Next Article in Journal
Predicting Missing Values in Survey Data Using Prompt Engineering for Addressing Item Non-Response
Previous Article in Journal
Context-Driven Service Deployment Using Likelihood-Based Approach for Internet of Things Scenarios
Previous Article in Special Issue
Ontology in Hybrid Intelligence: A Concise Literature Review
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Digital Transformation in Maritime Ports: Defining Smart Gates through Process Improvement in a Portuguese Container Terminal

by
Juliana Basulo-Ribeiro
1,
Carina Pimentel
2 and
Leonor Teixeira
1,*
1
Department of Economics, Management, Industrial Engineering and Tourism (DEGEIT), Institute of Electronics and Informatics Engineering of Aveiro (IEETA), Intelligent Systems Associate Laboratory (LASI), University of Aveiro, 3810-193 Aveiro, Portugal
2
Algoritmi Research Center, Department of Production and Systems, School of Engineering, University of Minho, 4800-058 Guimarães, Portugal
*
Author to whom correspondence should be addressed.
Future Internet 2024, 16(10), 350; https://doi.org/10.3390/fi16100350
Submission received: 1 August 2024 / Revised: 8 September 2024 / Accepted: 24 September 2024 / Published: 27 September 2024
(This article belongs to the Special Issue ICT and AI in Intelligent E-systems)

Abstract

:
As the digital paradigm stimulates changes in various areas, seaports, which are fundamental to logistics and the global supply chain, are also undergoing a digital revolution, evolving into smart ports. Smart gates are essential components in this transformation, playing a vital role in increasing port efficiency. In the context of smart gates, the aim of this study is to understand how process management can serve as a catalyst for digital transformation, promoting efficiency in traffic flow and logistics. To achieve this objective, the design science research (DSR) methodology was followed, which allowed for the integration of information from several sources of requirement, encompassing both theoretical and practical aspects. The practical component took place at one of Portugal’s largest container terminals, which allowed for the integration of information from various sources. As a result, this study presents the conceptual definition of a smart gate in terms of processes, main technologies, and key performance indicators that will support the monitoring and improvement of future operations. The results provide theoretical and practical contributions: on a practical level, they present a real application of the transformation towards a smart gate, serving as a model for other ports in their digitalization; on a theoretical level, they enrich the literature with a methodology for digitalizing maritime road gates, showing how the use of process management approaches, such as the BPMN, can increase operational efficiency in container terminals.

1. Introduction

1.1. Background

As the digital paradigm causes turbulence in all areas, maritime ports, considered pillars of logistics and the global supply chain, are also embarking on a data-driven revolution. About 90% of worldwide trade is transported by sea (maritime trade), so the efficiency of these nodal points is not only desirable but essential [1]. Digitalization is redefining this scenario with the promise of unprecedented efficiency, productivity, sustainability, and transparency of business processes [2,3,4,5,6]. With this new digital paradigm comes the concept of the smart port with the “emergence” of Industry 4.0 in 2011. It represents the adoption of advanced technologies to achieve benefits, in this context, managing and improving the flow of cargo, with an impact on optimizing the supply chain [7,8].
Smart ports are a natural extension of smart cities, as both leverage digital technologies to enhance operations and promote sustainability. Similar to the way in which smart cities utilize data to create more efficient urban environments, smart ports apply these principles to optimize maritime logistics and port management. This integration plays a crucial role in minimizing environmental impacts and fostering economic development in the urban areas where ports operate, thereby enhancing the overall competitiveness and quality of life in these regions [9,10].
The smart port thus aims to maintain market competitiveness by proactively adapting and responding to the demands of world trade, which have seen an increase [8]. This sharp increase is described by Sánchez et al. [11] in their study, in which they mention that, since 2006, the growth in container ship capacity has been a defining feature of the industry, reflecting in an overall increase in the number of containers in circulation to accommodate the ever-expanding world trade. Also, to confirm this statement, according to Al-Fatlawi & Motlak [1], “Maritime transport is one of the cheapest types of transport, so international maritime trade has increased”.
In maritime logistics, particularly in smart ports, smart gates, which link port operations and external traffic, are leading a major change to improve efficiency and safety. These essential gates use advanced technology to enhance port entry and exit, improve security, and increase performance [12,13,14].
According to Heikkilä et al. [15], stakeholders tend to operate independently in digital innovation in seaports, which can result in a lack of synchronization and shared goals. Similarly, stakeholders may be hesitant to disclose information or modify their processes, which is essential for the effective integration of digital technologies [16,17]. The digitalization of port operations represents a crucial step towards operational excellence, with a focus on solving communication and information problems [18,19]. Existing communication barriers can generate operational inefficiencies that translate into lower productivity and profitability of operations [3,20]. At the same time, the information gap for decision-making, evidenced by the difficulty in accessing critical information in real-time, can be filled by the introduction of information systems. Thus, the information system is expected to facilitate the exchange of information between the different stakeholders, ensuring that decisions are supported by data collected in real-time to improve coordination and, consequently, the efficiency of port operations as a whole [21,22].
So, for Paul & Zhou [23], achieving the ideal harmony between individuals, procedures, and technology has always been essential to the success of any change and the heart of achieving business competitiveness. To effectively harness the potential of digitalization, it is essential to establish clear and transparent processes that can mitigate risks, meet market demands, and avoid bottlenecks and inefficiencies [3,24,25]. Also, overcoming inherent human resistance to new technologies is key to digital adaptation, and a learning environment is necessary for successful digitalization [18,20]. It is, therefore, essential to keep stakeholders involved right from the start of the digitalization process to overcome this resistance to change since, when people feel part of the change, they tend to contribute to it more and better [26].
So, as recent global upheavals bring about change, it is vital for ports not only to adopt digital solutions but also to improve their internal dynamics (processes and people) to take advantage of the new opportunities. This way, as ports increasingly integrate digital technology, research in this area is growing, as collaboration between ports and universities is vital to broaden knowledge within the port [2,22,27].

1.2. Study Motivation

Like airports, port areas operate as international territories and are a highly regulated sector that requires strict authorization and registration procedures for people, goods, and equipment moving through these areas [28].
Of the various opportunities for improvement within a seaport, the one addressed here is the road gate. The road gate at port terminals generally faces significant challenges that make the entry and exit of vehicles inefficient, often causing congestion [29,30]. There are several causes of inefficiency, and according to [3,30,31,32,33] they can be listed as follows:
  • Too many bureaucratic procedures;
  • Lack of infrastructure and equipment;
  • Lack of efficient communication mechanisms;
  • Lack of integration and interoperability between systems and with stakeholders;
  • Inadequate infrastructure;
  • Fluctuating driver arrival times and drivers’ failure to comply with the rules;
  • Lack of knowledge/training/awareness on the part of stakeholders regarding the use of technology.
In this context of a paradigm shift towards the digital, the implementation of innovative technological solutions, such as automated information collection systems and the intensive use of information technology, is expected to offer new ways of operating. According to [15,32,34], the following stand out:
  • Mitigating the current challenges in terms of vehicle and goods flows;
  • Promoting opportunities to improve the user experience;
  • Efficient management of resources;
  • Impacts on the sustainability of port operations.
Although the problems portrayed here are general to seaports, it was also possible to find them in a specific Portuguese seaport, which served as a case for the development of the practical component of this study. Of all Portuguese trade, about 52% is handled from this port, which is considered the largest in Portugal. With all this responsibility, the terminal needs to become more efficient and solve some inefficiencies to remain competitive in the ever-growing market. Given its significant cargo, this port has implemented a system of prior scheduling for delivery and/or pick-up services. This initiative is fundamental to improving efficiency, as it organizes time and resources better, reducing queues and speeding up logistics operations.
Thus, modernizing facilities and infrastructures and mapping and optimizing operational processes are crucial steps in transforming a seaport into a model of port efficiency and sustainability by implementing a smart gate system.
As Behdani [35] states, “detailed models and frameworks are needed to guide this development and customize the Industry 4.0 concepts to the port and shipping sector”. While there have been significant technological advancements, the current literature on smart gates often lacks a thorough analysis of their role in digital transformation. This study aims to fill this gap by developing a conceptual model of a smart gate through process management and design science research. It demonstrates how smart gates can drive digital transformation, enhancing traffic flow efficiency and logistics while also preparing for future demands in an evolving commercial environment. The practical case study conducted at one of Portugal’s largest seaports exemplifies these concepts, providing a detailed analysis of verification and authentication needs, operational stages, and sustainability indicators to ensure the viability of smart gates.

1.3. Aims and Goals

Therefore, the main objective of this study is to develop a conceptual model of a smart gate using process management and design science research and to show also how they can serve as catalysts for digital transformation, promoting efficiency in traffic flow and logistics while anticipating future needs in a constantly evolving commercial environment. To achieve this, a practical case study was carried out in one of Portugal’s largest seaports, which wanted to develop a smart gate. From the outset, the development was conducted using a process approach, with three specific objectives established:
  • Understand the verification and authentication needs at a seaport entry gate;
  • Map out the various stages of a smart gate to understand its structure and operation;
  • Analyze a set of efficiency and sustainability indicators to ensure the ongoing viability of the smart gate.
This document is structured as follows: Section 2 provides the theoretical background that supports this study; Section 3 focuses on the methods used to achieve the objectives; Section 4 describes the practical case; Section 5 offers a discussion of the findings; and, at the end, Section 6 presents the concluding remarks, including this study’s conclusions, contributions, limitations, and suggestions for future research.

2. Theoretical Background

Digital transformation is a process that involves the integration of digital technologies in all areas of a company or sector, resulting in fundamental changes in how they operate and deliver value to customers.
According to Reis et al. [36], digital transformation is a multifaceted process that involves various dimensions, as highlighted in this article. These dimensions include business models, digital businesses, sustainability, human resources, and smart cities, among others. Therefore, digital transformation not only reshapes the internal processes and structures of organizations but also extends its impact to encompass broader social and environmental aspects, aligning with emerging concepts such as smart cities and sustainable manufacturing.
This transformation is driven by the growing use of automation, which optimizes processes, minimizes human errors, and increases overall efficiency. In the realm of automation, intelligent and connected systems are employed to collect, analyze, and apply data more effectively. This technological advancement is closely related to the “smart” concept, which denotes the ability of systems and devices to communicate and operate autonomously, leveraging advanced technologies. By integrating automation into various processes, organizations can achieve higher precision, faster decision-making, and adaptive operations that enhance their competitiveness and responsiveness to market demands [15,18,32,37].
As stated by Yang et al. [38], the level of “smartness” largely relies on data-driven innovations that ensure all information related to the manufacturing process is accessible whenever and wherever needed and that it is presented in an easily understandable format across the organization and among interconnected enterprises. Similarly, in the context of smart ports and, specifically, smart gates, these innovations are crucial for transforming a traditional port into a smart port. Also, Heikkilä et al. [15] suggest that automation, sustainability, and collaboration are the key ingredients of smart ports. By leveraging digital transformation, these components enhance operational efficiency, security, and sustainability, leading to smarter, more connected operations [35].

2.1. Smart Gates

Smart gates at seaports refer to integrated gate systems that use various technologies, including sensors, cameras, biometrics, automatic identification, data analytics, and information systems, to automate and optimize entry and exit procedures [12,13,14,39]. Some of the most important features of port smart gates are detailed below:
  • Enhanced security: Smart gates significantly enhance security measures in maritime ports by utilizing advanced identification and verification techniques. Biometric systems, such as fingerprints, ensure that only authorized individuals have access to the terminal, mitigating the risk of unauthorized entry and potential security threats [13,22,39].
  • Improved efficiency and productivity: Smart gates streamline the entry and exit processes, reducing congestion and minimizing waiting times for trucks and cargo. Through automated systems and information systems, truck drivers can preregister their information, allowing for faster verification and seamless entry into the port. This optimized flow of vehicles and cargo results in improved operational efficiency, enhancing the overall productivity of the port [22,40,41].
  • Accurate data collection and analysis: Smart gates generate a wealth of data that can be collected, analyzed, and utilized for operational optimization and decision-making. By capturing information such as entry and exit times, vehicle details, and cargo manifests, ports can gain valuable insights into traffic patterns, resource allocation, and demand forecasting. This data-driven approach enables port authorities to make informed decisions, allocate resources efficiently, and proactively address potential bottlenecks or capacity constraints [14,22].
  • Integration with port systems: Smart gates can be integrated into various port management systems, enabling real-time information exchange and process automation. This integration improves coordination between different stakeholders, facilitating smoother operations, accurate documentation, and faster cargo clearance processes, optimizing traffic across different transport modes [22,40].
Smart gates have become important components of modern maritime ports, revolutionizing the way in which the process of container pick-up from trucks is conducted. With their ability to enhance security, optimize operations, and enable data-driven decision-making, smart gates play a vital role in improving efficiency, accuracy, and overall port performance [14]. As ports continue to evolve and embrace digital transformation, investing in technologies is crucial for staying competitive in the global market [16]. The emissions of pollutants from the trucks can be drastically decreased with the use of smart gates due to the organized and efficient way that the trucks can operate [13,41,42].
The focal point of numerous works in the literature revolves around the advantageous efficiency that terminals can bring, often neglecting to recognize the repercussions experienced by the stakeholders influenced by these systems [21].

2.1.1. Technologies Applied in Smart Gates

As noted above, smart gates in seaports apply various technologies to automate and optimize entry and exit processes. According to the literature, some of the main technologies commonly used in smart gates are as follows:
  • Sensors: These are used to detect the presence of vehicles and containers and monitor traffic flow at the gates. They help identify when a vehicle is approaching the entrance or exit, triggering the start of the verification and registration process [12,39].
  • Automated identification: This is performed using technologies such as RFID (radio-frequency identification) and NFC (near-field communication). Vehicles, containers, and drivers can have tags or cards equipped with these technologies, allowing for quick, contactless identification when passing through the gate. This helps to control entry and exit operations at the gate and to make the gate itself more available [12,21,22].
  • Biometric recognition: Using techniques such as fingerprint reading or facial recognition, this is used to verify the identity of drivers and other individuals entering the terminal, and this information is later stored in a database using big data technology. In this way, these systems contribute to the security of the terminal [39,40,43].
  • Cameras and OCR: High-resolution cameras and optical character recognition (OCR) systems are employed to capture images of vehicles, license plates, damage inspection, and other relevant information. These cameras can automatically read and interpret information, speeding up the registration and verification process. So, OCR can be used for the collection and verification of trucks and their driver information and other port users’ information [13,21,22]. (Although RFID reduces throughput time just as OCR does, the latter has the advantage that vehicles and containers do not need specific technologies to reduce this time [22].)
  • Data integration: Automated gate systems are connected to different port information systems, such as the port community system (PCS) and the terminal operating system (TOS), and technologies, such as OCR and RFID, to handle the flow of cargo. This integration allows the exchange of information in real-time and the automation of processes. Also, these systems could be integrated with external parties to improve the flow of information [22].
  • Data analysis and artificial intelligence: The data collected by the smart gates are analyzed using artificial intelligence and machine learning algorithms. This makes it possible to identify patterns, optimize traffic flow, predict waiting times and truck arrivals, and make informed decisions to improve operational efficiency [44,45].

2.1.2. Information Systems Applied in Smart Gates

There are at least two information systems referenced in the literature that aim to improve gate operations: the gate appointment system and the automated gate system.
Gate operational management can be improved by a gate appointment system (GAS) (or vehicle booking system, or terminal appointment system), which is an information system (IS) that can be used both to facilitate the operations of the terminal operator and the drayage company operators. The goal of this IS (on the drayage company operator’s side) is to ease the schedule of the arrival of truckers at the terminal and smooth the flow of cargo, which consequently avoids peak hours, reduces waiting times for the trucks, and reduces vehicle emissions. On the terminal operator’s side, it can facilitate the management of the terminal operations according to the appointments during each time interval. It should also be pointed out that the information on the arrival of the trucks should be updated in real-time to improve the efficiency of the operations, for example, in cases of delays due to unforeseeable external factors. Therefore, this system must allow information sharing and communication between both parties [13,21,22,42,46,47].
The automated gate system (AGS) is a technological solution that automates and optimizes gate operations and represents another IS for terminal operations. Marine terminal gates manage inbound and outbound cargo flows, and accurate recording and verification of container and vehicle movements is crucial for efficient operations. Gate information systems integrated with the terminal’s TOS (terminal operating system) play a vital role in ensuring accurate data management. The procedures involve checking containers for damage, cargo classifications, and truck driver authorizations. Technologies such as OCR and RFID are used for the automatic identification and verification of vehicle, driver, and container data [13,22,48].
These technologies work together to create an efficient and secure smart gate, streamlining entry and exit processes at seaports and improving the management of traffic flow and vehicle and cargo records [13,22,39]. Heilig & Voß [22] offer a detailed analysis of the information systems used in a smart port, including the TOS and the PCS (port community system), among others.

2.2. Process Management and Lean Management at Smart Gates

Process management is a crucial topic in the digitalization of modern operations and is also relevant for infrastructures such as smart gates in seaports. This topic covers both improving process performance and eliminating process waste, aligning perfectly with lean management principles [49,50]. By adopting lean management practices, organizations seek to maximize efficiency and reduce waste, and it is even considered a prerequisite for digital transformation [51,52,53].
Combined with processes and when applied to production, leanness is a concept that implies the analysis of information and product flows to understand the existence of waste [54]. This philosophy can then be applied to processes and information flows, giving rise to the concept of lean information management (LIM) [55,56]. This way, LIM aims to eliminate waste in information flows [57]. Also, according to Hölttä [57], it is important to understand that “information management and communication are essential parts of lean thinking” [57]. The information flow can be described as lean when the information is available at the right time, in the right quality, and without any waste [58]. This way, it is possible to conclude that leanness can be applied to all types of processes, making them more effective and efficient.
Each company has its business process, and those that can represent and model their processes can make them more efficient [56], showing the necessity of the organizations in mapping the processes.
BPM (business process management) is considered the concept according to which businesses can “operate, control, design, document and improve” processes and/or business activity flow [59,60] to manage the company’s processes. This concept can be seen to achieve a competitive advantage since it helps the company to adapt easily and continuously to change [61]. Since knowledge is a source that can make processes more efficient, and BPM allows more knowledge and information to be obtained regarding the process [61], this method (BPM) can help the processes to become more effective and efficient [62].
BPMN 2.0 (business process modeling and notation) is a standardized representation (visual) that is used as a modeling language to illustrate processes, using a diagram for that purpose [59,60].
After the individual analysis of each of the approaches—lean and BPM—it was perceived that they present common characteristics. According to Rymaszewska [63], one of the similarities that stands out is the fact that both aim at achieving improvements on a continuous basis. In other words, to reach the goal, small changes are carried out incrementally, and radical changes are not emphasized.
Matching the various references analyzed, it can be stated that BPM focuses on improving process effectiveness and efficiency [64], while the lean approach enables the achievement of the objectives of improving the organization’s performance and reducing waste and is focused on continuous improvement [65,66]. Uriona Maldonado et al. [67] describe some similarities and differences between the two. On the one hand, regarding the similarities, the following are highlighted: the focus on the customer, the focus on continuous improvement, standardization, quality improvement, cost reduction, waiting time, and increased quality. On the other hand, these approaches present well-defined differences regarding the implementation methodology, the competencies to operate each one of them, and the flow that they propose to improve, among others.
Finally, it is crucial to note that these two approaches (lean and BPM) can both be considered important in achieving increased process efficiency and effectiveness.

3. Methods

Having established the theoretical foundations of smart gates, the next section details the methodology used to apply these concepts in a practical case study.
To lead the investigation towards a proposed gate solution, a design science research (DSR) by Hevner [68,69] was adopted. This methodological approach considered information from several sources of requirements, encompassing both theoretical and practical aspects, as can be seen in Figure 1.
This study begins by characterizing the environment, identifying the application domain, and understanding the people, techniques, and systems involved. In the relevance cycle, links are made to the environment to identify and evaluate improvements. In the rigor cycle, existing knowledge is investigated to ensure innovation and practical application. In the design cycle, the construction, evaluation, and improvement of the artifact are carried out, integrating knowledge from the relevance and rigor cycles.
In the first phase, to explore the topic under study and learn about the state of the art in ports, detailed analyses were carried out based on existing knowledge. Therefore, for the theoretical requirements, the following actions were carried out:
  • Surveying the state of the art in the existing literature on smart ports and smart gates to find the best practices in this area [9];
  • Benchmarking the best international practices of seaports about the management and operation of gates [70].
On the practical requirements side, the following analyses were carried out:
  • Direct observation of current operations at the specific road terminal gate was conducted with the active participation of stakeholders, including port users, gate operators, and logistics managers. This collaborative approach allowed stakeholders to provide insights into the operational challenges they face daily, contributing to a comprehensive understanding of the current situation (AS-IS). Through these observations, critical areas needing improvement were identified based on both the researchers’ analyses and the stakeholders’ direct feedback;
  • Meetings with gate operators, drivers, and other stakeholders. These sessions were designed to gather detailed information on the problems faced, requirements, and expectations of each stakeholder group. Each session included both individual and group discussions to ensure diverse perspectives were captured. Stakeholders were actively engaged throughout the entire process, from initial discussions about the digital transformation to the final validation of proposed solutions. This approach ensured that all relevant insights and feedback were integrated into the digital transformation strategy from the beginning of the digital transformation;
  • Based on the feedback gathered from stakeholders during these meetings, problems were categorized into distinct groups to streamline the development of solutions. These categories included problems due to a lack of equipment/infrastructure, a lack of information and agile communication—lack of communication mechanisms; problems due to lack of knowledge/training/awareness, and problems of interoperability and systems integration.
From this, it was possible to understand what will apply to the study under analysis, moving on to the next phase of the DSR, the construction of the artifact and models, considering the practical case and the relevance of the research. By applying this methodology, it was possible to realize that what was reported in the literature was reflected in the reality of this specific port. This multifaceted approach will ensure that digital implementation is not only viable but also a transformative force in today’s logistics landscape.

4. Results

Having understood the theoretical context of smart gate technologies, it is essential to apply these concepts to a real case study to observe their practical implications. In the next case study, a port terminal in Portugal is examined, where these technologies have been implemented to assess their impacts on efficiency and safety.
This chapter will present the results that will culminate in a smart gate model for the entry and exit processes of a container terminal, in line with the three specific objectives defined, based on a case carried out in one of Portugal’s largest seaport container terminals. In addition to the critical components that will determine the key phases of the process representative of the smart gate’s activities and operations, the main coupled technologies responsible for capturing and collecting data in operations will also be explored and defined. This study ends with some proposals for indicators that will ensure the sustainability of the new smart gate operating model.
Before detailing the TO-BE process (the desired or ideal state of the process), we will first present the AS-IS process (the current state of the process without any improvements) (see Table 1).
Figure 2 illustrates the different locations where the AS-IS process for entering and leaving the terminal is carried out: documentation room (container and lorry access control point), security area (people access control point), entry and exit gates (and their respective barrier and gateway), and road access to the gates.
Based on the limitations identified, such as manual checks and inadequate integration systems, the need for a more automated and efficient system is evident. The following explains the TO-BE process and how the essential technological elements and strategic control points can transform these processes, ensuring greater efficiency, security, and better data flow management in the terminal.

4.1. Critical Components and Checkpoints of a Smart Gate

So, to maintain high standards of efficiency and competitiveness, ports face the critical challenge of managing the vast flow of data and information generated throughout the logistics chain. This task impacts the efficient collection and storage of these data and their analysis and interpretation to enhance decision-making, optimize operations, and improve communication between various stakeholders. The ability to transform these data into actionable insights is key to maintaining the agility and adaptability of ports in a dynamic and highly competitive global environment and will be achieved through the adoption of technology.
With the implementation of technology, the interaction between humans and machines has been minimized, reducing the possibility of errors and improving the safety of both workers and terminal operators.
Terminal gates play a crucial role as control points for registering and identifying entities accessing or leaving controlled areas. Due to the growth in the size of ships and the increase in container movement, improving the efficiency and security of these gates has become a key tactic for terminal management. It is, therefore, necessary to make the gate IN and gate OUT process easier and faster.
From what can be concluded from a search of the literature and the port under study, there are at least five critical components when it comes to automating a terminal’s gates (see Table 2).
As part of the transition to digital in the port under study, the strategy implemented involved restructuring the gate and dividing it into four different control points. This initiative aims to decentralize operations to minimize interruptions, queues, and bottlenecks, ensuring a faster, more efficient flow into the terminal. These checkpoints, where data associated with the terminal entry are introduced and verified, serve as preliminary checks before arriving at the main gate, which provides access to the international zone. They aim to implement multiple layers of security in data processing and verification, thereby ensuring that no unauthorized entries into the terminal occur. This approach highlights the importance of combining technological innovation and process optimization in the continuous improvement of operations.
Table 3 summarizes the four checkpoints, detailing the hardware required and the activities carried out at each one. This table shows the application of the technologies discussed in the theoretical section (2.1.1) of this practical case study.

4.2. Smart Gate Processes

Considering the need for the controls presented in the previous chapter (Table 3), a smart gate can be organized into four verification stages, culminating in a final verification before access to the international zone. The transportation, which justifies the main needs for terminal operations, can be used for three different purposes:
  • Collection of a particular full container;
  • Collection of empty containers (if the customer has a reservation of empty containers at the terminal);
  • Delivering a particular container, full or empty.
The process starts with the need for an entity to enter the terminal, with the hauler/entity requesting access authorization to the terminal for his/her driver. There are two options for delivering or collecting an empty or full container: (i) prior booking of the service, booking the delivery or collection service at GAS, or (ii) no prior booking. In either case, the vehicle driver goes to the terminal and, when everything is in order, goes to the boarding gate or, if there is a problem, returns to the public highway. After entering the terminal, the service is processed inside the terminal. At the end of this process, the vehicle goes to the exit gate to leave the terminal, and the process is complete.
Going into the specifics of the process of entering the terminal, it begins, as mentioned above, with the need for an entity to deliver/collect the goods and with the hauler/driver requesting authorization to access the terminal for his/her lorry driver and making or not making a prior appointment for the service. The driver then heads for the terminal and then to the four different checkpoints in the case of normal lorries. For large exceptional vehicles, access is via a parallel road. Non-exceptional lorries go to checkpoint 1 without stopping and then to checkpoint 2, stopping at the kiosk. Depending on his/her situation, the driver can have two different outcomes: (i) go to checkpoint 4 if everything is fine, or (ii) go to checkpoint 3 if he/she cannot solve the problem in the short term. At checkpoint 3, if the driver manages to resolve his/her situation, he/she should proceed to checkpoint 2; if not, he/she should return to the road. In the end, when everything is in order, the driver goes to gate IN and enters the terminal. Thus, the driver and his/her cargo will only enter the terminal when three conditions are met: container, driver, and vehicle are identified and authorized. Figure 3 illustrates the terminal access process.
After the general explanation of the process, the input process will now be detailed. Firstly, Figure 4 illustrates the layout of the proposal for the first checks. This detailed explanation will be divided into four checkpoints, and each of these parts is explained in this subsection.

4.2.1. Checkpoint 1—Non-Stop Station for Checking Vehicle Type and Reading Truck/Container/Galley Data Automatically

The driver goes to the terminal and, depending on the type of vehicle/load identified through a recognition system (OCR), the driver must follow the route indicated for the purpose. If the driver has an authorized heavy goods vehicle, he/she goes to checkpoint 2.
This phase also involves the automatic reading and collection of (i) truck and galley registration using LPR and (ii) container data through ACCR.
By collecting these data and comparing them with the information in the schedules, the system can validate the existence or non-existence of a schedule. After this check, the driver will be told which route to take (it differs according to whether he/she has an appointment or not):
  • If the driver has an appointment, there will be signs directing him/her to the left-hand lanes;
  • If the driver does not have an appointment, he/she goes to those on the right.
In addition, information about the request to weigh the goods will be identified at checkpoint 1, and if there is no prior request to weigh the goods, they will proceed to the lane without a weighbridge; otherwise, the driver will proceed to the lane with a weighbridge.

4.2.2. Checkpoint 2—Container, Vehicle, and Driver Identification

As mentioned above, drivers will take different routes depending on whether they have a prior appointment or not. Regardless of the situation, in both alternatives (lanes for scheduled and unscheduled services), a lane equipped with scales is essential, both for those who are marked and for those who are not.
At checkpoint 2, the driver initially crosses a barrier, which is open by default, and data are collected: (i) truck registration using LPR; (ii) container data (if available) with ACCR; and (iii) container status records, checking the container for damage (images of the container from both sides and the top) accessed by ADDR.
After collecting data while the vehicle is in motion, the first barrier of checkpoint 2 closes, preventing a second vehicle from entering the control area. Subsequently, the driver parks next to a kiosk (hardware: TOUCH HMI—touch screen and intercom) where the following takes place:
  • The driver’s identification (if they have a card and a valid entry permit) using a card and biometric identification;
  • Verification of the logistics service (if they have a valid prior appointment) through hardware: PIN or QR code (laser scanner);
  • The confirmation of the service data by the driver;
  • Weighing of the cargo (if they have not done so before going to the terminal) by means of a weighbridge);
  • If necessary, the help mechanism can be activated.
Based on this information, the driver will be told where to go next, whether to checkpoint 3 or checkpoint 4. If the appointment and authorization are valid, the driver receives information on his/her phone with the location where he/she should go and the drop-off/pick-up points for the container(s) inside the terminal. If the conditions for entering the terminal are not met, then the driver will not receive any message, and he/she will be guided to park/checkpoint 3. Figure 5 illustrates the checkpoint 2 process.

4.2.3. Checkpoint 3—Solve Anomalous Situations

This is where anomalous situations are resolved to validate the driver’s entry into the terminal. This stop happens, among other unforeseen scenarios, in the event of the following:
  • The appointment and/or authorizations (container/driver) not being complete to enter the terminal;
  • The driver has an appointment but arrived early;
  • Scheduling has a problem;
  • There has been an error in reading the data from the truck/galley/container at checkpoint 1;
  • The driver’s identification is not operational;
  • The driver does not have an appointment.
In either situation, if a driver needs help, a terminal operator can be “called” to help remotely, via the intercom, or in person.
Once the situation(s) that led the driver to checkpoint 3 have been dealt with, if everything is valid to enter the terminal, then the driver can return to checkpoint 2, carrying out all the operations there. Between checkpoint 3 and checkpoint 2, there will be an LPR that allows the process of checkpoint 3 to be closed. If something does not comply, then the driver can be routed to the public road, passing through an LPR that will allow this driver’s process to be closed. Figure 6 illustrates the checkpoint 3 process.

4.2.4. Checkpoint 4—Ensure That Vehicles Have Permission to Enter the Terminal

Before the driver heads to gate IN (from which he/she enters the international zone), he/she passes checkpoint 4, where there are barriers with LPR recognition, which will ensure that vehicles that did not obtain permission at checkpoint 2 and were directed to checkpoint 3 (or to the public highway) do not go to the terminal.
After these four checkpoints, it is essential to designate specific locations for releasing and securing the containers from the trucks. To ensure safety and efficiency in these processes, it is crucial to establish clear procedures and instruct drivers in detail to minimize risks and ensure that journeys and processes run smoothly.

4.2.5. Gate IN—Where the International Zone Starts

When the driver arrives at the entry gate, all the paperwork has already been taken care of, and all that is left to do is to recognize the truck’s license plate, open the gate, and the driver enters the terminal. If something is not working properly, the driver should use the intercom and ask a remote operator for help if necessary.
At this point, when the truck’s license plate is read, the work inside the terminal (P-check) is triggered since the truck’s license plate makes it possible to identify the container and the logistics service (Figure 7).

4.2.6. Gate OUT—To Leave the International Zone

In the smart gate, the gate out will be divided into two parts. In the first part, information will be collected automatically, without the need to stop. In the second part, the driver will have to stop to identify himself/herself and the logistics service.
In the first phase, as the lorry passes through the OCR exit gantry, automatic recognition of the container numbers and the vehicle’s license plate is carried out to confirm that the container(s) and the vehicle match. Photographs are also taken of the container(s) to detect possible damage.
In the second phase, the driver must enter the PIN/QR code of the booking he/she received to enter the terminal, triggering the system to send the information (exit slip) to the driver. The drivers will also have to identify themselves in the same way as they did at checkpoint 2. If the driver is carrying an empty container and needs to buy a seal, there will be an automatic stamp dispenser at this point (see Figure 8).

4.3. Some KPIs to Measure Smart Gate Efficiency

Key performance indicators (KPIs) are essential for assessing the efficiency and effectiveness of operational processes in any logistics terminal, ensuring its future sustainability, with the capacity to evaluate and improve (see Table 4). The system to be developed must show the quality of the service and be able to measure the times and efficiency of the gate service.
These indicators will be essential to understand who should be penalized for failing to comply with good practices.
After detailing the processes and improvements expected with the implementation of the smart gate system, Table 5 shows a comparison between the AS-IS (current) and TO-BE (proposed) states. This comparison highlights the limitations of the current processes and demonstrates how the proposed innovations aim to overcome these challenges, increasing operational efficiency, safety, and customer satisfaction at the terminal.

5. Discussion

In the context of optimizing port terminals, smart gates have emerged as a crucial part, as identified by Henríquez et al. [14]. These technologies not only modernize access to the terminal through automation but are also fundamental in improving the efficiency and safety of port processes, as these areas are considered international by Moszyk et al. [28]. The implementation of smart gates makes it possible to significantly reduce waiting times by contributing to the uninterrupted flow of cargo and vehicles, as well as making information available in real-time for better decision-making. Although the initial investment in such technologies can be considerable, the long-term benefits will justify this adoption through improved productivity rates and customer satisfaction in terminals, as highlighted by the literature [20].
Our study’s findings on the implementation and impact of smart gates are closely aligned with existing research highlighting the benefits of digital transformation in port operations. For instance, the literature emphasizes the role of automation and advanced information systems in enhancing port efficiency and reducing operational costs through real-time data management and automated processes [22]. Similarly, our results demonstrate significant improvements in both efficiency and safety at the port terminal following the introduction of smart gates, particularly in terms of reduced congestion and faster processing times. This is consistent with the observations of Henríquez et al. [14], who note that the use of digital technologies in ports leads to improved operational flow and heightened security measures.
This proposal was based on process mapping with the TO-BE solution of a smart gate while presenting the necessary and most appropriate technologies at each stage of the process. Specifically, this project is grounded in a real case in one of Portugal’s largest container shipping ports, aiming to meet the ever-increasing demands of world trade and transform it into an increasingly sustainable port. As mentioned by several authors [3,24,25], it is essential to make processes clear and avoid inefficiencies to meet market demand.
Building on this case study, this research also fulfills the need identified by Behdani [35] for detailed models to apply Industry 4.0 concepts to the port sector. Unlike the current literature, which lacks in-depth analyses of the roles of smart gates, this work develops a conceptual model that demonstrates how smart gates can improve logistical efficiency and prepare ports for future demands, as well as providing a methodology to guide this progress. The practical study carried out in a major Portuguese port provides a detailed analysis of operational and sustainability needs, demonstrating the viability of smart gates in port digital transformation.
As discussed, it can be concluded that the role of processes in defining and implementing smart gates cannot be underestimated, especially in a context where every step must be planned and executed (as seaports are considered highly regulated international zones). This study shows that process management is a fundamental component in the context of digital transformation and is an indispensable pillar for the success of this change.
It should be noted that collaboration between the various players/stakeholders appears to be a vital element in the success of the port’s digital transformation project under study, recognizing that the effectiveness of implementation and operational excellence continue to depend on people and synergy between teams, and not just on technological merit. In line with this thinking, stakeholders were actively involved in the survey of requirements and identification of problems during the port’s modernization process, which is essential, as referred to in the literature [26]. Thus, validating the processes with stakeholders not only guarantees and supports the alignment and buy-in of all parties involved but also provides a crucial opportunity to identify and eliminate points of inefficiency. This step is key to ensuring that the proposed system not only meets current needs but is also scalable and adaptable to future needs. In addition, the use of visual representations of the processes facilitates stakeholder understanding and involvement, allowing for a clear and transparent view of the current state and the potential impact of the proposed changes.
Although this research was developed within the framework of a specific port, the insights and solutions developed could have a wider impact, suggesting that this proposed smart gate solution could be adapted and implemented in other ports with similar characteristics. This generalization is crucial, especially in cases involving advance scheduling, making it possible to improve the efficiency and sustainability of ports in a global context.
While this study focuses on a specific port in Portugal, future research could explore several areas to broaden the understanding of smart gates. Comparative studies across different ports could provide insights into the factors influencing technological implementation success in varied contexts. Longitudinal studies could track the long-term impacts of digital transformation on operational efficiency and sustainability. Additionally, investigating human factors, such as resistance to change and training needs, could improve the adoption of new technologies. These research directions could further enhance academic knowledge and guide ports in their digitalization efforts.

Practical Recommendations for Digital Transformation in Ports

To build on the findings of this study and address some of the challenges identified, it is important to provide practical recommendations for port managers, policymakers, and researchers. The following table (Table 6) outlines key strategies for overcoming obstacles such as stakeholder resistance, integrating new technologies, and ensuring successful digital transformation in ports.

6. Final Remarks

6.1. Conclusions

In this study, technological solutions and optimized practices are proposed to increase the terminal’s efficiency, safety, and operational sustainability. To this end, a comprehensive methodological approach was followed based on direct observation, interviews with key stakeholders, categorization of problems, a literature review on smart gates, and benchmarking of best practices in seaports worldwide. This resulted in the main technologies used in smart gates being analyzed in detail. This methodology contributed to the development of a proposal to improve the entrance and exit of the container terminal at the port under study.
As such, the adoption of process optimization strategies by organizations is constantly growing, using process modeling through the BPM notation. This method is not limited to mapping processes but also extends to digitizing them and eliminating/mitigating waste through the lean philosophy. In other words, the AS-IS model (mapping the current state of operations) makes it possible to identify problems and inefficiencies in the process to take advantage of opportunities for improvement and ultimately map the TO-BE model (state of operations to be achieved) in line with these improvements.
The new solution includes the implementation of advanced technologies, such as sensors, automatic identification, biometric recognition, and data integration, among others, all of which are essential for transforming the port’s operations into a more agile, secure, and environmentally sustainable system.
Alongside the TO-BE model proposal, it is recognized that the long-term vision for the port under study is aimed not only at immediate technological progress but also at preparing the terminal to meet the growing increase in demand. With this evolution, it is hoped that, by 2030, the terminal will be capable of doubling the volume of peak heavy goods vehicles per hour, reflecting not only an expansion in capacity but also an increase in operational efficiency.
This shift to a digitalized gate will bring challenges, not least people’s resistance to change and the need for training. As mentioned above, alongside technology and processes, it is also necessary to look at the aspects involving people. Therefore, the effective implementation of these innovations requires strong collaboration between the various stakeholders and a cultural change to ensure the adoption of the proposed new practices.
To guarantee a return on significant investments in digital transformation, ports can explore various monetization strategies. By taking advantage of the data generated by digitized operations, ports can offer value-added services such as predictive maintenance, optimized routing, and dynamic pricing models for berthing and storage. In addition, increased efficiency and reduced operating costs can lead to competitive prices, attracting more business and partnerships. The introduction of new digital services, such as real-time tracking and automated reporting, can also generate new revenue streams. By monetizing these digital advances, ports not only recoup their investments but also position themselves as leaders in innovation and sustainability in the maritime sector.
From a cause–effect analysis and considering the contributions of the different areas involved in this study in the search for operational efficiency or simply the elimination of waste in a seaport road terminal, Figure 9 systematizes the main areas of intervention, from the purpose to the solution. Areas such as lean management, processes, people, and technological innovation feature prominently as important contributions to the solution. Thus, each of the branches in Figure 9, represented by an Ishikawa diagram, shows a cause coming from an area: in lean management, the emphasis is on continuous improvement and eliminating/mitigating waste; in processes, BPMN is highlighted as a vital tool for mapping, managing and understanding processes, helping to anticipate results and mitigate risks; in technological innovation, technology and automation stand out, making it possible to manage and analyze data used to drive strategic decisions based on information updated in real-time; in the area of people, their involvement and collaboration, their training and qualification, and the promotion of a strong organizational culture are considered crucial to achieving operational efficiency. The benefits expected from these aspects are listed on the right-hand side of Figure 9. Therefore, these aspects position the organization to face future challenges and maintain its competitive edge in the market.

6.2. Contributions and Implications

This study makes significant contributions both in theory and practice, as well as policymaking.
  • Practical Contributions
On a practical level, this research provides a comprehensive case study on the digitalization of a port gate, transforming it into a smart gate. This transformation serves as a valuable reference for other ports embarking on their own digital transformation journeys. By outlining the step-by-step process of implementing smart gates, from the identification of operational requirements to the integration of various technologies such as sensors, automatic identification, and data analytics, this study offers a blueprint that can be adapted to different contexts and needs. The findings demonstrate the tangible benefits of smart gates, such as enhanced security, improved efficiency, reduced emissions, and optimized resource management. These outcomes can serve as benchmarks for other ports aiming to enhance their operations through digital innovation.
  • Theoretical Contributions
On a theoretical level, this study advances research in the field of port management and digital transformation. It contributes to the literature by proposing a novel framework for the digitalization of road gates, focusing on methodologies that enhance operational efficiency and data-driven decision-making. This study identifies and fills a gap in the existing literature with a methodology to guide this development and customize the Industry 4.0 concepts to the port and shipping sector. By bridging this gap, this research not only enriches academic discourse but also lays the groundwork for future studies that may explore similar technological transformations in other sectors or geographical regions.
  • Policy Implications
This study highlights the importance of policies that encourage innovation and digital transformation in ports. The creation of a regulatory framework that standardizes the integration of technologies in different ports is essential to ensure compatibility and best practices. In addition, policies should address data privacy and cybersecurity, considering the sensitivity of data collected by smart gates, such as biometric information. Finally, environmental policies that incentivize the reduction of emissions and the efficient use of energy through digital technologies can support sustainability goals in the maritime sector.
  • Global Implications
Furthermore, the findings have global implications for the adoption of digital technologies in port operations. By demonstrating the successful implementation of smart gates in a specific context, this study provides evidence that such technologies can be adapted and scaled to fit the needs of ports worldwide. The global standardization of smart gate technologies could facilitate smoother international trade by enhancing the interoperability of port systems across different countries and regions. This would not only streamline logistics but also foster greater collaboration and information sharing among global ports, leading to improved efficiency and security in international maritime operations.

6.3. Limitations and Future Work

In addition, for future work, it will also be essential to analyze the automatic reading of container seal numbers, a critical component in the definition of a smart gate. These are crucial for guaranteeing the integrity and security of the cargo being transported and are used to check whether a container has been opened and/or modified during transport. From what we can gather from technology providers, reading the container’s seal number is still a work in progress, as cameras have difficulty accurately reading seal numbers that are small, not at an ideal angle, or in sub-optimal lighting conditions.
This study focussed on process management and the integration of technology as an opportunity to improve processes. As this study progressed, the need arose to study the critical role of people in any innovation process such as this, an essential component of the trilogy mentioned above—technology, processes, and people [23]. One of the biggest challenges of digital transformation is resistance to change on the part of people, and this is one of the problems that currently exist at the terminal under study (a problem due to lack of knowledge/training/awareness). The intention, therefore, was to implement a strategy in the short term at the current gate facilities of the terminal under study to reinforce the need for and benefits of using technologies and the new digitized process by means of an awareness-raising study. Implementing this measure will reap immediate benefits and will contribute to the success of the future motorway gate. Therefore, for it to serve as a holistic and replicable model for other ports seeking modernization and operational optimization in line with global digitalization and sustainability trends, a paradigm shift should be encouraged, which could involve awareness-raising actions with new practices for using and providing services at the Portuguese port under study.

Author Contributions

Conceptualization, J.B.-R.; methodology, J.B.-R. and L.T.; validation, L.T.; formal analysis, J.B.-R., C.P. and L.T.; writing—original draft preparation, J.B.-R.; writing—review and editing, J.B.-R., C.P. and L.T.; supervision, C.P. and L.T.; funding acquisition, J.B.-R. and L.T. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the PRR—Recovery and Resilience Plan and by the NextGenerationEU funds at Universidade de Aveiro, through the scope of the Agenda for Business Innovation “NEXUS: Pacto de Inovação—Transição Verde e Digital para Transportes, Logística e Mobilidade” (Project no. 53 with the application C645112083-00000059). This work was also supported by the research unit IEETA (UIDB/00127/2020), funded by national funds through FCT—Funda̧cão para a Ciência e a Tecnologia.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy issues.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Al-Fatlawi, H.A.; Motlak, H.J. Design and Implementation of Smart Port Gate System Based on the Internet of Things. In Proceedings of the 2023 International Conference on Information Technology, Applied Mathematics and Statistics (ICITAMS), Dewaniyah, Iraq, 20–22 March 2023; Institute of Electrical and Electronics Engineers Inc.: Piscataway, NJ, USA, 2023; pp. 291–296. [Google Scholar] [CrossRef]
  2. Jović, M.; Tijan, E.; Brčić, D.; Pucihar, A. Digitalization in Maritime Transport and Seaports: Bibliometric, Content and Thematic Analysis. J. Mar. Sci. Eng. 2022, 10, 486. [Google Scholar] [CrossRef]
  3. Almeida, F. Challenges in the Digital Transformation of Ports. Businesses 2023, 3, 548–568. [Google Scholar] [CrossRef]
  4. Othman, A.; El-Gazzar, S.; Knez, M. A Framework for Adopting a Sustainable Smart Sea Port Index. Sustainability 2022, 14, 4551. [Google Scholar] [CrossRef]
  5. Neugebauer, J.; Heilig, L.; Voß, S. Digital Twins in the Context of Seaports and Terminal Facilities. Flex. Serv. Manuf. J. 2024, 1–97. [Google Scholar] [CrossRef]
  6. El Idrissi, A.; Haidine, A.; Aqqal, A.; Dahbi, A. Deployment Strategies of Mobile Networks for Internet-of-Things in Smart Maritime Ports. In Proceedings of the 2022 11th International Symposium on Signal, Image, Video and Communications (ISIVC), El Jadida, Morocco, 18–20 May 2022; pp. 5–10. [Google Scholar] [CrossRef]
  7. Zadeh, S.B.I.; Perez, M.D.E.; López-Gutiérrez, J.-S.; Fernández-Sánchez, G. Optimizing Smart Energy Infrastructure in Smart Ports: A Systematic Scoping Review of Carbon Footprint Reduction. J. Mar. Sci. Eng. 2023, 11, 1921. [Google Scholar] [CrossRef]
  8. Paraskevas, A.; Madas, M.; Zeimpekis, V.; Fouskas, K. Smart Ports in Industry 4.0: A Systematic Literature Review. Logistics 2024, 8, 28. [Google Scholar] [CrossRef]
  9. Basulo-Ribeiro, J.; Teixeira, L. Industry 4.0 supporting logistics towards smart ports: Benefits, challenges and trends based on a systematic literature review. J. Ind. Eng. Manag. 2024, 17, 492–515. [Google Scholar] [CrossRef]
  10. Kolotouchkina, O.; Barroso, C.L.; Sánchez, J.L.M. Smart cities, the digital divide, and people with disabilities. Cities 2022, 123, 103613. [Google Scholar] [CrossRef]
  11. Sánchez, R.J.; Perrotti, D.E.; Fort, A.G.P. Looking into the future ten years later: Big full containerships and their arrival to south American ports. J. Shipp. Trade 2021, 6, 2. [Google Scholar] [CrossRef]
  12. Ahmad, R.W.; Hasan, H.; Jayaraman, R.; Salah, K.; Omar, M. Blockchain applications and architectures for port operations and logistics management. Res. Transp. Bus. Manag. 2021, 41, 100620. [Google Scholar] [CrossRef]
  13. AlKheder, S.; Naif, D.; Musaed, D.; Al Shrekah, S.; Al Rshaid, M.; Anzi, N.A.; Baqer, I. Maritime transport management in Kuwait toward an automated port logistical city. Clean. Logist. Supply Chain 2022, 3, 100031. [Google Scholar] [CrossRef]
  14. Henríquez, R.; de Osés, F.X.M.; Marín, J.E.M. Technological drivers of seaports’ business model innovation: An exploratory case study on the port of Barcelona. Res. Transp. Bus. Manag. 2022, 43, 100803. [Google Scholar] [CrossRef]
  15. Heikkilä, M.; Saarni, J.; Saurama, A. Innovation in Smart Ports: Future Directions of Digitalization in Container Ports. J. Mar. Sci. Eng. 2022, 10, 1925. [Google Scholar] [CrossRef]
  16. Boullauazan, Y.; Sys, C.; Vanelslander, T. Developing and demonstrating a maturity model for smart ports. Marit. Policy Manag. 2022, 50, 447–465. [Google Scholar] [CrossRef]
  17. Acciaro, M.; Sys, C. Innovation in the maritime sector: Aligning strategy with outcomes. Marit. Policy Manag. 2020, 47, 1045–1063. [Google Scholar] [CrossRef]
  18. Rajabi, A.; Saryazdi, A.K.; Belfkih, A.; Duvallet, C. Towards Smart Port: An Application of AIS Data. In Proceedings of the 2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/SmartCity/DSS), Exeter, UK, 28–30 June 2018; pp. 1414–1421. [Google Scholar] [CrossRef]
  19. Yau, K.-L.A.; Peng, S.; Qadir, J.; Low, Y.-C.; Ling, M.H. Towards smart port infrastructures: Enhancing port activities using information and communications technology. IEEE Access 2020, 8, 83387–83404. [Google Scholar] [CrossRef]
  20. Tijan, E.; Jović, M.; Aksentijević, S.; Pucihar, A. Digital transformation in the maritime transport sector. Technol. Forecast. Soc. Chang. 2021, 170, 120879. [Google Scholar] [CrossRef]
  21. Neagoe, M.; Taskhiri, M.S.; Nguyen, H.O.; Turner, P. Exploring the Role of Information Systems in Mitigating Gate Con-gestion Using Simulation: Theory and Practice at a Bulk Export Terminal Gate. In Production Management for Data-Driven, Intelligent, Collaborative, and Sustainable Manufacturing. APMS 2018; IFIP Advances in Information and Communication Technology; Springer: Cham, Switzerland, 2018; Volume 535. [Google Scholar] [CrossRef]
  22. Heilig, L.; Voß, S. Information systems in seaports: A categorization and overview. Inf. Technol. Manag. 2016, 18, 179–201. [Google Scholar] [CrossRef]
  23. Paul, J.; Zhou, Y. How to build sustainable innovation capability in supply chain management. Int. J. Bus. Glob. 2017, 19, 456–476. [Google Scholar] [CrossRef]
  24. Rodrigue, J.-P.; Notteboom, T.; Pallis, A. Chapter 2.4—The Digital Transformation of Ports. In Port Economics, Management and Policy; Routledge: London, UK, 2022. [Google Scholar]
  25. Brunila, O.-P.; Kunnaala-Hyrkki, V.; Inkinen, T. Hindrances in port digitalization? Identifying problems in adoption and implementation. Eur. Transp. Res. Rev. 2021, 13, 62. [Google Scholar] [CrossRef]
  26. Wang, D.; Chen, S. RETRACTED: Digital Transformation and Enterprise Resilience: Evidence from China. Sustainability 2022, 14, 14218. [Google Scholar] [CrossRef]
  27. Min, H. Developing a smart port architecture and essential elements in the era of Industry 4. Marit. Econ. Logist. 2022, 24, 189–207. [Google Scholar] [CrossRef]
  28. Moszyk, K.; Deja, M.; Dobrzynski, M. Automation of the road gate operations process at the container terminal—A case study of DCT Gdańsk SA. Sustainability 2021, 13, 6291. [Google Scholar] [CrossRef]
  29. Rahman, R. Five Problems with Truck Congestion at Ports and How to Solve Them. Port Technology Internation. 2023. Available online: https://www.porttechnology.org/news/five-problems-with-truck-congestion-at-ports-and-how-to-solve-them/ (accessed on 31 July 2024).
  30. Vukić, L.; Lai, K.-H. Acute port congestion and emissions exceedances as an impact of COVID-19 outcome: The case of San Pedro Bay ports. J. Shipp. Trade 2022, 7, 25. [Google Scholar] [CrossRef]
  31. Nikghadam, S.; Molkenboer, K.F.; Tavasszy, L.; Rezaei, J. Information sharing to mitigate delays in port: The case of the Port of Rotterdam. Marit. Econ. Logist. 2021, 25, 576–601. [Google Scholar] [CrossRef]
  32. Belmoukari, B.; Audy, J.-F.; Forget, P. Smart port: A systematic literature review. Eur. Transp. Res. Rev. 2023, 15, 4. [Google Scholar] [CrossRef]
  33. Gui, D.; Wang, H.; Yu, M. Risk Assessment of Port Congestion Risk during the COVID-19 Pandemic. J. Mar. Sci. Eng. 2022, 10, 150. [Google Scholar] [CrossRef]
  34. Othman, A.; El Gazzar, S.; Knez, M. Investigating the Influences of Smart Port Practices and Technology Employment on Port Sustainable Performance: The Egypt Case. Sustainability 2022, 14, 14014. [Google Scholar] [CrossRef]
  35. Behdani, B. Port 4.0: A conceptual model for smart port digitalization. Transp. Res. Procedia 2023, 74, 346–353. [Google Scholar] [CrossRef]
  36. Reis, J.; Melão, N. Digital transformation: A meta-review and guidelines for future research. Heliyon 2023, 9, e12834. [Google Scholar] [CrossRef]
  37. Douaioui, K.; Fri, M.; Mabrouki, C.; Semma, E.A. Smart port: Design and perspectives. In Proceedings of the 2018 4th International Conference on Logistics Operations Management (GOL), Le Havre, France, 10–12 April 2018; pp. 1–6. [Google Scholar] [CrossRef]
  38. Yang, H.; Kumara, S.; Bukkapatnam, S.T.; Tsung, F. The internet of things for smart manufacturing: A review. IISE Trans. 2019, 51, 1190–1216. [Google Scholar] [CrossRef]
  39. D’amico, G.; Szopik-Depczyńska, K.; Dembińska, I.; Ioppolo, G. Smart and sustainable logistics of Port cities: A framework for comprehending enabling factors, domains and goals. Sustain. Cities Soc. 2021, 69, 102801. [Google Scholar] [CrossRef]
  40. Jovic, M.; Kavran, N.; Aksentijevic, S.; Tijan, E. The transition of Croatian seaports into smart ports. In Proceedings of the 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019, Opatija, Croatia, 20–24 May 2019; pp. 1386–1390. [Google Scholar] [CrossRef]
  41. Jin, Z.; Lin, X.; Zang, L.; Liu, W.; Xiao, X. Lane allocation optimization in container seaport gate system considering carbon emissions. Sustainability 2021, 13, 3628. [Google Scholar] [CrossRef]
  42. Chen, R.; Meng, Q.; Jia, P. Container port drayage operations and management: Past and future. Transp. Res. Part E Logist. Transp. Rev. 2022, 159, 102633. [Google Scholar] [CrossRef]
  43. Mazzarino, M.; Braidotti, L.; Cociancich, M.; Bottin, G.; La Monaca, U.; Bertagna, S.; Marinò, A.; Bucci, V. On the Digitalisation Processes in the Adriatic Region. In Nautical and Maritime Culture, from the Past to the Future; Progress in Marine Science and Technology; IOS Press: Amsterdam, The Netherlands, 2019; Volume 3, pp. 180–190. [Google Scholar] [CrossRef]
  44. Hill, A.; Böse, J.W. A decision support system for improved resource planning and truck routing at logistic nodes. Inf. Technol. Manag. 2016, 18, 241–251. [Google Scholar] [CrossRef]
  45. E Mekkaoui, S.; Benabbou, L.; Berrado, A. A systematic literature review of machine learning applications for port’s operations. In Proceedings of the 2020 5th International Conference on Logistics Operations Management (GOL), Virtual, 28–30 October 2020; pp. 1–5. [Google Scholar] [CrossRef]
  46. Giuliano, G.; O’brien, T. Reducing port-related truck emissions: The terminal gate appointment system at the Ports of Los Angeles and Long Beach. Transp. Res. Part D Transp. Environ. 2007, 12, 460–473. [Google Scholar] [CrossRef]
  47. Zhao, W.; Goodchild, A.V. The impact of truck arrival information on container terminal rehandling. Transp. Res. Part E Logist. Transp. Rev. 2010, 46, 327–343. [Google Scholar] [CrossRef]
  48. Kashav, V.; Garg, C.P.; Kumar, R. Ranking the strategies to overcome the barriers of the maritime supply chain (MSC) of containerized freight under fuzzy environment. Ann. Oper. Res. 2021, 324, 1223–1268. [Google Scholar] [CrossRef]
  49. Chinosi, M.; Trombetta, A. BPMN: An introduction to the standard. Comput. Stand. Interfaces 2012, 34, 124–134. [Google Scholar] [CrossRef]
  50. Bevilacqua, M.; Ciarapica, F.E.; Paciarotti, C. Implementing lean information management: The case study of an automotive company. Prod. Plan. Control 2014, 26, 753–768. [Google Scholar] [CrossRef]
  51. Tripathi, V.; Chattopadhyaya, S.; Mukhopadhyay, A.K.; Sharma, S.; Li, C.; Di Bona, G. A Sustainable Methodology Using Lean and Smart Manufacturing for the Cleaner Production of Shop Floor Management in Industry 4. Mathematics 2022, 10, 347. [Google Scholar] [CrossRef]
  52. Marsikova, K.; Sirova, E. Optimization of selected processes in a company with the support of the lean concept. MM Sci. J. 2018, 2018, 2300–2305. [Google Scholar] [CrossRef]
  53. Mayr, A.; Weigelt, M.; Kühl, A.; Grimm, S.; Erll, A.; Potzel, M.; Franke, J. Lean 4.0—A conceptual conjunction of lean management and Industry 4.0. Procedia CIRP 2018, 72, 622–628. [Google Scholar] [CrossRef]
  54. Michaud, M.; Forgues, E.-C.; Carignan, V.; Forgues, D.; Ouellet-Plamondon, C. A lean approach to optimize BIM information flow using value stream mapping. J. Inf. Technol. Constr. 2019, 24, 472–488. [Google Scholar] [CrossRef]
  55. Castle, A.; Harvey, R. Lean information management: The use of observational data in health care. Int. J. Prod. Perform. Manag. 2009, 58, 280–299. [Google Scholar] [CrossRef]
  56. Arromba, A.R.; Teixeira, L.; Xambre, A.R. Information flows improvement in production planning using lean concepts and bpmn an exploratory study in industrial context. In Proceedings of the 2019 14th Iberian Conference on Information Systems and Technologies (CISTI), Coimbra, Portugal, 19–22 June 2019; pp. 206–211. [Google Scholar] [CrossRef]
  57. Hölttä, V.; Mahlamäki, K.; Eisto, T.; Ström, M. Lean information management model for engineering changes. World Acad. Sci. Eng. Technol. 2010, 42, 1459–1466. [Google Scholar]
  58. Pschybilla, T.; Homann, A. Evaluation of end-to-end process and information flow analyses through digital transformation in mechanical engineering. Procedia CIRP 2020, 93, 298–303. [Google Scholar] [CrossRef]
  59. Schönig, S.; Ackermann, L.; Jablonski, S.; Ermer, A. IoT meets BPM: A bidirectional communication architecture for IoT-aware process execution. Softw. Syst. Model. 2020, 19, 1443–1459. [Google Scholar] [CrossRef]
  60. von Rosing, M.; Scheer, A.-W.; von Scheel, H. The Complete Business Process Handbook: Body of Knowledge from Process Modeling to BPM; Elsevier: Amsterdam, The Netherlands, 2014; Volume 1. [Google Scholar]
  61. Salvadorinho, J.; Teixeira, L. Organizational knowledge in the I4.0 using BPMN: A case study. Procedia Comput. Sci. 2021, 181, 981–988. [Google Scholar] [CrossRef]
  62. Navarro, A.M.; Sancho, M.P.L.; Garrido, J.A.M. Business process management systems in port processes: A systematic literature review. Int. J. Agil. Syst. Manag. 2020, 13, 258–278. [Google Scholar] [CrossRef]
  63. Rymaszewska, A. Lean implementation and a process approach—An exploratory study. Benchmarking Int. J. 2017, 24, 1122–1137. [Google Scholar] [CrossRef]
  64. Mehdouani, K.; Missaoui, N.; Ghannouchi, S.A. An approach for Business Process Improvement Based on Simulation Technique. Procedia Comput. Sci. 2019, 164, 225–232. [Google Scholar] [CrossRef]
  65. Das, B.; Venkatadri, U.; Pandey, P. Applying lean manufacturing system to improving productivity of airconditioning coil manufacturing. Int. J. Adv. Manuf. Technol. 2013, 71, 307–323. [Google Scholar] [CrossRef]
  66. Tiwari, P.; Sadeghi, J.K.; Eseonu, C. A sustainable lean production framework with a case implementation: Practice-based view theory. J. Clean. Prod. 2020, 277, 123078. [Google Scholar] [CrossRef]
  67. Maldonado, M.U.; Leusin, M.E.; Bernardes, T.C.d.A.; Vaz, C.R. Similarities and differences between business process management and lean management. Bus. Process. Manag. J. 2020, 26, 1807–1831. [Google Scholar] [CrossRef]
  68. Hevner, A.R. A Three Cycle View of Design Science Research. Scand. J. Inf. Syst. 2007, 19, 87–92. [Google Scholar]
  69. Hevner, A.R.; March, S.T.; Park, J.; Ram, S. Essay in Information Design Science systems. Manag. Inf. Syst. 2004, 28, 75–105. [Google Scholar] [CrossRef]
  70. Basulo-Ribeiro, J.; Pimentel, C.; Teixeira, L. What is known about smart ports around the world? A benchmarking study. Procedia Comput. Sci. 2024, 232, 1748–1758. [Google Scholar] [CrossRef]
Figure 1. Study methodology.
Figure 1. Study methodology.
Futureinternet 16 00350 g001
Figure 2. Layout of current entry and exit gate.
Figure 2. Layout of current entry and exit gate.
Futureinternet 16 00350 g002
Figure 3. BPMN of the smart terminal access process (BPMN 2.0).
Figure 3. BPMN of the smart terminal access process (BPMN 2.0).
Futureinternet 16 00350 g003
Figure 4. Representation of the layout of the four checkpoints.
Figure 4. Representation of the layout of the four checkpoints.
Futureinternet 16 00350 g004
Figure 5. BPMN of the process in checkpoint 2.
Figure 5. BPMN of the process in checkpoint 2.
Futureinternet 16 00350 g005
Figure 6. BPMN of the process in checkpoint 3.
Figure 6. BPMN of the process in checkpoint 3.
Futureinternet 16 00350 g006
Figure 7. BPMN of the gate IN process.
Figure 7. BPMN of the gate IN process.
Futureinternet 16 00350 g007
Figure 8. BPMN of the gate OUT process.
Figure 8. BPMN of the gate OUT process.
Futureinternet 16 00350 g008
Figure 9. Investigation artifact.
Figure 9. Investigation artifact.
Futureinternet 16 00350 g009
Table 1. AS-IS process description and its limitations.
Table 1. AS-IS process description and its limitations.
ProcessDescriptionLimitations
Entry process
  • With prior scheduling
  • The carrier or truck driver schedules the delivery or pick-up service via the GAS system, providing details about the service, cargo, and vehicle.
  • After authorization from the Tax Authority and the customer, the appointment is confirmed in TOS.
  • The driver receives a PIN for terminal access and can proceed to the registration booth to verify identification documents.
  • At the express gate, if the driver has a valid Express Gate card, they swipe it, enter the PIN received at the time of booking, and the gate opens. If not, the driver signals for security to open the gate.
  • Manual verification: the manual verification of documents and information by gate operators causes delays and increases the risk of human error.
  • Limited system integration: a lack of integration between systems (GAS, TOS, SPC (single port card) results in potential inconsistencies and delays.
Entry process
  • Without prior scheduling
  • The driver arrives at the terminal without prior scheduling.
  • The driver goes to the PSA gate documentation room and security area to provide necessary information and validate the access request manually.
  • In the PSA gate documentation room, the documentation operator registers the truck’s information and the cargo details in TOS (PSA).
  • The driver proceeds to the entry gate, signals to the security operator (if they do not have an Express Gate card), and the gate is opened manually.
  • Prolonged manual verification: the time needed for manual verification of each vehicle and its documentation can cause delays.
  • Need for access cards or manual signals: dependence on access cards or manual procedures to open the gate adds to inefficiency.
Exit process
  • The driver goes to the exit gate.
  • The exit gate operator opens TOS (PSA), enters details about the truck and containers being carried, and verifies this information against the loading instructions.
  • An exit slip is printed (one for each container leaving the terminal) and given to the truck driver.
  • The driver uses their Express Gate card to activate the exit gate and complete the terminal exit process. If they have not swiped an Express Gate card upon entry, they must signal for the security operator to manually open the gate.
  • Manual data entry: manual entry of data and the requirement for manual verification by the exit operator can be time-consuming and prone to errors.
  • Dependence on manual validation: the need for manual validation to release the exit gate increases processing time and can cause queues and delays.
Table 2. Critical components of smart gates.
Table 2. Critical components of smart gates.
Critical ComponentsExplanation
Automatic driver identificationUse of a driver identification system, where drivers register and use ID cards or biometrics.
Automatic capture of data from equipment entering and leaving terminals
  • Vehicle license plate recognition: use of optical character recognition (OCR) technology to identify truck license plates.
  • Container number recognition: use of OCR to identify container numbers, requiring advanced algorithms and the capture of multiple angles.
  • Verification of weight, seal number, and cargo type: integration of scales and verification of seals for security and customs compliance. Danger sign verification.
Schedule verificationThe data collected are compared with those contained in the schedule.
Integration with TOSIntegration between different information systems: TOS, GAS and AGS.
Remote communication for routes/lanes and exception handlingPeople from the terminal who work remotely to support these activities.
Table 3. Summary of each checkpoint.
Table 3. Summary of each checkpoint.
# *CheckpointHardwareExplanation
1Checkpoint 1—1.1. TriageLPR (license plate recognition)—Vehicle registration number
ACCR (automatic container code recognition)—Container license plate
Camera context
Identification of the following:
  • Vehicle number plate;
  • The license plate of the container(s), which makes it possible to validate the appointment.
The context camera can also be used to check whether the vehicle trying to enter the terminal is authorized to do so or not.
2Checkpoint 1—1.2. Variable messageInformation panelAccording to the check carried out earlier, the panels indicate whether the driver can proceed to checkpoint 2, or whether he/she should take the public road.
In the case of proceeding to checkpoint 2, the driver also receives information on which lane to take (on the left if they have an appointment, on the right if they do not).
3Checkpoint 2—2.1. ACCR/ADDRInformation boards
Barrier
LPR—Front and rear
ACCR/ADDR cameras
Context cameras
Each lane should have a panel showing whether the lane is operational or not. In addition, each lane will have a first barrier to inhibit access to the lane if it is inoperative or if it is occupied by a vehicle in process.
Collect information on the following:
  • Vehicle number plate;
  • License plate of the containers;
  • Photographs of the containers.
4Checkpoint 2—2.2. Driver validationBarrier
Service kiosk with:
Card reader,
Biometric reader,
Intercom,
Touch screen.
This is where the driver is identified, and information is also given about where the driver should go, as follows:
  • To checkpoint 4, if he/she has a valid appointment and a is driver with authorization;
  • Proceed to checkpoint 3, park the vehicle and proceed to resolve the conflicts that made it impossible to enter the terminal;
  • Head for the exit onto the public highway.
5Checkpoint 3—3.1. Park entryLPRCar park entry record.
6Checkpoint 3—3.2. Park exitLPR
Information panel
Registration of the vehicle leaving the car park.
The vehicle leaving the car park may be travelling to the pre-gate (checkpoint 2) or to the public road.
Tell the driver whether he/she can access the gate or must follow the exit route.
7Checkpoint 3KiosksSelf-service terminals support drivers in solving problems that have prevented them from entering the terminal.
8Checkpoint 4—Access to the container terminalLPR
Barrier
Allows validation of which car is authorized to enter the terminal.
* Step numbering.
Table 4. KPI measures.
Table 4. KPI measures.
KPIExplanation
No. of services not performed (due to inefficiency or unavailability of the terminal operator)This KPI refers to the number of services that were scheduled but not performed as planned. This can happen due to various factors, such as vehicle breakdowns, delays, scheduling errors, lack of necessary documentation, lack or mismanagement of resources within the terminal, or other operational problems. This indicator is important because non-performed services can lead to delays in the supply chain, customer dissatisfaction, and operational inefficiencies.
Average time inside the terminal (time from entering the terminal to leaving)This measures the average time vehicles spend inside the terminal from the moment they enter until the moment they leave. This time includes processes such as waiting, loading and unloading goods, documentation, and other administrative procedures. A low average time usually indicates an efficient flow and well-managed operations, while a high average time can indicate congestion, inefficient processes, or problems with loading/unloading operations. This KPI is crucial for understanding how to optimize operations and improve the terminal’s overall productivity.
No. of appointments vs. No. of no appointmentsThis measures the percentage of vehicles that arrive on time according to their appointment versus those that arrive without an appointment. This can help users to understand the effectiveness of training in using the scheduling system.
Canopy read error rate 1This quantifies the failure rate when reading data from the truck/container/galley, which may indicate the need for maintenance or updating of the system.
Average time between passing checkpoint 1 and gate IN (gate service time)This evaluates the average time a truck takes from checkpoint 1 to gate IN, which can help identify bottlenecks and efficiency.
Percentage of trucks diverted to checkpoint 3This calculates the percentage of trucks that are diverted to checkpoint 3, which may indicate problems with pre-validation or the scheduling system. Subsequent identification of the situation that led the vehicle to checkpoint 3 (causes—software, hardware, scheduling, etc.).
Time to resolve contingencies in checkpoint 3This measures the time needed to resolve problems that make it impossible for the driver to enter the terminal.
Customer/driver satisfactionThis evaluates the level of satisfaction of drivers with the terminal entry process using surveys or feedback.
Manual intervention rateThis accounts for the frequency with which manual intervention is required due to faults in the automated system.
Peak capacity vs. effective utilizationThis compares the maximum number of trucks the terminal can process in a period with the actual number of trucks processed.
Intermodal terminal throughput (volume)This measures the number of cargo units (containers) that pass through the entry/exit gate per unit of time.
No. of system response failures (TOS, GOS, GAS, others)The aim is to quantify the number of failures in information systems for a year and to categorize these failures based on their specific causes (e.g., hardware failures, software errors, network problems, human failures, security issues, etc).
OthersWho went out onto the public highway, what controls they went through, and how long they spent inside from checkpoint 1 to checkpoint 4; trying to identify the cause of their exit (at the limit they were validated and decided to leave…).
Table 5. Comparison between the AS-IS and TO-BE states of the terminal processes.
Table 5. Comparison between the AS-IS and TO-BE states of the terminal processes.
AspectAS-IS StateTO-BE StateBenefits of the TO-BE State
Entry process with schedulingManual verification of documents and information by gate operators. Limited system integration causing delays and errors.Automated verification using OCR and integration between systems (TOS, GAS, AGS).Reduces manual labour, decreases delays, minimizes human error, and improves overall efficiency and accuracy in data handling.
Entry process without schedulingManual process for access validation, prolonged verification time, and dependence on access cards or signals.Drivers are directed to a specific location that does not interfere with the entry flow. This measure aims to make the process without an appointment more complex, thus emphasising the advantages of making an appointment in advance and indirectly encouraging drivers to adhere to the appointment.Reduces delays caused by manual checks, enhances security, and allows for seamless entry without prior scheduling.
Exit processManual data entry and verification by exit operators; prone to errors and causes queues and delays.Automated data capture and verification with minimal manual intervention.Streamlines exit process, reduces errors, and decreases the time needed for trucks to exit, enhancing throughput and efficiency.
System integrationLack of integration between critical systems leading to inconsistencies and delays.Full integration between all relevant systems (TOS, GAS, AGS) for seamless data flow.Ensures consistent and reliable data across systems, reducing delays and improving decision-making and operational flow.
Security and verificationReliance on manual checks and signals, which are time-consuming and prone to errors.Enhanced security with multiple automated checkpoints for driver, vehicle, and cargo validation.Improves security and reduces unauthorized access, minimizes manual intervention, and speeds up the verification process.
Data handling and accuracyHigh potential for errors due to manual data entry and lack of real-time data integration.Real-time data capture and automated processing with integrated systems.Increases data accuracy, reduces errors, and provides real-time insights for better operational management and decision-making.
Operational efficiencyInefficient processes with significant delays and manual interventions leading to lower productivity.Streamlined processes with automation at every checkpoint, reducing delays and manual interventions.Enhances overall terminal efficiency, reduces operational costs, and increases throughput capacity and customer satisfaction.
Table 6. Practical recommendations.
Table 6. Practical recommendations.
Category Strategies
Overcoming stakeholder resistance
  • Emphasize the importance of comprehensive training programmes for port staff and stakeholders to familiarize them with new technologies and processes.
  • Suggest strategies for involving stakeholders early in the process to ensure their input is considered and their concerns are addressed.
Integration of new technologies
  • Recommend a phased approach to implementing new technologies to allow for gradual adaptation and troubleshooting of any integration issues.
  • Highlight the need for standardizing technologies across different ports to ensure compatibility and ease of integration.
Practical applications and use cases
  • Discuss the potential of real-time data analytics to enhance decision-making and operational efficiency.
  • Cost-benefit analysis: encourage port managers to conduct cost-benefit analyses of different technologies to determine the most cost-effective solutions.
Addressing human factors
  • Propose the development of comprehensive change management strategies to handle the human aspect of technological adoption.
  • Suggest establishing mechanisms for continuous feedback and improvement.
Policy and regulatory recommendations
  • Advocate for policies that support innovation and digital transformation in ports.
  • Emphasize the importance of complying with international standards and regulations related to data privacy, cybersecurity, and environmental impact.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Basulo-Ribeiro, J.; Pimentel, C.; Teixeira, L. Digital Transformation in Maritime Ports: Defining Smart Gates through Process Improvement in a Portuguese Container Terminal. Future Internet 2024, 16, 350. https://doi.org/10.3390/fi16100350

AMA Style

Basulo-Ribeiro J, Pimentel C, Teixeira L. Digital Transformation in Maritime Ports: Defining Smart Gates through Process Improvement in a Portuguese Container Terminal. Future Internet. 2024; 16(10):350. https://doi.org/10.3390/fi16100350

Chicago/Turabian Style

Basulo-Ribeiro, Juliana, Carina Pimentel, and Leonor Teixeira. 2024. "Digital Transformation in Maritime Ports: Defining Smart Gates through Process Improvement in a Portuguese Container Terminal" Future Internet 16, no. 10: 350. https://doi.org/10.3390/fi16100350

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop