1. Introduction
  1.1 Background and motivation
  1.2 Objectives of the project
2. Literature review
  2.1 Process monitoring and control techniques
  2.2 Artificial intelligence in chemical engineering
  2.3 Sensor data integration and analysis
3. AI-based process monitoring
  3.1 Data preprocessing and feature selection
  3.2 Machine learning algorithms for process monitoring
  3.3 Neural network-based monitoring systems
4. Case studies and applications
  4.1 Monitoring of chemical reactors
  4.2 Fault detection in process equipment
  4.3 Real-time process optimization using AI
5. Performance evaluation
  5.1 Robustness and reliability analysis
  5.2 Comparison with traditional monitoring techniques