Use Of Internet Of Things For Large Scale Shipping Ports


The operations of large-scale shipping ports can be improved through the use of Internet of Things,

Big data, and analytics:
Explain how these technologies can be used in the enterprise architecture of

A large-scale port.

Abstract: In this report, technologies and concepts are explained and summarized under the headings of Internet of Things, Big Data, Analytics, Enterprise Architecture and Large-scale ports. These technical advancements and concepts are explained using definitions, statistics, rational for use and examples of how they are implemented and functioning in today’s enterprise architecture of large-scale ports. A keen focus is directed at how the operations of these ports is improved by the technological headings stated above. Moving on, these concepts are correlated with headings of popular current topic discussions and real-world functioning examples of systems implemented and functioning in major ports around the world today.

Keywords: Internet of Things, Big Data, Analytics, Enterprise Architecture, Large-Scale Ports


Ports all over the world have developed through phases of innovation. Some of the development stages that ports go through are informationalized, digital and most recently intelligent ports. With the advancements in technologies related to The Internet of Things (IoT), Big Data and Analytics, the formation of intelligent ports is possible.

For example, we see ports like Rotterdam joining forces with the super tech company IBM to transform the biggest port in Europe to an IoT digital operation. As the largest port in Europe, the Port of Rotterdam handles over 461 million tonnes of cargo and more than 140,000 vessels annually. The digital transformation involves applying sensors for over 42km across land and sea. (Campfens, 2018)

This major transformation could/would not happen without IoT, Big data and Analytics. These sensors are spread  accross a 42km radius from the City of Rotterdam into the North Sea. The sensors gather multiple data streams which include water (hydro) and weather (meteo) data about tides and currents, temperature, wind speed and direction, water levels, berth availability and visibility. (Campfens, 2018)

This is just one instance example of how technologies can be used in the enterprise architecture of a large-scale port.

This report produces many more functioning examples in detail of how these technologies are been utilized today, based on the concepts and motives for this review.

1.1    Internet of Things – IoT

The term Internet of Things was invented approximately in 1999, initially to promote Radio-frequency identification technology (RFID). The new buzz acronym (IoT) then took off in 2010 and hit the market in 2014 as the next big tech advancement. (Lueth, 2018)

The IoT concept essentially displays billions of internet enabled devices around the world that collect and share data with each other. Wireless networks are the backbone to the IoT architecture and with fibre power fast connections it can just get better, without wireless networks IoT would not be possible. Devices that were once dumb can now have digital intelligence and become useful within the wireless network spectrum. (Ranger, 2018)

1.2 Big Data

Data has been exponentially increasing in the last decade, it is increasing in every facet of our lives. On the internet alone, take Google, Amazon, Microsoft and Facebook for example. It is closely estimated that they alone store at least 1,200 petabytes between them. That is 1.2 million terabytes (one terabyte is 1,000 gigabytes). Yet this is only a tiny minuscule subset of the data population that resides in the world. But where is all of this data been stored? And what is been done it analytically to make value of it? (Mitchell, 2018)

In theory, big data is a term used to represent a large amount of data structured or unstructured, that is so large it is difficult to process it using the traditional methods of database technology and software techniques. In most enterprise scenarios, the volume of data is too big or it moves too fast, or it exceeds current processing capacity. (Beal, 2018)

1.3 Analytics

Analytics is the discovery, interpretation, and communication of meaningful patterns in data. It is common among organisations for example to apply analytical methods to their business data to describe, predict and improve business performance. (Knight, 2018)

Big data and analytics have an important relationship with each other. With the huge amounts of data been generated, analytics is more prevalent, more manipulation and analysis can be done with this data. Predictions can be made analytically from this data, organisations can strategically use the now analysed data for forecasting and profitization techniques. (Knight, 2018)

1.4 Large Scale Ports

A port is a maritime commercial facility which may comprise of one or more wharves where ships may dock to load and discharge passengers and/or cargo.

Currently, statistically speaking Asia shows the greatest growth in port development having some of the biggest in the world. The biggest and busiest ports in the world are ranked by there cargo tonnage and volume of container shipment. (Underwriting, 2018)

As of April 2018 the top 3 busiest ports in the world are, please see: Table 1, Appendix A.

1.5 Enterprise Architecture

According to TOGAF (The Open Group Architecture Framework) enterprise architecture is a formal description of a system or a detailed plan of the system at component level to guide its implementation. The structure of components, their inter-relationships and the principles and guidelines governing their design and evolution over time. (Opengroup, 2018)

According to the ISO (International Organization for Standardization) enterprise architecture is the fundamental organization of a system, embodied in its components, their relationships to each other and the environment, and the principles governing its design and evolution. (ISO, 2018)

An enterprise architecture is broken down into the following layers: please see Fig. 1, Appendix B.


Although some shipping ports could be considered functioning in the Stone Age when it comes to operations, there have been a number of technological advancements in ports. We have seen the introduction of facets like sensor technology and drones in the present day and in the future we expect to see (AI) artificial intelligence and nanotechnologies to emerge accordingly to meet the demand. (Scott, 2018)

2.1 TEUbooker – Port of Rotterdam

TEUbooker is a platform for facilitating the booking of container transports. This idea was born in 2015, which on the tech timeline could be considered a long time ago. However, it was born as a result of not being able to book container transports online within the port of Rotterdam. Everyday there are many rail and barge movements that still have unused capacity, leaving a niche to capitalize on. Using this capacity TEUbooker creates a huge amount of free space for exchanging containers. The platform simply finds free space on a paid order and sells that space to another customer. (TEUbooker, 2018)

TEUbooker’s algorithm optimises the booking of containers, by searching for space on existing barges and matching a new order to see if there is a match with an existing one, which in turn lowers the cost by adding an order to an existing one. The resulting output is that costs get lowered as they are ultimetly now shared, space is maximised and costs minimized leaving everyone happy. (TEUbooker, 2018)

Additionally there is also personalised dashboard software for users to use for tracking and monitoring the cargo. The user will no longer have to look for available space, TEUbooker assigns containers directly to participating operators on the basis of their capacity and schedules. The system will do all of the work, efficiently. (Swarttouw, 2018)

2.2 Infrastructure

Sensors help port component workers like terminal operators to track, operate and maintain physical infrastructure that they manage. Sensors are embedded throughout the port and transmit real-time data about operating conditions. These sensors eliminate the need for scheduled inspections and provide data that can be used to take preventative maintenance for the important infrastructure. (Riedl, Delenclos and Rasmussen, 2018)

2.3 Cargo Handling

Monitoring systems improve the port efficiency by viewing performance status of cargo machinery, operations can be completed at full performance and properly maintained as needed. A container terminal in the Port of Valencia in Spain uses this tech. They use “Black Boxes” to gather this data in real-time. This data can now be used to raise red flags or identify busy or relaxed times to maximise on. An estimated 10% could now be saved by minimizing energy use and maximizing on idle time. (Riedl, Delenclos and Rasmussen, 2018)

2.4 Intermodal Traffic

Traffic handling can be complex when ports are congested with traffic, this can essentially slow down operations if not managed efficiently.

The port of Singapore is testing a GPS traffic monitoring system that tracks the movements of trucks, with this system it notifies terminals when vehicles are approaching certain areas and provides directions on where to go, and specific instructions on how to approach a particular area. (Riedl, Delenclos and Rasmussen, 2018)

2.5 Customs and Collections

Managing paperwork and authenticating port shipments can also be done more efficiently. Work like handling cargo information and payments, trade licenses and permits can be time consuming. Some European ports like Antwerp and Rotterdam are experimenting with blockchain technology making encrypted secure data and away from paper based records. This saves huge amounts of money on labour and processing costs. (Riedl, Delenclos and Rasmussen, 2018)

2.6 Safety and Security

Advancements in security risk are vast, ports can use surveillance systems that use advanced video analytics to predict and detect breaches by pattern recognition and movement which automatically work to notify authorities and security personal. Biometrics like eye scanning and finger print authentication are more common. Senor networks can tell someone driving a piece of machinery to stay in between the lines if they cross for some reason. (Riedl, Delenclos and Rasmussen, 2018)


Currently the world is experiencing a data revolution “data deluge”. In previous years, much smaller amounts of analogue data was produced and available through a limited number of channels. Today a massive amount of data is regularly being generated and flowing from many sources through different channels in today’s digital age.

What creates the data deluge is the speed and frequency which the data is being emitted and transmitted, plus the rise in the number of sources in which the data emanates from. The figure in Appendix C Fig. 2, shows the market size based on monetary value expectations in billons forecasted for from present day to the year 2026. (Letouzé, 2018)

3.1 Big Data Exploitation in Container Terminals

Analysing all of this exponentially generated Big Data can bring value to a ports operations and efficiency. The most widely used piece of software used within a container terminal is the TOS, terminal operating system.

This piece of software handles from documentation to planning, to operations, to billing other business processes. This in turn creates a huge amount of data.

This data along with all of the other data like sensors being generated in the port is not being used to gain business value.

With the use of analytics, the data is a useful tool for analysing past operational data and can be used for making educated future predictions. This can help to reduce risks and costs by prediction based on factual data. (Jung, 2018)

3.2 Big Data Exploitation – Stages

In order to create value from the data, the data must go through a logical sequence of phases, please see Fig. 3, Appendix D.

Phase 1: The data plus the system will generate information. For example, GPS sensor is installed in a yard truck to gather location data in the formats of time stamp, sensor ID, and send these values to big data storage, using the terminal’s Wi-Fi network. (Jung, 2018)

Phase 2: The now gathered information from the previous stage plus the experience will generate knowledge. For example, one decides in which area (in relative location; e.g., 1A-31) a vehicle (in absolute location; e.g., 34.5678, 75.3454) is located and if it is the location for the task at hand, based on the location data for the yard truck that is acquired stage 1. (Jung, 2018)

Phase 3: The generated knowledge plus intuition will create wisdom. For example, when traffic is heavy on the road leading to a destination, information is provided to help a motorist avoid crowded roads and take a less-congested one. Or, work orders are delivered to ensure speedier performance by a yard truck depending on yard status. (Jung, 2018)

Phase 4: With the now wisdom plus imagination we can have a creation. For example, by simulating work implementation prior to the arrival of a container ship, one can predict the number of cranes and trucks that has to be allotted to tasks, operators to be assigned to the yard, and the severity of congestion at the gate. (Jung, 2018)


Intelligent ports are a service system for port transportation based on modern electronic information technology. This service system feature set is to provide an umbrella of information services for port components which are based upon collection, processing, release, exchange, analysis and usage for the relevant information. Intelligent ports cannot function without IoT integration, the Internet of Things poses efficient data sharing and stability of port services. (Dong et al., 2013)

IoT is the foundation technology for any intelligent port. “Sensor” technology allows port components to obtain the ability of perception. “RFID” technology allows them to speak. “M2M” can let them exchange. Lastly IoT lets all of the objects in the world interconnect. (Dong et al., 2013)

With this system in place, handling equipment, ships, containers, vehicles, and instruments, which are widely distributed in the global ports are connected to the “NET”. (Dong et al., 2013)

IoT by collecting business data essentially can eliminate manual collection errors, improve the collection efficiency and deliver instantly to every corner of the earth through the internet. (Dong et al., 2013)

The most common applications of IoT in ports at the moment are container RFID, electronic seals, port equipment condition monitoring, engineering equipment asset management, wireless automatic meter reading. (Dong et al., 2013)

Please see: Fig 4, Appendix E.

The goal for the Port of Rotterdam is to host autonomous ships by 2025. The port has paired with IBM to for a digital transformation. (Dong et al., 2013) Part of the initiative has already implemented:

4.1 IBM – Ship Shape 3D Printing

The port believes that quality industrial spare parts should always be available when they are needed and at a competitive price. The first 3D printing of its kind in the port industry. IBM cognitive IoT technology uses a robotic welding arm to apply high-quality metal layer-by-layer to create ship components such as propellers. In traditional manufacturing, this process can take 6-8 weeks, but with IBM Ship-Shape it roughly equates to a fractional 200 hours. (Campfens and Dekker, 2018)

4.2 Gemalto – IoT Solutions

Gemalto a futuristic company specializing in IoT and other cutting edge technologies is a leader in digital security. The company has created a solution that is enabling M2M connectivity for an innovative Internet-of-Things solution that monitors dynamic ocean conditions to optimize safety and efficiency in Brazilian ports. (Jung, 2018)

SISMO, this system is a real-time weather-oceanographic information system that will monitor waves, currents, water depth, temperature and salinity to improve navigation safety, streamline ship traffic and increase port productivity. (Jung, 2018)

Port workers in Sao Paulo have been using SISMO since 2013 which transmits current, level, tide, temperature, wind speed/direction and visibility data directly to their smartphones. (Tepper, 2018)

With that detailed dashboard, pilots can manoeuvre and dock precisely in nearly any conditions. Harbourmasters use the same data to fine-tune the loading of each vessel, optimizing the load for the available draft. (Tepper, 2018)


Ports all over the world have been collaborating with technology companies all over the world to improve port efficiency with time and money for their shipping clients. Any of these technologies in turn generate large amounts of data and will have to be shared with other port stakeholders.

5.1 Aquatic Drones

Inspections of ships in ports can be a long drawn out and time consuming process, which costs a lot of money. Aquatic Drones, a Dutch maritime company has created a small autonomous vehicle that provides data/information about the ship and port conditions below the waterline. These water drones essentially increase inspection speed which in turn saves time and money, while generating large amounts of data. This system is currently successfully working out of the port of Rotterdam. (Demaitre, 2018)

Please see: Fig 5, Appendix F for the aquatic drone in operation.

5.2 IBM – Weather Predictions

Relevant and accurate predicted data from the weather and water levels give companies the best times to bring their ships into a port.

Low fuel consumption is obtained when water is calm and will make for cost efficiency. The port of Rotterdam in Europe, partnered with IBM’s weather company for the use of their data. The port can now access large amounts of accurate data and can make strategic decisions with analytical tools based on this data. With the use of IoT sensors, augmented intelligence and smart weather data, the port can provide accurate water and weather data updates in real-time and predict the best times/conditions for entering or exiting the port. (Campfens and Dekker, 2018)


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Appendix A.

Table 1.  Largest Ports – Worldwide



Container Traffic in (thousand TEUs)


Shanghai, China






Shenzhen, China


Note: (TEUs) – Twenty-foot equivalent units

Appendix B.

Fig. 1. Enterprise Architecture Layers.

Appendix C.

Fig. 2. Big data market size forecasting.

Appendix D.

Fig. 3. Big Data Exploitation Stages.

Appendix E.

Fig. 4. Intelligent port.

Appendix F.

Fig. 5. Aquatic drone.




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