Script-Based IoT Decision Management for Rapid Incident Response
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Solution Overview
Problem
Conventional big data analysis and decision-making systems are time-consuming and inflexible, relying on manual operations and standard operating procedures, leading to inefficient and rigid response strategies that lack automation and flexibility.
Innovation Solution
A big data related script-based decision management system utilizing IoT technology and an open architecture, integrating data from remote devices, annotating features, constructing events, and generating response strategies through script analysis to automate incident management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual operations and standard operating procedures are used for event assessment and data retrieval, then personnel can follow established protocols, but the response time increases significantly (20 minutes) and the system lacks flexibility
Solution Approach 1:
The system performs self-assessment of events and automatic data retrieval without requiring manual personnel intervention. The automated system evaluates events against predefined criteria and retrieves relevant data autonomously, eliminating the 20-minute manual response time while maintaining protocol adherence through structured decision rules
Solution Approach 2:
The patent replaces the mechanical manual operation system with an automated computing system. Instead of personnel manually accessing systems and retrieving data, the automated system electronically processes events and queries databases, dramatically reducing response time while maintaining reliability through consistent automated execution of assessment protocols
2Stability of the object's composition
If standard operating procedures are followed for event processing, then consistent protocols are maintained, but the response strategy becomes rigid and less flexible
Solution Approach 1:
The system transitions from static, rigid SOPs to dynamic automated decision-making that can adapt to different event types and severity levels. The automated system evaluates each event against multiple criteria and selects appropriate response strategies from a library of predefined actions, maintaining consistency through structured rules while achieving flexibility through conditional logic and varied response options
Solution Approach 2:
The patent changes the parameters of the decision-making system from fixed procedural steps to variable automated rules that can be adjusted based on event characteristics. The system modifies its behavior based on input parameters such as event type, severity, and contextual data, enabling flexible response strategies while maintaining protocol consistency through structured decision frameworks
3Ease of operation
If manual assessment and personal decision-making are used, then personnel can exercise judgment, but automation efficiency is reduced and comprehensive event handling becomes slower
Solution Approach 1:
The system performs self-assessment and automatic decision-making without requiring human intervention for routine events. The automated system evaluates events, retrieves data, and executes appropriate responses autonomously, achieving high productivity for standard events while reserving human judgment for complex or exceptional cases that require nuanced decision-making
Data Source
AI summary
The present invention relates to a big data related script-based decision management system and method thereof that applies the Internet of Thing technology and adopts an open architecture for setting up a big data database. The big data database stores a plurality of data collected by a plurality of remote devices, wherein the data consists of a feature extracted from the operational statuses of a plurality of remote devices; an event that is formed by analyzing the feature; a script that stores the response strategy created based on the event; and a unit of analysis that produces a strategy result by comparing and analyzing the event and the script.