Construction Fleet Proximity Tracking for Correlated Work Cycles
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Solution Overview
Problem
Existing systems fail to effectively track and manage the material movement and coordination of multiple independent machines in earthmoving and earthworks operations, leading to inefficiencies and lack of oversight in productivity and payload activities.
Innovation Solution
A method and system for managing a fleet of machines by correlating telematics data to identify positional and temporal proximity between machines, associating work cycles, and deriving payload data to enhance productivity and coordination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple independent machines are used for earthmoving operations, then productivity and material movement capacity increase, but coordination difficulty and lack of oversight increase
Solution Approach 1:
The patent merges data from multiple independent machines (load sensors, GPS, telematics) into a unified centralized system that tracks material movement across all machines, enabling coordinated management while maintaining individual machine productivity
Solution Approach 2:
The system introduces a centralized management platform that acts as an intermediary between machines, collecting and processing telematics data to provide real-time coordination and oversight without requiring direct machine-to-machine communication
2Loss of information
If separate machine data sets are collected, then individual machine performance can be monitored, but material movement tracking becomes difficult
Solution Approach 1:
The centralized system serves multiple functions simultaneously: it collects individual machine performance data, tracks material movement across the fleet, monitors payload activities, and provides coordination oversight, eliminating the need for separate tracking systems
Solution Approach 2:
The system continuously collects telematics data from all machines, processes it to identify material movement patterns, and provides real-time feedback on coordination status and productivity metrics to improve overall operation efficiency
3Productivity
If machines operate independently, then operational flexibility is maintained, but idle time and coordination inefficiency increase
Solution Approach 1:
The system dynamically adjusts machine coordination based on real-time telematics data, automatically identifying when machines are available and optimizing their assignment to minimize idle time while preserving operational flexibility
Solution Approach 2:
Real-time feedback from load sensors and GPS data enables the system to monitor machine status and material movement continuously, allowing dynamic optimization of machine assignment and reducing idle time through coordinated scheduling
Data Source
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AI summary
Systems and methods are disclosed for management of a fleet of machines operating in a construction and/or civil engineering project. Telematics data is received from first and second machines at regular intervals. Positional and temporal proximity is determined between the first and second machines based at least in part on an analysis of the telematics data, indicating for example that the first machine is within a predetermined maximum distance of the second machine for at least a predetermined minimum duration. If there is positional and temporal proximity, work cycle data is received from the machines and is correlated. If there is a correlation in the work cycle data, an association is generated between the first and second machines and the association is applied to enable inheritance of material type between the first and second machines to support automated mass haul monitoring, and generate and implement a construction plan.