Vessel tracking and AIS data

Understanding AIS data

AIS (Automatic Identification System) is a tracking system used by vessels to report their position, speed, course over ground, and other navigation details. While widely used for real-time tracking, it comes with limitations that affect data consistency and trace calculations.

Key characteristics of AIS data

• Event-driven, not time-driven:
  • Updates depend on vessel speed, location, and coverage—not fixed time intervals.
• Irregular transmission intervals:
  • High-frequency updates nearshore or during slow maneuvers (e.g., docking).
  • Low-frequency updates in open seas, sometimes hours apart, especially via satellite relays.
• Signal loss and coverage gaps:
  • Signals may be blocked by terrain, weather, or interference.
  • Dense areas may experience data thinning when signals overload satellite processing.
• Operational variability:
  • Vessels might sometimes turn off transponders for security reasons or switch between AIS classes, affecting signal behavior.

AIS was designed for collision avoidance, not historical tracking or analytics. This inherent variability shapes how we process and clean AIS data for trace calculations.

How we use AIS data

1. Vessel last known position

• /vessel/v2/{imo}/position
• We use AIS data to provide the vessel’s last known position.
• ETA (estimated time of arrival) is calculated to the next port, considering factors like speed, course overground and port location.

2. Vessel timeseries

• /vessel/v2/timeseries
• It provides a detailed historical record of a vessel’s positions, including timestamps, speed, draft, and course over ground.
• Unlike /vessel/v2/trace, which reconstructs a vessel’s trajectory as a geometry, the timeseries endpoint returns raw positional data for analytical use.

3. Trace creation using AIS data

• /vessel/v2/trace
• When delivering a trace of a vessel between two past dates, we:
  • Retrieve successive positions from AIS data.
  • Process the data to create a geometry (route) and statistics such as distance traveled, average speed (for the entire trace, stops included), time spent at sea, and areas crossed.

How we clean AIS data for traces

AIS data often includes errors or unrealistic points, which can result from:

• Signals crossing land.
• Unrealistics points suggesting impossible movements or speeds.
• Inconsistent updates causing gaps in the data.

To ensure trace accuracy, we apply cleaning rules:

1. Remove invalid points that deviate significantly from expected routes.
2. Fill gaps with interpolated points to recreate realistic paths.

Key takeaways for users

• Users should expect irregular intervals in AIS data due to its event-driven nature—this is not an error but a realistic representation of vessel operations:
  • vessel/v2/{imo}/position
  • /vessel/v2/{imo}/eta
  • vessel/v2/timeseries
• While AIS data is inherently variable, we optimize it to deliver realistic traces :
  • /vessel/v2/trace