Ad Hoc Network Data Analysis for Predictive Decision-Making
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Solution Overview
Problem
Conventional systems for data analysis in rapidly changing environments are inefficient due to reliance on large data inventories, manual processing, and inability to dynamically analyze spatial, temporal, and contextual elements, leading to unmanageable information and delayed predictive decision-making.
Innovation Solution
A computer-implemented method and system that receives and indexes spatial, temporal, and contextual data elements, allowing for real-time analysis and predictive decision-making by identifying events that satisfy predefined rules, with the capability to modify rules dynamically and process data in a distributed cloud computing environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If large buffer stocks of data inventory are maintained to protect against change, then data availability is improved, but information manageability deteriorates
Solution Approach 1:
The patent segments data into structured categories (spatial, temporal, contextual elements) and organizes them into hierarchical data models. This segmentation transforms unmanageable large-scale data inventories into structured, queryable components that can be efficiently processed and analyzed.
Solution Approach 2:
The patent introduces multiple dimensional frameworks for data organization including spatial dimensions (geographic coordinates, locations), temporal dimensions (time stamps, sequences), and contextual dimensions (categories, attributes). These additional dimensions enable efficient retrieval and analysis of large data inventories without increasing management complexity.
2Device complexity
If manual processing methods are used for data analysis, then system complexity is reduced, but decision-making speed deteriorates
Solution Approach 1:
The patent replaces manual mechanical processing with automated computer-implemented systems that perform data collection, analysis, and decision-making functions. The system automatically processes spatial, temporal, and contextual data elements using algorithms and computational methods, eliminating the need for manual intervention while significantly increasing decision-making speed.
Solution Approach 2:
The system enables self-service data analysis and decision-making through automated processes that collect, process, and analyze data without requiring manual intervention. The computer-implemented system autonomously performs data retrieval, processing, and predictive analysis functions, freeing users from manual processing tasks.
3Ease of operation
If static information storage is used in conventional systems, then data retrieval simplicity is improved, but real-time predictive decision-making capability deteriorates
Solution Approach 1:
The patent transitions from static information storage to dynamic data processing by implementing systems that continuously collect, update, and analyze spatial, temporal, and contextual data elements. The system processes data in real-time, enabling adaptive decision-making that responds to changing conditions while maintaining ease of data retrieval through structured organization.
Solution Approach 2:
The patent creates a multi-functional system that simultaneously performs data storage, retrieval, processing, analysis, and predictive decision-making. The computer-implemented system integrates multiple functions into a unified platform that handles various data types and operations, providing both simple retrieval and advanced predictive capabilities.
4Loss of time
If data latency is reduced for real-time analysis, then predictive decision-making speed is improved, but data processing complexity deteriorates
Solution Approach 1:
The patent implements preliminary action by pre-organizing data into structured spatial, temporal, and contextual elements and pre-establishing analysis frameworks. This preliminary structuring enables rapid real-time processing without increasing operational complexity, as the data is already organized for efficient querying and analysis when real-time decisions are required.
Data Source
AI summary
A computer-implemented system and method of predictive decision-making in an ad hoc network. The computer-implemented method includes receiving a set of rules into the ad hoc network and identifying a data set for each rule. The computer-implemented method also includes selecting a first and second node from the ad hoc network to process a first and second rule as a function of the identified data set according to an optimizing algorithm. The computer-implemented method also selects a third node to receive the processed results from the first and second nodes. An indication is provided of the processed results by the third node.