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SMT202

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Data-Driven Sustainable Smart Buildings

SCIS Sch of Computing & Info Sys

Course (UG/PG)

Undergraduate

Offering Unit/Department

SCIS

Course Description

This course explores how analytics and applied Artificial Intelligence (AI) can transform smart buildings into sustainable, efficient, and adaptive environments. Students will learn how to apply machine learning, digital twins, and IoT data to optimise energy use, reduce emissions, and improve occupant well-being. Through real-world case studies, hands-on labs, and a project, students will develop the skills needed for the green buildings of the future.

Course Learning Outcomes

Course Objectives:

Upon completion of the course, students will be able to:

  1. Apply analytics and AI techniques (including machine learning, digital twins, and IoT data) to optimise energy use, reduce emissions, and enhance occupant well-being in smart buildings.

  2. Analyse and interpret real-world smart building data for sustainable and adaptive solutions.

  3. Design and evaluate AI-driven solutions for predictive maintenance, occupant comfort, and environmental quality.

  4. Integrate multiple data sources and technologies to support sustainable smart living applications.

Competencies:

  1. Ability to apply advanced analytics and AI tools in smart building contexts.

  2. Skill in processing and interpreting IoT-generated datasets.

  3. Capability to design and implement predictive models for operational efficiency.

  4. Proficiency in evaluating environmental and occupant comfort metrics using AI methods.

  5. Team-based problem-solving and project execution skills in applied smart living scenarios.

Discipline-Specific Competencies

Data Analytics, Computational Modelling, Research, Design Concepts Generation, Stakeholder Management

SMU Graduate Learning Outcomes

Disciplinary Knowledge, Multidisciplinary Knowledge, Interdisciplinary Knowledge, Critical thinking & problem solving, Innovation and enterprising skills, Collaboration and leadership, Communication, Understanding of global and Asian perspectives, Understanding of sustainability issues

Grading Basis

GRD - Graded

Course Units

1