Edge Node Sensor System for Real-Time Forklift Hazard Detection

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Solution Overview

Problem

Logistics in environments like warehouses are challenging due to the complexity of managing multiple mobile and stationary objects, which can lead to accidents and unsafe interactions, especially with forklifts, as their movements are difficult to coordinate effectively.

Innovation Solution

A system utilizing edge nodes equipped with sensors and machine learning models to detect cornering events and other hazards, enabling real-time monitoring and decision-making by processing data from both local and central nodes, and generating alerts or taking automated actions to prevent accidents.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If multiple mobile devices operate simultaneously in a warehouse environment, then productivity increases, but the risk of accidents and unsafe interactions increases

Engineering Contradiction:

Improvelogistics operations efficiencyVSAvoidaccident risk

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The system continuously monitors mobile device trajectories and provides real-time feedback about dangerous cornering events. The monitoring system detects cornering maneuvers and communicates hazard information back to operators, enabling them to adjust their behavior and avoid accidents while maintaining operational efficiency.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent introduces an intermediary monitoring system that acts as a mediator between multiple mobile device operators. This system collects trajectory data, analyzes cornering events, and provides coordinated information to all operators, enabling them to navigate safely without direct communication between each operator.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If forklift operators communicate with each other to coordinate movement, then safety improves, but operational complexity increases

Engineering Contradiction:

Improvecoordination safetyVSAvoidcommunication coordination complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The monitoring system enables operators to self-regulate their behavior by providing them with objective information about cornering events and hazards. Each operator receives tailored feedback about their own driving patterns and the environmental conditions, allowing them to make safe decisions independently without complex inter-operator communication.

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If forklifts perform various mobile maneuvers to access different locations, then operational versatility improves, but the risk of dangerous events increases

Engineering Contradiction:

Improvemaneuver capabilityVSAvoiddangerous event risk

Core Design Contradiction:

Adaptability or versatilityVSObject-affected harmful factors

Solution Approach 1:

The system performs preliminary analysis of trajectory data to identify potential cornering hazards before dangerous events occur. By detecting cornering maneuvers in advance and providing warning information to operators, the system enables them to take corrective action before accidents happen, allowing versatile maneuvers to be performed safely.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20230368129A1Unsupervised learning for real-time detection of events of far edge mobile device trajectories

Publication Date: 2023.11.16 DELL PROD LP

AI summary

An event driven detection model is disclosed. A model operates at a node using data generated by sensors associated with the node to identify events. The events are provided to a model configure to infer whether the event is non-normative. When a non-normative event is inferred by the model, a decision may be made and performed.