Collaborative Decision Support via Asynchronous Sensor Tagging
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Solution Overview
Problem
Existing collaborative decision-making systems in virtual environments lack the ability to efficiently process and present sensor data from multiple sources to users asynchronously, leading to potential misinterpretation and delayed decision-making due to the complexity of data and lack of situational awareness.
Innovation Solution
A computer-implemented method that receives sensor data from multiple sensors, allows users to input tag data, and uses a decision support algorithm to generate decision options, which can be visually or audibly presented, enabling asynchronous data visualization and collaborative decision-making while adhering to a stored operational plan.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If sensor data from multiple sources is processed and presented to users in real-time, then decision-making speed is improved, but data complexity and processing requirements increase
Solution Approach 1:
The system segments sensor data processing by assigning different sensor types and data streams to different processing modules and users. Each user receives customized data subsets relevant to their role, reducing individual processing complexity while maintaining overall system comprehensiveness.
Solution Approach 2:
The patent introduces a virtual reality environment as an intermediary layer between raw sensor data and human decision-makers. This virtual environment automatically processes, integrates, and visualizes multi-source sensor data, reducing the computational burden on individual users while enabling rapid decision-making through intuitive 3D representations.
2Reliability
If multiple users collaborate on decision-making with comprehensive data access, then decision quality is improved, but system complexity and data management burden increase
Solution Approach 1:
The system merges multiple users' analytical perspectives and tag data into a unified decision-making process. By combining diverse user inputs and expertise in the virtual environment, the system achieves more reliable decisions while the automated integration reduces manual coordination complexity.
Solution Approach 2:
The virtual reality environment serves multiple functions simultaneously: data visualization, collaboration platform, decision support system, and operational plan management. This multi-functionality improves decision quality by providing comprehensive tools in one system while reducing overall system complexity by eliminating the need for separate specialized systems.
3Adaptability or versatility
If tag data from multiple users is stored and processed asynchronously, then collaborative analysis is improved, but data management complexity increases
Solution Approach 1:
The system performs preliminary organization and structuring of tag data as users input it asynchronously. Data is automatically tagged, categorized, and linked to relevant sensor data in advance, reducing the complexity of subsequent data retrieval and analysis while enabling flexible collaborative work.
4Ease of operation
If visualisations are presented to users at different times asynchronously, then user flexibility is improved, but real-time collaboration capability deteriorates
Solution Approach 1:
The system implements feedback mechanisms where users can view and respond to each other's tag data and annotations asynchronously. This allows users to work at different paces while maintaining collaborative continuity, as later users can build upon previous analyses without requiring simultaneous presence.
Data Source
AI summary
A computer implemented method of generating decision options. Sensor data is received from a plurality of sensors and presented visually to two or more users. Those users can then analyze the images and enter tag data which is received and stored along with the sensor data. The sensor and tag data are then input to a computer implemented decision support algorithm along with a stored operational plan. The algorithm then outputs one or more decision options which can assist a human decision maker in making a decision. The invention enables such a decision maker to make a decision quickly which complies with a previously stored operational plan and is likely to be correct since it is based on inputs from multiple human users. The invention is capable of being easily scaled to deal with a high volume of sensor data and a large number of users.