The following are models that will provide guidelines for the next steps in our design
PROCESS MODEL
Wireless Sensor Network
Implement a network of sensors through train cabins to monitor and collect real-time data
Data statistics could include temperature, pressure, force of vibration, and any abnormalities
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Data Collection/Transmission
Sensors emit data that is then transmitted to a database through low-latency communication protocols
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Data Storage
Collected data is then stored in a database or cloud-based system
Raw data is then preprocessed to be clean and normalized
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AI program system
A machine learning algorithm that performs predictive maintenance takes in the data
Program monitors the data in real-time to visualise the system's health and status
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Feedback & Control System
Alerts from the AI program indicate when a maintenance team is needed to repair or solve any issues that are detected
Control integration allows for the system to adjust train operations, for example, slowing a train down due to maintenance on tracks further ahead (or any other detected risk)
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System User Interface
A user interface that allows operators to access the real-time data analytics of the system health and perform actions based off the results
SYSTEM MODEL
Sensor
Collects data and information regarding train conditions
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Transmitter
Delivers gathered sensor information to data storage
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Data Storage
Stores relevant sensor data and information
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AI program system
Sources and analyzes information from data storage, then formulates maintenance solution accordingly
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Feedback & Control System
Returns analyzed and processed information from AI program system
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System User Interface
Allows user to observe and influence information recieved from control system