23_Ministry-of-Oceans-and-Fisheries-Project

Project Name

• Development of AI-based Maritime Logistics Analysis Program

Topic Area

• Smart Logistics

Technical Field

• SW.AI

Project Goal

• Competition (Smart Maritime Logistics Contest)

Achievement Goal

• App Registration

Expected Duration

• April 17, 2023 ~ November 15, 2023

Member

AI & Frontend

• TaeHoonHer

BackEnd

• MinUkSon

FrontEnd

• JunSeoPark
• wonnie205

Project Introduction

This project aims to use AI technology to analyze and collect the latest news in the field of maritime logistics and develop a personalized recommendation system for users. Through the results of this project, users can easily and quickly access news that they are interested in, and can obtain high-quality information related to maritime logistics from among the various news that is pouring in real-time. Based on this, they can keep up-to-date with the latest trends in the maritime logistics industry.

The four main technologies that make up this project are as follows:

• Web Crawling

  • To collect the latest news from domestic and international news sites, web crawling technology will be used. This will allow us to collect real-time news data and analyze it.

• NLP

  • Natural Language Processing (NLP) technology will be used to analyze the collected news data. This will involve analyzing text data, extracting keywords, and conducting sentiment analysis. Recommendation System By analyzing user profiles, search histories, and previous recommendation results, a personalized news recommendation algorithm will be developed. This system will allow users to primarily access the news they want.

• Search Function

  • Users can search for and filter news related to specific keywords on their own.

The biggest advantage of this project is the personalized news recommendation system for users. Through this system, users can easily and quickly access news in their areas of interest, and are expected to have an easier time keeping up with the latest trends in the logistics industry. The search and recommendation functions will also make it easier for users to find the information they want, which will be a great help to those working in the maritime logistics industry.

Background and Proposal

• The field of maritime logistics is rapidly changing and steadily growing. Keeping up-to-date with the latest trends is becoming a competitive advantage, and news information has become an important asset. However, collecting and analyzing a large amount of news data is difficult and time-consuming.
• Therefore, we plan to use AI technology to collect and analyze the latest news in the field of maritime logistics, develop an algorithm that can provide personalized recommendations to users, and make it into a service. This will allow users to easily and quickly access news that they are interested in, and keep up-to-date with the latest trends in the industry.

Main Functions

• Development of AI-based chatbot and recommendation algorithm model
• Development of a recommendation algorithm that can provide customized recommendations by analyzing user's desired keywords and interests
• Visual representation of news data and analysis results
• Development of an algorithm to update real-time collected news data
• Development of an intuitive and user-friendly UI
• Development of a feature that allows users to bookmark specific news for future reference
• Sharing function to other SNS platforms of the news currently being viewed
• Notification function to send news related to the user's interest keywords
• Feature to display the latest news related to maritime logistics on the app main screen.

Applied Technologies

• The overall execution involves collecting data on domestic and international news that is updated in real-time on the internet, categorizing them by category, and delivering them to users. If a user enters a specific keyword, information related to that keyword and desired company is provided
• The developed model is stored in a deep learning server, and when information is entered into the trained model, the results of news from the past to the present related to that information are provided
• News is categorized and classified by category and provided accordingly.
• A mobile development platform is used to guide the above deep learning operations to fit the mobile device
• A push notification is developed to inform the database server and administrators of the data to be stored
• Through the collection and learning of domestic and international logistics data, an AI chatbot specializing in maritime logistics is developed

Expected Effects and Application Fields

Key Features

• Efficient information collection: Easily understand the latest trends and issues in the maritime logistics industry to enable more accurate decision-making.

• Customized news provision: Analyze user preferences and interests to provide personalized news, helping users utilize their time more efficiently.

• Increased competitiveness: Quickly understand the latest trends in the maritime logistics industry and respond accordingly to increase a company's competitiveness.

• Business opportunity discovery: Increased interest in the industry can lead to the discovery of new business opportunities.

Application Areas

This project can be applied in companies, research institutes, and universities related to the maritime logistics industry. It can contribute to the development of the industry and assist in making more accurate and timely decisions. Additionally, students and aspiring industry professionals interested in maritime logistics can easily obtain information to improve their knowledge.

Project Introduction

This project is expected to play an important role in the maritime logistics industry, which has a significant impact on South Korea's trade and economic development. The maritime logistics industry is a crucial industry worldwide, and South Korea actively promotes domestic and international trade activities for economic development. However, the industry is currently facing various challenges, including complex regulations. SOLAS and MARPOL are two representative examples of international maritime conventions. SOLAS contains regulations for ship safety, while MARPOL is a convention for preserving the marine environment, managing waste, and pollutants.

Some examples of the problems in the maritime logistics industry include the difficulty in real-time tracking of ship positions and environmental issues caused by marine pollution. Furthermore, accidents in the maritime logistics industry require sufficient preparation for disaster recovery, which is often inadequate.

These regulations and challenges highlight the importance of collecting and analyzing information on various incidents in the maritime logistics industry. This project will use NLP technology to collect and classify news related to the domestic and international maritime logistics industry. It aims to provide users with easy access to information on regulations and challenges.

This project has various practical applications. For example, professionals in the port industry can use the application to obtain information on the maritime logistics industry, allowing them to make more efficient decisions. Additionally, the application can improve understanding of foreign trade and promote the development of South Korea's trade. Students interested in the maritime logistics industry or news media seeking information on the industry can also use the application.

This project is expected to contribute significantly to the development of South Korea's maritime logistics industry and trade and provide accurate and reliable information to professionals and the public. This project may also propose and develop new technologies for NLP and news analysis, leading to research and publication of new services and technologies.

Background and Necessity

The background for planning this service was the lack of accurate and reliable information that users need in the South Korean maritime logistics industry. The maritime logistics industry plays a very important role in the economic development and trade of South Korea, and various problems are arising as a result. However, finding information about them is not an easy task, and even among the various news articles related to incidents, it was difficult to find reliable ones. The maritime logistics industry accounts for over 95% of South Korea's trade volume and plays a very important role in the country's economic development. However, since 2020, due to international trade disputes and COVID-19, the maritime logistics industry has faced many difficulties.

One of the problems in the maritime logistics industry is the instability of cargo transportation. Problems such as accidents or delays that occur during cargo transportation cause a lot of losses every year and undermine the stability of the maritime logistics industry. The maritime logistics industry is currently facing fierce competition worldwide, and there are major problems due to the existing fixed cost structure and inefficiency caused by high-capacity transportation. These problems are considered factors that limit the growth of the maritime logistics industry.

In the maritime logistics industry, various crimes occur frequently. Crimes such as illegal operations, theft, and robbery cause significant damage to the maritime logistics industry. Reliable information and data are essential for preventing such crimes and tracking down criminals.

Therefore, we have determined that collecting and analyzing accurate and reliable information and data to increase the stability and efficiency of the maritime logistics industry is very important. Using NLP technology and news analysis technology, this chatbot and news integrated application can be used as a solution to solve various problems in the maritime logistics industry and help users obtain accurate and reliable information. Additionally, this can contribute to the development of trade by increasing the stability and efficiency of the maritime logistics industry.

Applied Technologies

• Natural Language Processing (NLP):

  • Leveraging advanced NLP techniques such as BERT, Word2Vec, GPT-3, and other state-of-the-art models, the system performs sophisticated natural language processing tasks on news articles such as topic modeling, entity recognition, sentiment analysis, summarization, and more. These technologies allow for the extraction of meaningful insights and patterns from large volumes of unstructured text data, enabling the system to provide valuable and actionable information to users

• Database Management Technology

  • Utilizing industry-standard database management systems and tools, the system ensures the efficient storage, retrieval, and management of vast amounts of structured and unstructured data such as user profiles, news articles, and other relevant information. The use of SQL and other advanced database management technologies helps to ensure data integrity, scalability, and security

• Android App Development Technology

  • The system leverages the latest Android app development technologies and frameworks, such as Android Studio and Java, to create engaging and user-friendly mobile apps that meet the needs and preferences of users. These apps provide intuitive and responsive user interfaces, fast and reliable performance, and seamless integration with other system components

• Server Development Technology

  • The system employs advanced server development technologies and frameworks such as Python and Flask to build robust and scalable back-end servers that can handle large volumes of requests from multiple users. These servers are designed to be highly modular and extensible, allowing for easy integration with other system components and third-party services.

• Cloud Technology

  • Leveraging cloud-based technologies and services such as AWS, the system ensures the reliable and scalable deployment and operation of its servers and data storage infrastructure. This allows for efficient resource utilization, cost savings, and enhanced data security and privacy. Additionally, the use of cloud technologies enables the system to easily scale up or down its resources based on changing user demand, ensuring optimal system performance and availability at all times.