Hierarchical Analytics Module for Dynamic Data Collection

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Solution Overview

Problem

In multi-layer data collection systems, interpreting and processing data from diverse sensors across different manufacturers with varying calibrations is challenging, leading to difficulties in making accurate inferences and taking timely actions.

Innovation Solution

A hierarchical analytics module system that collects data from sensors, filters and augments it, and provides feedback to optimize data flow, allowing lower-level modules to focus on relevant data and take quicker actions, while higher-level modules make comprehensive decisions based on extensive data insights.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If all sensor data from diverse manufacturers is collected and processed centrally, then comprehensive data insights are achieved, but data processing time and system complexity increase

Engineering Contradiction:

Improvedata insightsVSAvoiddata processing time

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The patent divides the data processing system into multiple hierarchical tiers (edge devices, regional servers, central cloud). Each tier processes data locally and passes aggregated insights upward, rather than sending all raw sensor data to a central processor. This segmentation reduces transmission time and enables parallel processing across multiple levels simultaneously.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Lower-tier edge devices perform preliminary data filtering, validation, and aggregation before data reaches higher tiers. This preliminary processing eliminates unnecessary data early in the pipeline, reducing the burden on central systems and accelerating overall processing time while preserving critical information.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If all sensor data is transmitted to higher-level modules for processing, then comprehensive decisions can be made, but network bandwidth and processing resources are consumed

Engineering Contradiction:

Improvedecision accuracyVSAvoidprocessing resources

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The patent extracts and processes critical data elements at lower hierarchical tiers before transmission to higher levels. Edge devices filter out redundant information and transmit only essential aggregated data upward, reducing network bandwidth consumption and processing resource requirements at central systems while maintaining decision accuracy.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Each hierarchical tier performs partial processing appropriate to its level, with lower tiers handling routine filtering and aggregation, and higher tiers focusing on complex analysis and decision-making. This distributed partial action across tiers reduces overall resource consumption compared to centralized full processing.

Inventive Principle:

Principle #16Partial or excessive action

3Reliability

If data processing is centralized in higher-level modules, then comprehensive decisions are made, but response time to local issues increases

Engineering Contradiction:

Improvedecision qualityVSAvoidresponse time

Core Design Contradiction:

ReliabilityVSSpeed

Solution Approach 1:

The patent segments decision-making authority across hierarchical tiers, enabling lower-tier edge devices to autonomously respond to local issues immediately while simultaneously transmitting data upward for broader context analysis. This segmentation allows parallel local response and centralized oversight, improving response time without sacrificing decision quality.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

Edge devices at lower tiers perform preliminary local processing and can execute immediate responses to critical local conditions before higher-level modules complete their analysis. This preliminary action at the edge ensures rapid local response while higher tiers provide comprehensive validation and broader contextual decisions.

Inventive Principle:

Principle #10Preliminary action

4Quantity of substance

If diverse sensor calibrations from different manufacturers are integrated, then complete data coverage is achieved, but data interpretation accuracy decreases

Engineering Contradiction:

Improvedata coverageVSAvoiddata interpretation accuracy

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The patent introduces intermediary processing layers at each hierarchical tier that normalize and calibrate data from diverse manufacturer sensors. These intermediary modules apply manufacturer-specific calibration corrections and convert heterogeneous sensor readings into standardized formats, enabling accurate integration of complete data coverage from multiple sources without sacrificing interpretation precision.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS20250103923A1Method and system for a dynamic data collection and context-driven actions

Publication Date: 2025.03.27 BLACKBERRY LTD

AI summary

A method at an analytics module on a computing device, the analytics module being at a tier within a hierarchy of analytics modules and data sources, the method including receiving a first data set from a data source or a lower tier analytics module; analyzing the first data set to create a second data set; providing the second data set to at least one higher tier analytics module, the second data set being derived from the first data set; and providing at least one of an inference and an interdiction to the lower tier analytics module