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At container terminals, tens of thousands of containers, along with numerous vehicles and machines, are constantly in motion. With increasingly complex ecosystems, movement alone is no longer the biggest challenge. The real question is: How precisely can it be tracked? Positioning has evolved into the invisible nervous system of modern port logistics – the digital compass that guides every container, container ship, truck, and employee across the site.
For a long time, location data was recorded manually. This worked – as long as the number of containers didn't exceed a certain limit and other processes remained largely manual. But digitalisation and automation are fundamentally changing the situation. This is evident in clear figures: “The Container Position Detection System (CPDS) market is experiencing robust growth, driven by increasing automation in port operations and the need for enhanced efficiency in container handling. The market, valued at approximately $2.5 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033.” (1)
When decisions must be made within a very short time, all necessary information must be immediately available. Positioning has evolved from supporting data to a core infrastructure, similar to power supply or connectivity.
Positioning acts as a link between the physical world and data-driven systems (smart port technology). On the one hand, the system continuously captures location data for assets and personnel. On the other hand, it feeds this information into the terminal's operational control system—the terminal operating system (TOS), the planning software, and the predictive analytics systems that determine the next steps.
This presents both opportunities and challenges for the IT manager. The opportunities lie in transparency and precision: Real-time data streams enable systems to synchronise movements, avoid collisions, and dynamically optimise operational planning. The challenges arise from integration and data management—ensuring that all signals are consistent, latency remains low, and existing systems can process this new flood of geodata.
Beyond Tracking: Understanding Movement
The value of location tracking lies not only in knowing where things are, but also in understanding how and why they move. Integrated into overall terminal operations, location data becomes a diagnostic tool. It can uncover inefficiencies in truck routes, identify underutilised equipment, and even correlate movement patterns with energy consumption. With the right level of analysis, a terminal can move from reactive decision-making to proactive coordination, predicting disruptions before they occur.
In this sense, location tracking does for terminal operations what X-rays and MRI scanners have done for medicine—it makes something that was once invisible visible, measurable, and optimisable. Every movement leaves a digital trace, and these traces combine to create a real-time map of terminal efficiency.
Strategic Relevance for IT Leadership
For IT management, the introduction of position tracking fundamentally shapes the future terminal environment. It requires a reliable network infrastructure, robust data storage, seamless integration with existing IT systems, and a clear framework for managing position data.
Increased complexity raises the importance of spatial information. The systems that control devices, security protocols, and resource allocation will depend increasingly on the accuracy and consistency of position data. Without such a digital compass, operations will be hampered and unable to meet the demands of modern ports.
Precision as a Platform
Terminals that want to thrive in the next decade leverage precision as a reliable, scalable layer upon which automation, analytics, and sustainability goals are built. Whether it's reducing fuel consumption, improving asset utilisation, or enhancing safety, all these goals are based on the same fundamental insight: You can't improve what you can't precisely locate.
In other words, the digital transformation of ports begins with knowing where everything is at all times. Positioning is that compass guiding terminals into a future defined by clarity and control.
What Do We Really Mean by Position Detection?
Positioning sounds deceptively simple – as if it were just a matter of placing a digital marker on a map. In reality, it describes a complex interplay of sensors, algorithms, and communication systems that together determine where something is, how it is moving, and how this information fits into the operational context. In the world of container terminals, understanding this distinction is crucial to developing precise, scalable systems.
From Location to Context
At its core, location tracking answers the question: "Where is this object right now?" For a terminal, however, this question is far more complex. The position of a container, for example, is not just its latitude and longitude – it also includes which block, row, and parking space it occupies within the terminal. For container handling equipment (CHE), it's not just a route on a map – it encompasses the lane, speed, and distance to other vehicles (for more, see: CHE operator).
Modern systems, therefore, go beyond simple localisation. They aim to translate physical movements into operationally meaningful coordinates – coordinates that can be interpreted by the terminal's software environment, from the terminal operating system (TOS) to the maintenance management system. Without this translation, raw location data remains unstructured and of limited use.
Positioning, Tracking, and Localisation — Not the Same Thing
It is important to distinguish between three key terms that are often used synonymously but serve different purposes:
Positioning: Determining the current position of an object at a specific point in time.
Tracking: Continuously monitoring the movement of an object over time, thereby creating a motion history.
Localisation: Determining a position relative to other known reference points—for example, the position of a container relative to a crane or sensor array.
At container terminals, all three are essential: Positioning enables the precise localisation of equipment. Tracking ensures that movements are recorded for analysis and follow-up. Localisation supports autonomous or semi-autonomous systems that navigate relative to their environment rather than relying solely on technologies such as GPS.
Absolute vs. Relative Positioning
Absolute positioning refers to coordinates tied to a global reference system, such as GPS. It is useful for field applications, such as truck navigation or monitoring approaching ships.
Relative positioning determines an object's position relative to other objects or fixed reference points in its environment. It is crucial in densely populated container terminals, where GPS signals are often weak and accuracy down to a few centimetres can determine the success or failure of automated processes.
A robust positioning system often combines both methods—absolute data for global orientation and relative data for precise control. This hybrid approach is becoming increasingly common as terminals become more automated and require high spatial resolution, even in areas with poor GPS reception.
Real-Time vs. Event-Based Detection
Another key difference lies in the frequency of position data acquisition and processing.
Real-time position tracking provides continuous updates and is ideal for moving equipment or safety-critical operations.
Event-based position tracking records the position only when specific events occur—for example, when a container is lifted or set down, or when a truck enters a defined area.
The choice between the two methods depends on operational requirements. The challenge lies in balancing data volume, resolution, and relevance to achieve optimal results (PDS automation).
The Container Terminal as a Living Map
The terminal can be thought of as a living map – a dynamic environment where every object, vehicle, and container has a digital twin that constantly updates its position. RTGs know the location of the next truck and, therefore, the next container to be handled before they have even completed their current hub. Trucks optimise their routes based on the terminal area's current occupancy. The terminal operating system (TOS) predicts delays before they occur.
Behind the idea of "knowing every location precisely" lies a complex ecosystem of diverse technologies. Each positioning method—from satellites to sensors installed on terminal premises—brings its own trade-offs in terms of accuracy, cost, and scalability. For IT managers in terminals, understanding this landscape is crucial for making informed infrastructure decisions and planning future extensions.
The Big Picture: Precision Meets Environment
A container terminal is not an ideal environment for positioning systems. Metal surfaces reflect radio waves. Stacks of containers block the line of sight. Metal parts of CHEs and cranes interfere with wireless communication. Given these conditions, no single technology can guarantee flawless accuracy everywhere. Therefore, modern positioning strategies increasingly rely on hybrid systems – combining different data sources to generate a more stable and precise positional picture. Let’s have a look at the most important pillars of this landscape:
GNSS: Reliable, But Not Everywhere
Global Navigation Satellite Systems (GNSS), including the world's most widely used GPS (USA), form the backbone of outdoor positioning. They offer global coverage and 2–5-meter accuracy in open areas—sufficient for many logistics processes, such as truck navigation.
However, GNSS reaches its limits in terminals. Crane booms, ship hulls, and dense stacks of containers cause multipath propagation, where signals are reflected before reaching receivers. Even slight distortions can lead to inaccuracies of several meters—unacceptable for automated stacking cranes or straddle carriers.
Therefore, terminals rarely rely solely on GNSS. While it serves as the primary source for large-scale positioning, it must be supplemented by local corrections or other technologies as operations extend deeper into the terminal area.
Global Navigation Satellite Systems (GNSS), including the widely used GPS, form the backbone of outdoor positioning and deliver about 2–5 m accuracy in open areas—enough for many logistics tasks such as truck navigation.
But GNSS reaches its limits in terminals. Crane booms, ship hulls, and dense container stacks cause multipath propagation, where signals are reflected before reaching the receiver. Even small distortions can introduce meter-level errors—unacceptable for automated handling equipment.
Differential GNSS (DGNSS) improves baseline accuracy through corrections from a fixed reference station and can reach sub-meter levels. Still, it depends on clean satellite signals, and in obstructed terminal environments, multipath dominates, limiting its effectiveness.
Terminals, therefore, rarely rely solely on GNSS or DGNSS. They serve as the large-scale positioning layer but must be supplemented by local correction or alternative positioning technologies deeper inside the terminal.
RFID and Passive Identification: Knowing “What” Rather Than “Where”
Radio-frequency identification (RFID) has been an integral part of the terminal ecosystem for decades. It is ideally suited for tracking identity and movement—for example, a truck passing through a gate or a truck arriving at an RTG.
Active RFID tags improve upon traditional approaches by emitting their own signals, allowing readers to detect their presence in specific areas. This makes them significantly better suited for monitoring movement and status—for example, confirming when a container enters a zone or when a vehicle passes a checkpoint.
Radio-frequency identification (RFID) has been part of terminal operations for decades. It is well-suited for identifying assets and tracking discrete events—such as a truck passing a gate or a container being placed on a chassis.
Active RFID extends this concept by using battery-powered tags that broadcast their own signal. This enables longer read ranges and more reliable detection, even on metal or in motion, making it useful for confirming zone entries, vehicle passages, or other status changes in operational areas.
Ultra-Wideband (UWB): Centimetre Precision
For dense, complex environments, ultra-wideband (UWB) technology has established itself as one of the most promising tools. UWB operates with extremely short radio pulses across a wide frequency range, enabling highly precise distance measurements—often down to tens of centimetres—even where GPS cannot operate reliably.
UWB tags can be attached to vehicles, containers, or personnel and communicate with fixed anchor points throughout the terminal area. The system then calculates precise positions based on signal propagation times. Because its short pulses reduce the impact of reflections, UWB remains robust in metal-rich and cluttered environments, although performance still depends on line-of-sight and careful anchor placement.
BLE and Wi-Fi: The Middle Ground
While less precise than UWB—typically within a range of 1–5 meters under favourable conditions—these technologies are well-suited for tracking equipment and personnel when relative positioning is more important than precise coordinates.
BLE beacons, for example, can complement other systems by confirming presence in a defined area. Their strength lies in their flexible integration: they can use existing network or Bluetooth infrastructure, thus reducing deployment costs. However, their reliance on signal-strength measurements makes them sensitive to noise, interference, and environmental changes, which limits their suitability for mission-critical automation.
Vision Systems and AI Recognition
Cameras and computer vision (such as optical character recognition, OCR) can determine object identity and approximate location (depending on view quality), provided the view is unobstructed. Mounted on cranes, vehicles, or fixed structures, cameras can identify containers, detect orientations, and visually verify positions.
Image processing systems are characterised by context awareness. They can confirm not only the location of an object but also its function—for example, the lifting of a container, the release of a twist lock, or the proximity of an employee. In combination with machine learning, these systems can detect anomalies and dynamically support safety protocols.
However, they also present their own IT challenges: high demands on bandwidth, storage, and processing, as well as the need to handle image data securely. For IT managers, this often means balancing local processing with centralised analysis to avoid network congestion.
Sensor Fusion: The Smart Combination
In most modern terminals, no single technology dominates. Instead, sensor fusion – which combines GNSS, UWB, and image processing data – provides the accuracy, reliability, and continuity required by automation. Sensor fusion systems use algorithms to balance conflicting signals, filter out noise, and ensure reliable position determinations even when a data source fails.
This approach is not only technically elegant but also operationally essential. As automation increases, redundancy becomes reliability. A position-detection system that adapts to its environment ensures that every automated process has a stable digital reference system.
Choosing the Right Mix
The optimal combination of positioning technologies depends on the layout, level of automation, and IT maturity of each terminal. For existing sites (brownfield locations), phased upgrades are often advantageous, while for new-build terminals, fully integrated hybrid systems can be planned from the outset.
For the IT department, the challenge lies not only in selecting the technologies but also in designing the data flow, ensuring that all positioning information, regardless of its source, is seamlessly integrated into the terminal's digital ecosystem.
Location data alone doesn't create value – only the insights gained from it do. Knowing where something is only relevant if you also understand why it's there, what it's doing, and what should happen next. This is where the real transformation begins: converting raw coordinates into operational information.
For IT managers, the challenge lies not in data collection, but in processing it – in integrating it with other systems, enriching it with contextual information, and visualising it to enable decisions across the entire terminal.
Every terminal generates vast amounts of location information – from cranes, trucks, AGVs, and containers. But location is only one layer of truth. To derive meaning from it, it must be combined with other layers:
Time data: Timestamps indicate movement, dwell time, and process bottlenecks.
Status data: Sensor readings from refrigeration units, machine monitoring systems, or gate systems provide context.
Operational data: TOS and ERP systems provide task assignments, inventory data, and key performance indicators.
When these layers are synchronised, a digital representation of the terminal is created – a representation in which every movement, delay, or anomaly is traceable and understandable.
Integration Is the Real Differentiator
Many terminals already have excellent data sources, but they operate in isolation. The key to real-time insights lies in system integration. Location data must flow seamlessly into planning, control, and analysis environments.
For an IT manager, this is not just a technical challenge. It's about creating a data infrastructure—a consistent, reliable layer of information that everyone, from operations to management, can depend on. Without this foundation, location information remains fragmented and underused.
Context Turns Coordinates into Decisions
A coordinate on a map is initially just a number. But when this number is linked to a container ID, an order, and a timestamp, it gains significance.
A simple example: A container remains stationary on the premises longer than planned. Position data alone indicates inactivity. However, in combination with TOS data (transport and operational data), it becomes clear that the container should have been moved two hours ago. Adding in the equipment's telemetry data might reveal that the assigned straddle carrier has broken down. Context transforms static data into operational insights—and ultimately, into corrective actions.
Modern positioning systems, therefore, function as context engines rather than just localisation tools. They imbue every movement with meaning.
The Visual Dimension
The human brain is designed for spatial understanding. Maps, dashboards, and 3D views of the site translate complex movement data into something immediately comprehensible.
Visual analytics platforms can display equipment movements, container accumulation, and bottlenecks in real time. However, the true power of visualisation lies in its ability to uncover patterns that weren't previously considered.
For example, overlaying location data with job completion times can reveal that delays occur regularly in certain areas or during specific shifts. These insights enable continuous improvement—not based on guesswork, but on facts.
Global Navigation Satellite Systems (GNSS) is the umbrella term for satellite-based positioning technologies, including GPS (USA), Galileo (European Union), GLONASS (Russia), and BeiDou (China). These satellite constellations continuously transmit signals that ground-based receivers interpret to calculate precise positions. In simple terms, a GNSS receiver measures the travel time of each signal and uses this information to determine its position via triangulation.
In container terminals, GNSS is commonly used to track vehicles and equipment, but its performance can vary. Steel structures, container stacks, and cranes can block or reflect signals, reducing accuracy. Therefore, terminals often combine GNSS with complementary technologies such as UWB, RTLS, or lidar to achieve decimetre- or centimetre-level accuracy. While GNSS remains the foundation for outdoor positioning, its full potential is realised within a more comprehensive, multi-sensor-based positioning system.
Position detection has become the foundation of future-proof terminals. Its benefits extend far beyond locating containers or tracking vehicles: it provides the spatial context that enables automated systems to operate, offers planning tools to anticipate disruptions, and enables operations teams to make faster, better decisions.
No single technology can meet all the requirements of a complex port environment—which is why hybrid systems and sensor fusion are now the strategic standard. For IT managers, the task is clear: develop a precise, integrated, and resilient positioning architecture. Terminals that master this level enable safer operations, higher utilisation, lower energy consumption, and unprecedented operational transparency. In the age of automation, precision is no longer optional—it's the platform that makes everything else possible.
Delve deeper into one of our core topics: Smart Port
Triangulation in position detection is a geometric method for determining an unknown point’s location by measuring angles from two or more known reference points. In practice, sensors, antennas, cameras, or laser heads with a known baseline distance measure bearing/angle to a target; intersecting the resulting rays yields the target position in 2D or 3D space. This principle underpins applications such as radio direction finding, optical tracking, laser triangulation sensors, surveying, and some indoor positioning and machine vision systems. (2)
Ultra Wideband (UWB) is a radio technology that uses very short pulses spread across a wide frequency spectrum (3.1 to 10.6 GHz) to precisely determine device locations. UWB measures time-of-flight (ToF), calculating the travel time of signals between transmitters and receivers to achieve centimetre-level accuracy. This capability allows real-time, highly accurate indoor and obstacle-penetrating localisation, making UWB ideal for asset tracking, navigation, and secure device interaction. It provides low latency, high data rates, and resistance to interference, outperforming other positioning technologies like Bluetooth and Wi-Fi. (3)
References
(1) https://www.archivemarketresearch.com/reports/container-position-detection-system-460501
(2) Wolf, Paul R., Ghilani, Charles D. (2012). Elementary Surveying: An Introduction to Geomatics. Pearson.
(3) Gezici, Sinan (2010). Ultra-Wideband Positioning Systems: Theoretical Limits, Ranging Algorithms, and Protocols. Cambridge University Press.
Note: This article was partly created with the assistance of artificial intelligence to support drafting.