Ontology-Based Message Parser for Smart City Collaboration
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Solution Overview
Problem
Current collaboration methods between operators in different organizations are inefficient, prone to errors, and hindered by 'siloed' behavior, leading to information overflow and inconsistent sharing, especially in Smart City environments.
Innovation Solution
A collaboration management system that uses a database, message parser, recommendation engine, and data distributor to classify and filter relevant information from electronic messages based on pre-defined ontologies and operator classes, providing class-relevant information to operators through a remote network, utilizing AI and machine-learning algorithms for decision-making and user feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If messages are shared ad hoc between different communicating organizations, then information can be exchanged between operators, but the collaboration becomes inefficient, inconsistent and prone to errors
Solution Approach 1:
The system segments information into structured data elements with defined schemas and ontologies. Messages are parsed into discrete, categorizable units that can be systematically managed and distributed, transforming unstructured ad hoc sharing into organized, reliable information exchange.
Solution Approach 2:
The system changes the parameters of information sharing by imposing structured schemas, ontologies, and classification systems on exchanged messages. This transforms the nature of collaboration from informal to formal, ensuring consistency and reliability while maintaining ease of operation through automated processing.
2Reliability
If operators work in closed environments with no encouragement to share information, then each organization maintains its own information security and autonomy, but 'siloed' behavior obstructs collaboration between different operators or organizations
Solution Approach 1:
The system introduces an intermediary layer that sits between closed organizational environments. This mediator translates and structures information from different organizations using common ontologies and schemas, enabling collaboration while preserving each organization's information security boundaries and autonomy.
Solution Approach 2:
The system creates a universal information exchange framework that can handle multiple types of organizations and message formats. The common ontology and schema system serves as a multi-functional interface that enables diverse organizations to collaborate efficiently while maintaining their own operational independence.
3Quantity of substance
If operators are overwhelmed by a multitude of feeds from communicating organizations and social media, then comprehensive information is available, but information overflow becomes a problem
Solution Approach 1:
The system extracts only the relevant information from the multitude of available feeds using structured schemas and ontologies. By pulling out specific, categorized data elements rather than presenting all raw information, the system maintains comprehensive information availability while making processing manageable through automated classification and filtering.
Solution Approach 2:
The system segments the overwhelming volume of information into categorized, structured elements based on ontologies and schemas. This segmentation transforms the undifferentiated information overflow into organized, manageable units that can be efficiently processed and distributed to appropriate operators.
4Measurement precision
If a structured system with ontologies and schemas is implemented, then information can be classified and filtered effectively, but the system complexity increases
Solution Approach 1:
The system performs preliminary action by pre-defining ontologies, schemas, and classification structures before information exchange occurs. This upfront structuring enables precise information classification and filtering without requiring complex real-time processing, as the framework is already in place to guide automated parsing and categorization.
Solution Approach 2:
The system implements self-service through automated parsing, classification, and distribution based on pre-defined schemas. Once the ontology framework is established, the system autonomously processes incoming information without requiring manual intervention, reducing the operational complexity despite the sophisticated underlying structure.
Data Source
AI summary
A collaboration management system, comprising a database having stored operator information about the participating operators, the operator information of each operator comprising at least one operator class assigned to the respective operator; a data receiver configured to receive a data stream comprising a plurality of electronic messages from a plurality of communicating agents, each electronic message comprising at least one piece of information; a message parser operatively coupled with the data receiver, the message parser configured to parse the received electronic messages to extract pieces of information of the parsed electronic messages and to classify the electronic messages according to one or more ontologies from a set of pre-defined ontologies; a recommendation engine operatively coupled with the message parser and the database; and a data distributor operatively coupled with the recommendation engine.