Cognitive Emergency Task Coordination via Skill Inference
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Solution Overview
Problem
Diverse communication methods and channels used by emergency responders lead to inefficiencies in coordinating tasks during emergency situations, as they often lack real-time, effective assignment of skills and expertise among participants.
Innovation Solution
A computer-implemented method and system for cognitive emergency task coordination that receives participant data, infers skills, generates task lists, assigns tasks based on expertise, and sends coordination data to participants, utilizing augmented reality and IoT sensors to dynamically prioritize and update tasks in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If diverse communication methods and channels are used by emergency responders, then communication coverage is improved, but coordination efficiency deteriorates
Solution Approach 1:
The patent combines multiple communication channels (radio, cellular, internet) into a unified task coordination system that manages all communications through a single platform. The server consolidates task assignments and coordination data across all channels, allowing responders to use diverse communication methods while maintaining centralized coordination efficiency.
Solution Approach 2:
The task coordination server acts as an intermediary between diverse communication channels and emergency responders. It receives participant data from various sources, processes task assignments, and distributes coordination data through appropriate channels, eliminating the need for direct multi-channel coordination among responders.
2Device complexity
If manual task assignment is used among emergency responders, then system complexity is reduced, but response time deteriorates
Solution Approach 1:
The system enables automatic task assignment based on participant skills and expertise data. The server autonomously matches tasks with suitable responders using algorithms that analyze participant profiles, eliminating manual assignment processes while reducing response time. The system serves itself by automatically generating and distributing task assignments without human intervention.
Solution Approach 2:
The system changes the parameter of task assignment from manual human decision-making to automated algorithmic processing. By transforming the assignment process into a computational task based on participant data parameters (skills, expertise, availability), the system achieves faster response times while managing complexity through standardized data structures and algorithms.
3Measurement precision
If real-time participant data collection is implemented, then task assignment accuracy is improved, but information processing load increases
Solution Approach 1:
The system collects and processes participant data (skills, expertise, availability) in advance before emergencies occur. This preliminary data collection and processing creates ready-to-use participant profiles that can be quickly matched with tasks during emergencies, reducing real-time processing load while maintaining high assignment accuracy.
Solution Approach 2:
The system processes only the essential participant data parameters needed for task matching (skills, expertise, availability) rather than collecting and processing all possible participant information. This selective processing approach achieves sufficient assignment accuracy while minimizing information processing load and energy consumption.
Data Source
AI summary
Systems and methods for cognitive emergency task coordination are disclosed. In embodiments, computer-implemented method comprises: receiving, by a computing device, participant data from one or more participant devices; inferring, by the computing device, skills or expertise of one or more available participants based on the participant data; generating, by the computing device, a task list including tasks associated with an emergency; assigning, by the computing device, select participants of the one or more available participants to one or more of the tasks in the task list based on the inferred skills or expertise; and sending, by the computing device, coordination data to the select participants, the coordination data including information regarding the one or more of the tasks assigned to the respective select participants.