Open Freight Market Simulation System
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Solution Overview
Problem
Current systems for simulating open freight markets via the Internet lack the ability to display specific management and production processes, fail to accurately reflect real-time data, and lack tools for data mining, self-learning, and contract management, leading to inefficiencies and inaccuracies in freight market operations.
Innovation Solution
An automated information system that includes a hardware-software platform with central servers, user devices, and databases, enabling data recognition, processing, and storage, along with tools for data mining, self-learning, and contract management, to simulate and manage open freight market processes in real-time, including the generation of electronic contracts and monitoring of vessel status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual data input methods are used for freight market information, then data accuracy can be maintained through human verification, but data processing speed and real-time simulation capability deteriorate
Solution Approach 1:
The system employs self-learning algorithms that automatically recognize and categorize freight market data from multiple sources without manual intervention. The system serves itself by continuously learning from incoming data streams, improving accuracy over time while maintaining high processing speeds through automated pattern recognition and validation rules.
Solution Approach 2:
Manual data input and verification processes are replaced with electronic data collection systems that automatically gather, validate, and process freight market information. The mechanical process of human data entry is substituted with automated software agents that collect data from ports, vessels, and market participants in real-time.
2Reliability
If comprehensive data collection from multiple sources is implemented, then market simulation accuracy improves, but system complexity and data processing burden increase
Solution Approach 1:
The system segments data collection and processing into specialized modules: data collection agents for different sources (ports, vessels, brokers), validation modules for specific data types, and processing pipelines for different market parameters. This modular architecture manages complexity by dividing the comprehensive data collection task into manageable, independent components that can be developed and maintained separately.
Solution Approach 2:
Standardized data interfaces and protocols act as intermediaries between diverse data sources and the core simulation engine. These intermediary layers translate various data formats into a unified structure, reducing system complexity by providing a consistent interface layer that abstracts the heterogeneity of source systems from the core processing logic.
3Loss of time
If real-time data processing is implemented for all market participants, then decision-making speed improves, but computational resources and system load increase
Solution Approach 1:
The system implements partial real-time processing by prioritizing critical data streams (vessel positions, cargo availability, rate changes) for immediate processing while using near-real-time or batch processing for less time-sensitive information (historical data, market trends). This selective approach maintains decision-making speed for critical operations while reducing overall computational resource consumption.
4Productivity
If automated contract generation and management tools are added, then operational efficiency improves, but software complexity and development costs increase
Solution Approach 1:
The system pre-generates contract templates and standard clauses based on common freight market agreements. Contract frameworks are prepared in advance with configurable parameters, allowing automated population of contract documents when deals are struck. This preliminary preparation significantly reduces the complexity of real-time contract generation while maintaining high operational efficiency.
Data Source
AI summary
An invention is referred to systems and methods of digital calculations or data processing, specifically designated for special functions, for systems and methods, which allow a consolidated search for information and data base structuring in particular, collection of data and its registration in a digitalized form for the further input into hardware-software system and displaying on devices of users on demand. The system and method use hardware-software system including a hardware module and a data processing module. The hardware module contains central server and a complex of external devices of users, connected with the mentioned central server by data interchange means. The central server is connected with external e-mail servers by e-mail sending/receiving media. The data processing module is being adapted to provide of transforming the received electronic circular letters into a electronic sea shipping contract, containing data on cargo for transportation and data on vessel for transportation, as well as conditions for carriage of freight and port of departure and port of destination date using information, received from the personal accounts of participants of open freight market and complex of personal accounts of transport infrastructure subjects. The central server is connected with at least one database, which contains data of the generated electronic sea shipping contracts, associated with the received applications and/or the personal accounts of users.