide for comparing situations.

m1 = length1 × width1
m2 = length2 × width2
k1 = m1 × SOG1²
k2 = m2 × SOG2²
Δ  = |COG1 − COG2|
f  = 1 − cos(Δ·π/180)
raw = (k1 + k2) × f
CRI0..99 = clip(99 × (raw − min) / (max − min))
      

Step-by-step: (1) Multiply length × width for each ship to get an effective size. (2) Square the speed to give fast ships more influence. (3) Multiply size by squared speed to estimate “movement energy” for each vessel. (4) Find the difference in course and convert it into a factor (0–2) using cosine. (5) Combine energies and angle factor to get the raw risk. (6) Scale that raw value between a configured min and max to produce a CRI from 0–99.

Interpreting CRI: Low (<25) = most likely an overtaking situation, Medium (25–49) = usually slow, small craft, High (50–74) = medium or large craft on various course meeting situations, Critical (≥75) = large and fast ships on a head-on situation. The 0–99 scale keeps scores easy to compare and consistent across different encounters, making it a practical decision-support tool.

Ship Length Colors

Marker Meanings

Warnings

I work at sea — a certified Unlimited Master Mariner — but whenever I can, I dedicate my free time to AISflix. This project is born out of pure curiosity and passion for data, AI, and the future of the maritime industry.

Every line of code you see here was generated in collaboration with ChatGPT, blending human experience with machine creativity. I started AISflix because I couldn’t find anything like it online — and I wanted to see what was possible when technology meets seafaring insight.

I’m genuinely proud of what has been built so far, and even more excited about what’s ahead. I believe there’s endless potential in how AIS data can be utilized, visualized, and expanded into powerful tools that serve everyone who works at sea.

If you have ideas, spot issues, or want to collaborate — your input is always welcome.
📧 daniel@danielmi.com