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Architectural Engineering
Indoor Air Quality (IAQ) Monitoring Systems Training Course
Introduction
Indoor Air Quality (IAQ) Monitoring Systems have become a critical component in modern building management, smart infrastructure, and occupational health compliance. With rising concerns around air pollution, COVID-19 aftermath, carbon emissions, volatile organic compounds (VOCs), and workplace wellness, the demand for real-time IAQ monitoring, sensor-based analytics, and smart ventilation control systems is rapidly increasing. Indoor Air Quality (IAQ) Monitoring Systems Training Course provides a comprehensive foundation in IoT-based air quality monitoring, environmental sensing technologies, data-driven HVAC optimization, and regulatory compliance frameworks aligned with global standards such as ASHRAE, WHO guidelines, and green building certifications.
Participants will gain in-depth knowledge of air quality sensors, PM2.5/PM10 detection, CO₂ monitoring systems, IAQ dashboards, predictive analytics, and cloud-based environmental monitoring platforms. The course emphasizes practical applications in smart buildings, hospitals, schools, industrial environments, and commercial spaces. By integrating AI-powered analytics, edge computing, and sustainable building technologies, learners will be equipped to design, deploy, and manage advanced IAQ monitoring systems that improve health outcomes, energy efficiency, and regulatory compliance.
Programme Curriculum
Indoor Air Quality (IAQ) Monitoring Systems Training Course
Introduction
Indoor Air Quality (IAQ) Monitoring Systems have become a critical component in modern building management, smart infrastructure, and occupational health compliance. With rising concerns around air pollution, COVID-19 aftermath, carbon emissions, volatile organic compounds (VOCs), and workplace wellness, the demand for real-time IAQ monitoring, sensor-based analytics, and smart ventilation control systems is rapidly increasing. Indoor Air Quality (IAQ) Monitoring Systems Training Course provides a comprehensive foundation in IoT-based air quality monitoring, environmental sensing technologies, data-driven HVAC optimization, and regulatory compliance frameworks aligned with global standards such as ASHRAE, WHO guidelines, and green building certifications.
Participants will gain in-depth knowledge of air quality sensors, PM2.5/PM10 detection, CO₂ monitoring systems, IAQ dashboards, predictive analytics, and cloud-based environmental monitoring platforms. The course emphasizes practical applications in smart buildings, hospitals, schools, industrial environments, and commercial spaces. By integrating AI-powered analytics, edge computing, and sustainable building technologies, learners will be equipped to design, deploy, and manage advanced IAQ monitoring systems that improve health outcomes, energy efficiency, and regulatory compliance.
Course Duration
5 days
Course Objectives
Understand Indoor Air Quality (IAQ) fundamentals & environmental health impact
Master IoT-based air quality monitoring systems architecture
Analyze PM2.5, PM10, CO₂, VOCs, CO gas detection technologies
Implement smart sensor calibration and deployment techniques
Design real-time IAQ data acquisition systems
Apply cloud-based environmental data analytics platforms
Integrate AI and machine learning for air quality prediction
Optimize HVAC systems using IAQ sensor feedback loops
Ensure compliance with WHO, EPA, and ASHRAE standards
Develop smart building automation systems for IAQ control
Utilize edge computing for real-time air quality processing
Build dashboard visualization and IoT monitoring interfaces
Implement sustainable green building IAQ strategies
Target Audience
Environmental Engineers
HVAC Engineers & Technicians
IoT Developers & System Integrators
Facility Managers & Building Operators
Occupational Health & Safety Professionals
Smart City Planners & Urban Developers
Sustainability & ESG Consultants
University Students & Research Scholars in Environmental Sciences
Course Modules
Module 1: Fundamentals of Indoor Air Quality (IAQ)
IAQ definitions and global standards
Air pollutants: biological, chemical, particulate
Health impacts of poor indoor air quality
Air circulation and ventilation principles
IAQ measurement parameters
Case Study: Office building experiencing high sick-leave rates due to poor ventilation and CO₂ buildup.
Module 2: Air Quality Sensors & Technologies
PM2.5/PM10 sensor technologies
Gas sensors (CO, CO₂, VOC detection)
Calibration techniques
Sensor accuracy and drift management
Sensor fusion systems
Case Study: Hospital deploying multi-sensor IAQ system to reduce airborne infection risks.
Module 3: IoT Architecture for IAQ Systems
IoT device integration for air monitoring
Wireless communication protocols
Edge vs cloud processing
System scalability design
Data transmission security
Case Study: Smart campus implementing IoT-based air quality network across classrooms.
Module 4: Data Analytics & Visualization
IAQ data collection frameworks
Real-time dashboards
Trend analysis & reporting
Cloud platforms
Data-driven decision systems
Case Study: Shopping mall optimizing ventilation using IAQ analytics dashboard.
Module 5: AI & Predictive Air Quality Modeling
Machine learning for pollution prediction
Pattern recognition in air quality data
Predictive maintenance of HVAC systems
Anomaly detection systems
AI-based alert systems
Case Study: Industrial plant predicting VOC spikes using AI models.
Module 6: HVAC Integration & Smart Control Systems
HVAC automation using IAQ feedback
Demand-controlled ventilation (DCV)
Energy efficiency optimization
Smart thermostats integration
Airflow optimization techniques
Case Study: Corporate office reducing energy cost by 30% using IAQ-driven HVAC control.
Module 7: Compliance, Standards & Green Building Certification
ASHRAE ventilation standards
LEED & WELL certification requirements
Indoor environmental quality compliance
Occupational safety regulations
Environmental reporting systems
Case Study: LEED-certified green building achieving top IAQ rating.
Module 8: Smart Building & Future IAQ Technologies
Smart city integration
Edge AI for real-time monitoring
Blockchain for environmental data integrity
Autonomous ventilation systems
Future trends in IAQ innovation
Case Study: Smart city deploying city-wide IAQ monitoring network with predictive alerts.
Training Methodology
This course employs a participatory and hands-on approach to ensure practical learning, including:
Interactive lectures and presentations.
Group discussions and brainstorming sessions.
Hands-on exercises using real-world datasets.
Role-playing and scenario-based simulations.
Analysis of case studies to bridge theory and practice.
Peer-to-peer learning and networking.
Expert-led Q&A sessions.
Continuous feedback and personalized guidance.
Register as a group from 3 participants for a Discount
Upon successful completion of this training, participants will be issued with a globally- recognized certificate.
Tailor-Made Course
We also offer tailor-made courses based on your needs.
Key Notes
a. The participant must be conversant with English.
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
c. Course duration is flexible and the contents can be modified to fit any number of days.
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
e. One-year post-training support Consultation and Coaching provided after the course.
f. Payment should be done at least a week before commence of the training, to FINESKILL TRAINING CENTER account, as indicated in the invoice so as to enable us prepare better for you.