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
PETE
Murtdha Ahmed Alramadhan
EE
Mohammed Mohsin Hamadah
EE
Hussain Ahmed Alabdulali
ICS
Abdulaziz Sameer Alabdulqader
PETE
Reda Basem Alali
ICSTeam Coach
DR. Omar Hammad
Assistant ProfessorInfo. & Computer Science Dept.
SDAIA-KFUPM Joint Research Center for Artificial Intelligence