Analyzing Big Data from Vessel Tracking Systems and Sensors
1. Introduction
1.1 Importance of analyzing big data in marine accidents and environmental incidents
1.2 Overview of vessel tracking systems and sensors
2. Methodology
2.1 Data collection and preprocessing
2.2 Data analysis techniques for identifying patterns
2.3 Statistical models used in analyzing big data
3. Findings and Analysis
3.1 Patterns and trends in marine accidents
3.2 Identification of environmental incidents
3.3 Impact of vessel tracking systems and sensors on safety and environmental protection
4. Conclusion
4.1 Summary of key findings
4.2 Implications for maritime industry and regulatory bodies
4.3 Future research directions
Analyzing Big Data from Vessel Tracking Systems and Sensors
1. Introduction
The application of big data in the maritime industry has gained significant attention in recent years. The analysis of vessel tracking data and sensor data not only benefits the advancement of the industry itself but also provides valuable insights in addressing safety issues and environmental problems. In practice, vessel tracking system refers to a system that identifies the location of a vessel at any moment using the satellite system and communication process. The Automatic Identification System (AIS) is a common vessel tracking system which is being used. It is legally required for all passenger vessels and vessels over 300 tonnes in the international voyage to install AIS transponders. As a result, AIS provides continuous information to vessel operators and maritime authorities about the identity, the type, the position, the speed and the course of the vessel. On the other hand, various types of sensor systems such as motion sensor, temperature sensor and fuel or chemical sensor can be applied in collecting data to monitor the conditions of different components of the vessel and also the surrounding environment. By analyzing the data collected from these systems, ranging from routine technical operations to incident and emergency situations, potential safety risks and environmental issues can be better identified. The “datafication” of the oceans, which means turn the physical and chemical characteristics of the sea and large data set from sensors and the satellite into digital data, has achieved significant progress. This refers to not only the vessel tracking data but also all other forms of data, for example, that taken from the remote sensor system. The increasing coverage and accuracy of big navigational and remote sensing data from the vessel and the environment at sea will further promote the development and application of big data analysis in marine study.
1.1 Importance of analyzing big data in marine accidents and environmental incidents
Marine transportation is perishable in the sense that they are subject to a wide variety of operational and environmental influences, and often they have to travel under challenging and uncertain, as well as highly unpredictable conditions. Marine accidents have serious implications on both the entity involved and the environment as a whole. Over the years, the world has seen some of the major accidents leading to loss of lives, fatalities, and damage to the environment. This has resulted in regulating the protection of the marine environment through the implementation of the International Safety Management (ISM) which entails that all entities have to demonstrate statutory and regulatory control in respect to the protection of the environment. The theory behind the ISM Code is the adoption of a management system which supports the objectives of maintaining safety at sea as well as preventing injury or loss of life. By analyzing big data, patterns and trends that are not directly obvious and those that are perhaps counterintuitive can be identified. This will offer insight into how and why certain types of marine accidents happen and at the same time be used to inform decisions on the possible strategies for improving marine safety. It is also evident that big data analytical tools have shown the impacts of the gradual shift that is being noticed as a result of the emergence of new technologies. These technologies include the developments of vessel tracking systems and sensors as well as the continued improvements in data storage and management facilities both onshore and offshore. With the introduction of vessel traffic services areas coupled with the developments in vessel traffic systems, it can be seen that the workload on the bridge from the crews insofar as the monitoring of vessels has been significantly reduced. This has been successful through the provision of automated sensors such as radar, digital CCTV, Automated Identification Systems (AIS), and direction finders. These sensors do not only work in real time but enable the tracking, surveillance, and analysis of the movement of all vessels in the coverage area. On the other hand, land-based differential global positioning system that uses satellite technology has seen the development of the vessel tracking system. This type of global navigation satellite systems has been customized for use in civilian vessel traffic and it provides a national navigation service intended for use in ship and inshore applications. These satellite-based augmentations have made it possible for ship navigation to cover any country at any location and at any time.
1.2 Overview of vessel tracking systems and sensors
New developments of the new types of vessel tracking systems and sensors are definitely showing progress in providing new data and information, such as advanced processing techniques of marine geospatial big data. With the technology advancement and implementation of the e-Navigation strategy in many countries, we are going to receive further advanced data and information from SIMD, Digital ATON, and e-Navigation Radio and Communication technologies in the future. It is no doubt that computational and analytical capabilities are going to be crucial in utilizing these big data and to help enhance our knowledge of maritime safety and marine environment protection.
The use of AIS is also becoming more prevalent in modern fisheries management. For example, in the European Union, Vessel Monitoring Systems (VMS), which were originally designed to monitor fishing quotas in line with the Common Fisheries Policy, are being upgraded to use AIS signals harvested by satellite to provide greater transparency with which government agencies and researchers can monitor the activities of fishing vessels.
The Automatic Identification Systems (AIS) is one of the most widely used vessel tracking systems. It was originally designed as a collision avoidance tool but is increasingly being used for other applications, including maritime domain awareness, search and rescue, vessel traffic management, and marine environmental monitoring. It has also been identified for its potential uses in a range of e-Navigation applications. The system operates in the VHF mobile maritime band using a network of land-based coastal AIS stations and is mandatory on all vessels and the class A mobile stations in the SOLAS treaty, which applies to all vessels of 300 gross tonnage and above on international voyages, and also passenger vessels regardless of size.
Vessel tracking systems and sensors provide the foundation for the collection of data that is used in analyzing the movements, behaviors, and characteristics of vessels at sea. There are many different types of systems and sensors that are used to monitor vessels in different environments, from the satellite-based vessel tracking systems that are used to monitor global shipping traffic, to the specialized sensors that are used to monitor the movements and conditions of vessels in real time, such as GPS, AIS, VMS, LRIT, cameras, voice communication, radar, and integrated bridge system. But the expanding era of big data in the maritime world has strengthened the interest of many stakeholders in these technological options.
2. Methodology
