Term 252

Predictive Maintenance and Anomaly Detection for Fluid Pipeline Systems

Project Type: Self-Initiated

Project Description

This project develops a simple, low-cost leak detection platform for fluid pipeline systems using a closed-loop flow setup. Pressure and flow sensors monitor the pipeline in real time, and when a leak occurs, the system detects abnormal changes, displays the condition on a dashboard, and supports quick warning for safer operation and maintenance.


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Project Team

Ahmed Naif Alessa
Ahmed Naif Alessa
PETE
Murtdha Ahmed Alramadhan
Murtdha Ahmed Alramadhan
EE
Mohammed Mohsin Hamadah
Mohammed Mohsin Hamadah
EE
Hussain Ahmed Alabdulali
Hussain Ahmed Alabdulali
ICS
Abdulaziz Sameer Alabdulqader
Abdulaziz Sameer Alabdulqader
PETE
Reda Basem Alali
Reda Basem Alali
ICS

Team Coach

DR. Omar Hammad
DR. Omar Hammad
Assistant Professor

Info. & Computer Science Dept.

SDAIA-KFUPM Joint Research Center for Artificial Intelligence