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Machine Learning for Predictive Maintenance in Buildings

COURSE NO: B01-005
PDH CREDIT: 1
Machine Learning for Predictive Maintenance in Buildings
Course Highlights

This online engineering CPD course examines machine learning applications for predictive maintenance in modern building systems.
 

Predictive maintenance uses operational data, sensors, and machine learning algorithms to identify equipment degradation and predict potential failures before they occur.
 

Building equipment performance varies with operating conditions, equipment age, usage patterns, and system interactions, requiring continuous data collection and analysis to identify anomalies and optimize maintenance activities.
 

This course covers machine learning fundamentals, data collection strategies, building automation systems, IoT sensors, and predictive maintenance applications for HVAC, electrical, elevator, and plumbing systems. It also emphasizes practical implementation strategies for reducing equipment downtime, maintenance costs, and unplanned failures while improving building performance.
 

This 1 CPD online course is applicable to mechanical and electrical engineers, as well as other technical professionals who are interested in learning more about machine learning-based predictive maintenance for building systems.

Learning Objectives

This PE continuing education course is intended to provide you with the following specific knowledge and skills:

  • Understanding the evolution of building maintenance from reactive to machine learning-based predictive strategies
  • Familiarizing with machine learning concepts including supervised learning, anomaly detection, and time-series analysis
  • Learning how building automation systems and IoT sensors support predictive maintenance data collection
  • Understanding predictive maintenance applications for HVAC equipment and common failure modes
  • Familiarizing with electrical fault prediction using transformer, power quality, and thermal monitoring
  • Learning how predictive maintenance is applied to elevator and vertical transportation systems
  • Understanding implementation strategies, pilot projects, phased deployment, and CMMS integration
  • Familiarizing with BIM and digital twin applications that enhance predictive maintenance capabilities
  • Understanding edge computing architectures and their benefits for building maintenance systems
  • Learning about emerging technologies including federated learning, large language models, and autonomous maintenance
Course Document
In this professional engineering CEU course, you need to review the course document titled, “Machine Learning for Predictive Maintenance in Buildings”, prepared by Amr Abouseif.
To view, print and study the course document, please click on the following link(s):
MACHINE LEARNING FOR PREDICTIVE MAINTENANCE IN BUILDINGS (953 KB)
Course Quiz
Once you complete your course review, you need to take a multiple-choice quiz consisting of ten (10) questions to earn 1 CPD credits. The quiz will be based on the entire document.
The minimum passing score is 70%. There is no time limit on the quiz, and you can take it multiple times until you pass at no additional cost.
Certificate of Completion

Upon successful completion of the quiz, print your Certificate of Completion instantly. (Note: if you are paying by check or money order, you will be able to print it after we receive your payment.) For your convenience, we will also email it to you. Please note that you can log in to your account at any time to access and print your Certificate of Completion.

To buy the course and take the quiz, please click on: