Fleet Asset Visualization Using Gateway-Filtered Sensor Data
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Solution Overview
Problem
Managing and analyzing vast amounts of sensor data from diverse physical assets in a fleet is challenging due to complexity and diversity, making it difficult to monitor and diagnose issues in real-time, especially with existing systems struggling to efficiently process and display data from multiple sensors across various locations.
Innovation Solution
A gateway device attached to each physical asset collects sensor data from various sensors and transmits it to a management server system, which generates interactive graphical user interfaces for real-time monitoring and management, including filters and visualizations to identify issues and trends, enabling efficient data processing and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data is collected from multiple physical assets in real-time, then monitoring capability is improved, but data processing complexity increases
Solution Approach 1:
The system segments the fleet management functionality into distributed gateway devices, each handling data collection and preliminary processing for specific physical assets. This segmentation allows real-time monitoring of multiple assets while distributing processing complexity across multiple independent units rather than concentrating it in a single centralized system.
Solution Approach 2:
Gateway devices serve as intermediary components between physical assets and the centralized management server. These gateways collect sensor data, perform initial filtering and processing, and transmit only relevant processed data to the server, thereby reducing the complexity of data processing at the centralized level while maintaining comprehensive monitoring capability.
2Loss of time
If real-time data processing is implemented across the fleet, then issue identification speed is improved, but computational resources required increase
Solution Approach 1:
The gateway devices perform preliminary data processing, filtering, and anomaly detection locally before transmitting data to the centralized server. This preliminary action enables faster local issue identification while reducing the volume of data requiring intensive computational processing at the server level, thereby balancing response speed with computational resource consumption.
Solution Approach 2:
The system implements partial real-time processing at the gateway level for immediate anomaly detection, while more comprehensive analysis is performed selectively based on detected issues. This approach provides sufficient issue identification speed for critical problems without requiring excessive computational resources for all data processing.
3Measurement precision
If comprehensive sensor data is collected from all assets, then diagnostic accuracy is improved, but data transmission bandwidth requirements increase
Solution Approach 1:
The gateway devices extract and transmit only the most relevant diagnostic data and anomalies to the centralized server, rather than transmitting all raw sensor data. This selective extraction maintains diagnostic accuracy by focusing on critical information while significantly reducing the bandwidth requirements for data transmission across the network.
Solution Approach 2:
The system changes the parameters of transmitted data by processing and aggregating sensor readings into meaningful diagnostic indicators and anomaly flags. This parameter transformation converts high-volume raw sensor data into compact, information-dense diagnostic data that maintains accuracy while reducing transmission bandwidth requirements.
Data Source
AI summary
A management server system may obtain sensor data generated by a plurality of sensors from a plurality of gateway devices. The sensor data may be associated with a plurality of vehicles. The management server system may identify, for each vehicle of the plurality of vehicles, a subset of the sensor data associated with a particular vehicle. The management server system may generate, in real time, for each vehicle of the plurality of vehicles, a virtual representation of the particular vehicle based on the subset of the sensor data associated with the particular vehicle. The management server system may generate a user interface that includes visualizations of virtual representations of the plurality of vehicles. The management server system may update, in real time, the visualizations of the virtual representations of the plurality of vehicles based on obtaining additional sensor data from the plurality of gateway devices.