# The Development of Key Technologies in Applications of Vessels Connected to the Internet
## 3 Characteristics of the Internet of Vessels
### Data Analysis Methods  
Depending on the VTS, AIS, GIS, CCTV and RFID, the maritime administration obtains the dynamic data of the ships. With the complete ships databases, crew databases, meteorological databases and hydrologic database, it establishes a big data platform. Traditional data analysis methods are sampling or filtering the raw data and analyzing the data sample to look for patterns and features. [PERSON] [52] proposed an approach of ant colony optimization (ACO) to path the ship planning to avoid collision. In the research, the ACO-based algorithm was constructed including the data initialization, solution construction, pheromone trail update and the objective function. According to the scenarios shown in [PERSON]'s research, the algorithm could help ships hedge their collision risks and satisfy rule 15 of COLEGCs (Convention on the International Regulations for Preventing Collisions at Sea). Therefore, it can be seen that the most important characteristic of the traditional data analysis method is the complicated algorithm to get as much information as possible. Apart from the traditional data analysis method, the big data analysis method of the IoV system could analyze the whole databases efficiently [53]. At present, there are several methods of big analysis used for the IoV system, such as the deep learning approach, the knowledge calculation method and the visualization method. 1. The deep learning approach usually uses the artificial neural network method. Based on the multi-layered framework, this method could analyze and express the data. Taking advantage of data volume from the big data platform, it can use a more complicated model to represent the data effectively. Now this method is widely applied in the prediction of ship operation [54], collision warning [55] and risk analysis [56]. [PERSON] [54] took the turning performance of a single screw ship as an example to establish a mathematical model based on the artificial neural network. As was known, when the ship conditions (loading, oil consumption, speed, trim angles and heel angles) and the environment (wind, waves, water flow, offshore voyage) changed, the characteristics of ship operation would change at the same time. Based on the big data from the IoV system, the artificial neural network was trained to meet the predicted requirement for the ship's operation. According to the experiment with the real ship, the reliability of this method was verified. [PERSON] [55] established a kind of collision risk evaluating model by the neural network. Due to the big data analysis, the collision risk model obtained good results and could provide a reference for increasing the safety of the ship. 2. The knowledge calculation method extracts valuable knowledge from the big data platform to construct searchable and computable knowledge bases that include knowledge base construction, integration of multiple knowledge and knowledge update. The integration of multi-knowledge considers the sharing and reusing of knowledge and improves the real time and effectiveness of the data. This method is widely applied in the VTS [57], ship navigation [58] and decisions regarding energy consumption for ships [59]. [PERSON] [60] developed a kind of information system supporting navigational decision making. Information was acquired in the information acquisition mode and then the situation analysis would calculate and process the data. With the results of the knowledge calculation, the system made a good choice and took action to help the ship avoid collision. [PERSON] [61] studied a multi-criteria analysis-based decision support system developed for the management of incidents in maritime traffic. The decision support system organized a variety of information data related to emergency management--spatial data, radar data, weather data and GIS data--for the administrator, in a comprehensible and user-friendly way. It used the preference ranking organization method for enrichment evaluations (PROMETHEE) for treating the multi-criteria problem.