Thesis Outlines

• Each chapter will have introduction, literature review and conclusion
• Thesis template

1. Chapter 1: Machine learning applications in Sewer Systems
   1. Introduction
   2. Literature Review
2. Chapter 2: Collection Systems Asset Management
   1. Deterioration analysis
   2. Sewer pipe condition assessment
3. Chapter 3: Sewer pipe assessment methods and LoF calculation
   1. Different methods people use to investigate the Sewer pipe conditions
      1. CCTV
      2. Laser
      3. Pipe leakage
      4. Machine learning
   2. Different scoring methods
      1. NASSCO PACP
      2. SCREAM
      3. Foto (Danish)
   3. Different metrics used to evaluate sewer models
   4. Different machine learning defect models
      1. Binary label (defect vs non defect)
      2. Multi label
      3. Object detection
      4. Segmentation
   5. Sewer pipe condition model
      1. Determine correlation between environmental condition and pipe condition
      2. Predict the likelihood of defects occuring in the uninspected pipe using feature engineering
   6. LoF calculation improvement
      1. Integrate Sewer modeling results
   7. Results
   8. Discussions
4. Chapter 4: CoF calculation
   1. COF for sewer pipe
5. Chapter 5: Risk calculation
   1. LoF * COF ??
6. Chapter 6: Replacement/Rehab scheduling
7. Chapter 7: Climate change impacts on LoF and CoF
   1. Climate change model