AI/ML Based Applications in Civil Engineering
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Follow on Instagram for UpdatesAI/ML Based Applications in Civil Engineering Syllabus — Unit-wise Content
The official GTU curriculum for AI/ML Based Applications in Civil Engineering (subject code ME02014081) as prescribed for C(EA · Semester 2 divides the course into 5 units, covering 54 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (ME02014081)Unit 1 INTRODUCTION TO MACHINE LEARNING
- Machine Learning Basics: Data Collection
- Data Management
- Big data
- taxonomy of machine learning algorithms
- Supervised Learning: Classification – Bayesian Classifier
- K-nearest Neighbours
- Regression- Linear Regression
- Multivariate Regression
- Logistic regression
- Support Vector Machine (SVM) Algorithm
- Unsupervised Learning: Clustering- K-means clustering algorithm and Hierarchical clustering algorithm
- Reinforcement Learning: Q-Learning algorithm
Unit 2 DATA COLLECTION APPARATUSES
- Type of data sources
- Types of data
- Types of sensors
- Introduction to microcontrollers
- data communication protocols
- Cloud storage and cloud computing
- Local server setup
- Cloud server setup
- Introduction to Python
- Introduction to Django server
- Database setup
Unit 3 APPLICATIONS IN CIVIL ENGINEERING
- Intelligent Transportation systems
- smart mobility
- shared mobility
- Mobility as a Service (MaaS)
- Real-time data monitoring
- Structural health monitoring
- Fire resistance evaluation of structures
- automation in water resource management
- Water quality monitoring
- water distribution system monitoring
- air and noise pollution monitoring
- Rainfall-runoff modelling
- Climate change monitoring
- Soil liquefaction
- Forecasting foundation related parameters
- Building occupancy modelling
- Building information modelling
- Energy demand prediction
- Predictive maintenance of equipment
- roads and buildings
Unit 4 APPLICATION PART I
- DATA COLLECTION AND MANAGEMENT Image processing for real time applications in Civil Engineering
- Description of available database across specialisations
- Selection of sensors and microcontroller
- Integration of sensors with Edge-device
- Programming of Edge-devices
- Programming of server in Django framework
- Collection of sensor data and storing to Database
- Cloud computing
Unit 5 APPLICATION PART II
- BIG DATA ANALYSIS Selecting the appropriate ML algorithm for analysis
- Data Processing
- Analysing the importance of each variable in decision making, and Analysis of processed data
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