Dynamic Occupancy Segmentation for RFID-Guided Pathfinding

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Solution Overview

Problem

Existing systems struggle to make real-time or near real-time decisions in environments with mobile entities, such as forklifts and autonomous robots, to prevent accidents and optimize logistics operations, due to challenges in accurately tracking and segmenting the environment and assessing occupancy levels.

Innovation Solution

A method involving RFID-based positioning systems to dynamically segment the environment, identify stationary and mobile entities, and calculate occupancy scores, which are adaptable to changes and noise, allowing for real-time decision-making and pathfinding operations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Speed

If RFID-based positioning systems are used to track mobile entities, then real-time occupancy data can be obtained, but system complexity and noise in positioning data increase

Engineering Contradiction:

Improvereal-time decision making speedVSAvoidpositioning system complexity

Core Design Contradiction:

SpeedVSDevice complexity

Solution Approach 1:

The environment is segmented into multiple zones based on RFID reader coverage areas and entity positions. This segmentation allows the system to process occupancy information in discrete, manageable zones rather than treating the entire environment as a single complex space, enabling real-time processing while reducing overall system complexity

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

A central server acts as an intermediary between RFID readers and pathfinding systems. The server aggregates positioning data from multiple readers, filters noise, determines entity mobility status, and provides processed occupancy scores to pathfinding algorithms, simplifying the overall system architecture while enabling real-time decision-making

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If the environment is dynamically segmented based on entity positions, then occupancy scoring accuracy improves, but computational complexity increases

Engineering Contradiction:

Improveoccupancy scoring accuracyVSAvoidsegmentation computation complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The segmentation of the environment into zones is made dynamic, automatically adjusting as mobile entities move between RFID reader coverage areas. The server continuously updates zone assignments based on current entity positions, maintaining high occupancy scoring accuracy without requiring manual reconfiguration or overly complex static segmentation schemes

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system automatically determines whether entities are stationary or mobile by analyzing their positioning data over time, without requiring external classification. This self-service approach to entity classification reduces computational complexity while maintaining accurate occupancy scoring

Inventive Principle:

Principle #25Self-service

3Stability of the object's composition

If stationary entities are used as markers for segmentation, then segmentation stability improves, but adaptability to changing environments decreases

Engineering Contradiction:

Improvesegmentation stabilityVSAvoidenvironment adaptability

Core Design Contradiction:

Stability of the object's compositionVSAdaptability or versatility

Solution Approach 1:

The system continuously monitors entity positions and mobility status, using this feedback to dynamically adjust segmentation. When mobile entities become stationary, they can become markers for new segments, allowing the system to adapt to changing environmental conditions while maintaining segmentation stability through the use of stationary reference points

Inventive Principle:

Principle #23Feedback

4Reliability

If occupancy scores are calculated for all segments, then decision-making accuracy improves, but processing time increases

Engineering Contradiction:

Improvedecision-making accuracyVSAvoidprocessing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system calculates occupancy scores with high precision for segments that are relevant to current pathfinding operations, while using approximations or cached values for less relevant segments. This local quality approach maintains decision-making accuracy for critical paths while reducing overall processing time

Inventive Principle:

Principle #3Local quality

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Enhances safety by reducing accidents and congestion through dynamic occupancy scoring and segmentation, enabling real-time risk-aware decision-making and optimizing logistics operations.

Implementation Method 1

A method involving RFID-based positioning systems to dynamically segment the environment, identify stationary and mobile entities

Methodology Applied

Scientific EffectRFID (Radio Frequency Identification): Electromagnetic Induction

Data Source

PatentUS12493095B2Dynamic segmentation and occupancy scoring in edge environments with mobile devices for real-time decision making

Publication Date: 2025.12.09 DELL PROD LP

AI summary

Occupancy aware decision-making is disclosed. Positions of entities in an environment are determined. Stationary entities are used as markers to segment the environment. Positions of non-stationary entities are used to determine an occupancy score for each of the segments. Decision making operations, such as pathfinding for mobile entities, can be performed using the occupancy scores of the segments. The occupancy scores and segmentation adapt to changes in the environment.